Monte Carlo modelling of large scale NORM sources using MCNP.

PubMed

Wallace, J D

2013-12-01

The representative Monte Carlo modelling of large scale planar sources (for comparison to external environmental radiation fields) is undertaken using substantial diameter and thin profile planar cylindrical sources. The relative impact of source extent, soil thickness and sky-shine are investigated to guide decisions relating to representative geometries. In addition, the impact of source to detector distance on the nature of the detector response, for a range of source sizes, has been investigated. These investigations, using an MCNP based model, indicate a soil cylinder of greater than 20 m diameter and of no less than 50 cm depth/height, combined with a 20 m deep sky section above the soil cylinder, are needed to representatively model the semi-infinite plane of uniformly distributed NORM sources. Initial investigation of the effect of detector placement indicate that smaller source sizes may be used to achieve a representative response at shorter source to detector distances. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Experimental and operational modal analysis of a laboratory scale model of a tripod support structure.

NASA Astrophysics Data System (ADS)

Luczak, M. M.; Mucchi, E.; Telega, J.

2016-09-01

The goal of the research is to develop a vibration-based procedure for the identification of structural failures in a laboratory scale model of a tripod supporting structure of an offshore wind turbine. In particular, this paper presents an experimental campaign on the scale model tested in two stages. Stage one encompassed the model tripod structure tested in air. The second stage was done in water. The tripod model structure allows to investigate the propagation of a circumferential representative crack of a cylindrical upper brace. The in-water test configuration included the tower with three bladed rotor. The response of the structure to the different waves loads were measured with accelerometers. Experimental and operational modal analysis was applied to identify the dynamic properties of the investigated scale model for intact and damaged state with different excitations and wave patterns. A comprehensive test matrix allows to assess the differences in estimated modal parameters due to damage or as potentially introduced by nonlinear structural response. The presented technique proves to be effective for detecting and assessing the presence of representative cracks.

Statistical model of exotic rotational correlations in emergent space-time

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Craig; Kwon, Ohkyung; Richardson, Jonathan

2017-06-06

A statistical model is formulated to compute exotic rotational correlations that arise as inertial frames and causal structure emerge on large scales from entangled Planck scale quantum systems. Noncommutative quantum dynamics are represented by random transverse displacements that respect causal symmetry. Entanglement is represented by covariance of these displacements in Planck scale intervals defined by future null cones of events on an observer's world line. Light that propagates in a nonradial direction inherits a projected component of the exotic rotational correlation that accumulates as a random walk in phase. A calculation of the projection and accumulation leads to exact predictionsmore » for statistical properties of exotic Planck scale correlations in an interferometer of any configuration. The cross-covariance for two nearly co-located interferometers is shown to depart only slightly from the autocovariance. Specific examples are computed for configurations that approximate realistic experiments, and show that the model can be rigorously tested.« less

GEWEX Continental-scale International Project (GCIP)

NASA Technical Reports Server (NTRS)

Try, Paul

1993-01-01

The Global Energy and Water Cycle Experiment (GEWEX) represents the World Climate Research Program activities on clouds, radiation, and land-surface processes. The goal of the program is to reproduce and predict, by means of suitable models, the variations of the global hydrological regime and its impact on atmospheric and oceanic dynamics. However, GEWEX is also concerned with variations in regional hydrological processes and water resources and their response to changes in the environment such as increasing greenhouse gases. In fact, GEWEX contains a major new international project called the GEWEX Continental-scale International Project (GCIP), which is designed to bridge the gap between the small scales represented by hydrological models and those scales that are practical for predicting the regional impacts of climate change. The development and use of coupled mesoscale-hydrological models for this purpose is a high priority in GCIP. The objectives of GCIP are presented.

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Heterogeneity and scaling land-atmospheric water and energy fluxes in climate systems

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behavior of hydrologic responses during rain events and between rain events. The third experiment compared the hydrologic responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2 - 3 times the correlation length of the process. For natural catchments this appears to be about 1 - 2 sq km. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are nonlinear, then lumping results in biases; otherwise a one-dimensional model based on 'equivalent' parameters provides quite good results. Further research is needed to fully understand these conditions.

SUBGRID PARAMETERIZATION OF SNOW DISTRIBUTION FOR AN ENERGY AND MASS BALANCE SNOW COVER MODEL. (R824784)

EPA Science Inventory

Representation of sub-element scale variability in snow accumulation and ablation is increasingly recognized as important in distributed hydrologic modelling. Representing sub-grid scale variability may be accomplished through numerical integration of a nested grid or through a l...

An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified Representation of Subgrid-Scale Turbulence and Convection

NASA Astrophysics Data System (ADS)

Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Schneider, Tapio; Teixeira, João.

2018-03-01

Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection—such as that they adjust instantaneously to changes in resolved-scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass-flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.

An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection

PubMed Central

Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Teixeira, João

2018-01-01

Abstract Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle. PMID:29780442

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2011-01-01

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

Using a Virtual Experiment to Analyze Infiltration Process from Point to Grid-cell Size Scale

NASA Astrophysics Data System (ADS)

Barrios, M. I.

2013-12-01

The hydrological science requires the emergence of a consistent theoretical corpus driving the relationships between dominant physical processes at different spatial and temporal scales. However, the strong spatial heterogeneities and non-linearities of these processes make difficult the development of multiscale conceptualizations. Therefore, scaling understanding is a key issue to advance this science. This work is focused on the use of virtual experiments to address the scaling of vertical infiltration from a physically based model at point scale to a simplified physically meaningful modeling approach at grid-cell scale. Numerical simulations have the advantage of deal with a wide range of boundary and initial conditions against field experimentation. The aim of the work was to show the utility of numerical simulations to discover relationships between the hydrological parameters at both scales, and to use this synthetic experience as a media to teach the complex nature of this hydrological process. The Green-Ampt model was used to represent vertical infiltration at point scale; and a conceptual storage model was employed to simulate the infiltration process at the grid-cell scale. Lognormal and beta probability distribution functions were assumed to represent the heterogeneity of soil hydraulic parameters at point scale. The linkages between point scale parameters and the grid-cell scale parameters were established by inverse simulations based on the mass balance equation and the averaging of the flow at the point scale. Results have shown numerical stability issues for particular conditions and have revealed the complex nature of the non-linear relationships between models' parameters at both scales and indicate that the parameterization of point scale processes at the coarser scale is governed by the amplification of non-linear effects. The findings of these simulations have been used by the students to identify potential research questions on scale issues. Moreover, the implementation of this virtual lab improved the ability to understand the rationale of these process and how to transfer the mathematical models to computational representations.

Validity of thermally-driven small-scale ventilated filling box models

NASA Astrophysics Data System (ADS)

Partridge, Jamie L.; Linden, P. F.

2013-11-01

The majority of previous work studying building ventilation flows at laboratory scale have used saline plumes in water. The production of buoyancy forces using salinity variations in water allows dynamic similarity between the small-scale models and the full-scale flows. However, in some situations, such as including the effects of non-adiabatic boundaries, the use of a thermal plume is desirable. The efficacy of using temperature differences to produce buoyancy-driven flows representing natural ventilation of a building in a small-scale model is examined here, with comparison between previous theoretical and new, heat-based, experiments.

A Multi-Scale, Integrated Approach to Representing Watershed Systems

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy; Kim, Jongho; Fatichi, Simone; Katopodes, Nikolaos

2014-05-01

Understanding and predicting process dynamics across a range of scales are fundamental challenges for basic hydrologic research and practical applications. This is particularly true when larger-spatial-scale processes, such as surface-subsurface flow and precipitation, need to be translated to fine space-time scale dynamics of processes, such as channel hydraulics and sediment transport, that are often of primary interest. Inferring characteristics of fine-scale processes from uncertain coarse-scale climate projection information poses additional challenges. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion, and sediment transport, tRIBS+VEGGIE-FEaST. The model targets to take the advantage of the current generation of wealth of data representing watershed topography, vegetation, soil, and landuse, as well as to explore the hydrological effects of physical factors and their feedback mechanisms over a range of scales. We illustrate how the modeling system connects precipitation-hydrologic runoff partition process to the dynamics of flow, erosion, and sedimentation, and how the soil's substrate condition can impact the latter processes, resulting in a non-unique response. We further illustrate an approach to using downscaled climate change information with a process-based model to infer the moments of hydrologic variables in future climate conditions and explore the impact of climate information uncertainty.

The Rosenberg Self-Esteem Scale: a bifactor answer to a two-factor question?

PubMed

McKay, Michael T; Boduszek, Daniel; Harvey, Séamus A

2014-01-01

Despite its long-standing and widespread use, disagreement remains regarding the structure of the Rosenberg Self-Esteem Scale (RSES). In particular, concern remains regarding the degree to which the scale assesses self-esteem as a unidimensional or multidimensional (positive and negative self-esteem) construct. Using a sample of 3,862 high school students in the United Kingdom, 4 models were tested: (a) a unidimensional model, (b) a correlated 2-factor model in which the 2 latent variables are represented by positive and negative self-esteem, (c) a hierarchical model, and (d) a bifactor model. The totality of results including item loadings, goodness-of-fit indexes, reliability estimates, and correlations with self-efficacy measures all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as "grouping" factors rather than as representative of latent constructs. Accordingly, this study supports the unidimensionality of the RSES and the scoring of all 10 items to produce a global self-esteem score.

The global reference atmospheric model, mod 2 (with two scale perturbation model)

NASA Technical Reports Server (NTRS)

Justus, C. G.; Hargraves, W. R.

1976-01-01

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Tip vortices in the actuator line model

NASA Astrophysics Data System (ADS)

Martinez, Luis; Meneveau, Charles

2017-11-01

The actuator line model (ALM) is a widely used tool to represent the wind turbine blades in computational fluid dynamics without the need to resolve the full geometry of the blades. The ALM can be optimized to represent the `correct' aerodynamics of the blades by choosing an appropriate smearing length scale ɛ. This appropriate length scale creates a tip vortex which induces a downwash near the tip of the blade. A theoretical frame-work is used to establish a solution to the induced velocity created by a tip vortex as a function of the smearing length scale ɛ. A correction is presented which allows the use of a non-optimal smearing length scale but still provides the downwash which would be induced using the optimal length scale. Thanks to the National Science Foundation (NSF) who provided financial support for this research via Grants IGERT 0801471, IIA-1243482 (the WINDINSPIRE project) and ECCS-1230788.

Static Aeroelastic Scaling and Analysis of a Sub-Scale Flexible Wing Wind Tunnel Model

NASA Technical Reports Server (NTRS)

Ting, Eric; Lebofsky, Sonia; Nguyen, Nhan; Trinh, Khanh

2014-01-01

This paper presents an approach to the development of a scaled wind tunnel model for static aeroelastic similarity with a full-scale wing model. The full-scale aircraft model is based on the NASA Generic Transport Model (GTM) with flexible wing structures referred to as the Elastically Shaped Aircraft Concept (ESAC). The baseline stiffness of the ESAC wing represents a conventionally stiff wing model. Static aeroelastic scaling is conducted on the stiff wing configuration to develop the wind tunnel model, but additional tailoring is also conducted such that the wind tunnel model achieves a 10% wing tip deflection at the wind tunnel test condition. An aeroelastic scaling procedure and analysis is conducted, and a sub-scale flexible wind tunnel model based on the full-scale's undeformed jig-shape is developed. Optimization of the flexible wind tunnel model's undeflected twist along the span, or pre-twist or wash-out, is then conducted for the design test condition. The resulting wind tunnel model is an aeroelastic model designed for the wind tunnel test condition.

Interactive coupling of regional climate and sulfate aerosol models over eastern Asia

NASA Astrophysics Data System (ADS)

Qian, Yun; Giorgi, Filippo

1999-03-01

The NCAR regional climate model (RegCM) is interactively coupled to a simple radiatively active sulfate aerosol model over eastern Asia. Both direct and indirect aerosol effects are represented. The coupled model system is tested for two simulation periods, November 1994 and July 1995, with aerosol sources representative of present-day anthropogenic sulfur emissions. The model sensitivity to the intensity of the aerosol source is also studied. The main conclusions from our work are as follows: (1) The aerosol distribution and cycling processes show substantial regional spatial variability, and temporal variability varying on a range of scales, from the diurnal scale of boundary layer and cumulus cloud evolution to the 3-10 day scale of synoptic scale events and the interseasonal scale of general circulation features; (2) both direct and indirect aerosol forcings have regional effects on surface climate; (3) the regional climate response to the aerosol forcing is highly nonlinear, especially during the summer, due to the interactions with cloud and precipitation processes; (4) in our simulations the role of the aerosol indirect effects is dominant over that of direct effects; (5) aerosol-induced feedback processes can affect the aerosol burdens at the subregional scale. This work constitutes the first step in a long term research project aimed at coupling a hierarchy of chemistry/aerosol models to the RegCM over the eastern Asia region.

Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013

USGS Publications Warehouse

Driscoll, Jessica; Hay, Lauren E.; Bock, Andrew R.

2017-01-01

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.

Spiral model of pitch

NASA Astrophysics Data System (ADS)

Miller, James D.

2003-10-01

A spiral model of pitch interrelates tone chroma, tone height, equal temperament scales, and a cochlear map. Donkin suggested in 1870 that the pitch of tones could be well represented by an equiangular spiral. More recently, the cylindrical helix has been popular for representing tone chroma and tone height. Here it is shown that tone chroma, tone height, and cochlear position can be conveniently related to tone frequency via a planar spiral. For this ``equal-temperament spiral,'' (ET Spiral) tone chroma is conceived as a circular array with semitones at 30° intervals. The frequency of sound on the cent scale (re 16.351 Hz) is represented by the radius of the spiral defined by r=(1200/2π)θr, where θr is in radians. By these definitions, one revolution represents one octave, 1200 cents, 30° represents a semitone, the radius relates θ to cents in accordance with equal temperament (ET) tuning, and the arclength of the spiral matches the mapping of sound frequency to the basilar membrane. Thus, the ET Spiral gives tone chroma as θ, tone height as the cent scale, and the cochlear map as the arclength. The possible implications and directions for further work are discussed.

Coupling scales for modelling heavy metal vaporization from municipal solid waste incineration in a fluid bed by CFD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soria, José, E-mail: jose.soria@probien.gob.ar; Gauthier, Daniel; Flamant, Gilles

2015-09-15

Highlights: • A CFD two-scale model is formulated to simulate heavy metal vaporization from waste incineration in fluidized beds. • MSW particle is modelled with the macroscopic particle model. • Influence of bed dynamics on HM vaporization is included. • CFD predicted results agree well with experimental data reported in literature. • This approach may be helpful for fluidized bed reactor modelling purposes. - Abstract: Municipal Solid Waste Incineration (MSWI) in fluidized bed is a very interesting technology mainly due to high combustion efficiency, great flexibility for treating several types of waste fuels and reduction in pollutants emitted with themore » flue gas. However, there is a great concern with respect to the fate of heavy metals (HM) contained in MSW and their environmental impact. In this study, a coupled two-scale CFD model was developed for MSWI in a bubbling fluidized bed. It presents an original scheme that combines a single particle model and a global fluidized bed model in order to represent the HM vaporization during MSW combustion. Two of the most representative HM (Cd and Pb) with bed temperatures ranging between 923 and 1073 K have been considered. This new approach uses ANSYS FLUENT 14.0 as the modelling platform for the simulations along with a complete set of self-developed user-defined functions (UDFs). The simulation results are compared to the experimental data obtained previously by the research group in a lab-scale fluid bed incinerator. The comparison indicates that the proposed CFD model predicts well the evolution of the HM release for the bed temperatures analyzed. It shows that both bed temperature and bed dynamics have influence on the HM vaporization rate. It can be concluded that CFD is a rigorous tool that provides valuable information about HM vaporization and that the original two-scale simulation scheme adopted allows to better represent the actual particle behavior in a fluid bed incinerator.« less

Representing macropore flow at the catchment scale: a comparative modeling study

NASA Astrophysics Data System (ADS)

Liu, D.; Li, H. Y.; Tian, F.; Leung, L. R.

2017-12-01

Macropore flow is an important hydrological process that generally enhances the soil infiltration capacity and velocity of subsurface water. Up till now, macropore flow is mostly simulated with high-resolution models. One possible drawback of this modeling approach is the difficulty to effectively represent the overall typology and connectivity of the macropore networks. We hypothesize that modeling macropore flow directly at the catchment scale may be complementary to the existing modeling strategy and offer some new insights. Tsinghua Representative Elementary Watershed model (THREW model) is a semi-distributed hydrology model, where the fundamental building blocks are representative elementary watersheds (REW) linked by the river channel network. In THREW, all the hydrological processes are described with constitutive relationships established directly at the REW level, i.e., catchment scale. In this study, the constitutive relationship of macropore flow drainage is established as part of THREW. The enhanced THREW model is then applied at two catchments with deep soils but distinct climates, the humid Asu catchment in the Amazon River basin, and the arid Wei catchment in the Yellow River basin. The Asu catchment has an area of 12.43km2 with mean annual precipitation of 2442mm. The larger Wei catchment has an area of 24800km2 but with mean annual precipitation of only 512mm. The rainfall-runoff processes are simulated at a hourly time step from 2002 to 2005 in the Asu catchment and from 2001 to 2012 in the Wei catchment. The role of macropore flow on the catchment hydrology will be analyzed comparatively over the Asu and Wei catchments against the observed streamflow, evapotranspiration and other auxiliary data.

Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system

PubMed Central

Miyazawa, Yasumasa; Guo, Xinyu; Varlamov, Sergey M.; Miyama, Toru; Yoda, Ken; Sato, Katsufumi; Kano, Toshiyuki; Sato, Keiji

2015-01-01

At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50 km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100 km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. PMID:26633309

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

NASA Technical Reports Server (NTRS)

Avissar, Roni; Chen, Fei

1993-01-01

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in large-scale atmospheric models.

Effective pore-scale dispersion upscaling with a correlated continuous time random walk approach

NASA Astrophysics Data System (ADS)

Le Borgne, T.; Bolster, D.; Dentz, M.; de Anna, P.; Tartakovsky, A.

2011-12-01

We investigate the upscaling of dispersion from a pore-scale analysis of Lagrangian velocities. A key challenge in the upscaling procedure is to relate the temporal evolution of spreading to the pore-scale velocity field properties. We test the hypothesis that one can represent Lagrangian velocities at the pore scale as a Markov process in space. The resulting effective transport model is a continuous time random walk (CTRW) characterized by a correlated random time increment, here denoted as correlated CTRW. We consider a simplified sinusoidal wavy channel model as well as a more complex heterogeneous pore space. For both systems, the predictions of the correlated CTRW model, with parameters defined from the velocity field properties (both distribution and correlation), are found to be in good agreement with results from direct pore-scale simulations over preasymptotic and asymptotic times. In this framework, the nontrivial dependence of dispersion on the pore boundary fluctuations is shown to be related to the competition between distribution and correlation effects. In particular, explicit inclusion of spatial velocity correlation in the effective CTRW model is found to be important to represent incomplete mixing in the pore throats.

Part 2 of a Computational Study of a Drop-Laden Mixing Layer

NASA Technical Reports Server (NTRS)

Okongo, Nora; Bellan, Josette

2004-01-01

This second of three reports on a computational study of a mixing layer laden with evaporating liquid drops presents the evaluation of Large Eddy Simulation (LES) models. The LES models were evaluated on an existing database that had been generated using Direct Numerical Simulation (DNS). The DNS method and the database are described in the first report of this series, Part 1 of a Computational Study of a Drop-Laden Mixing Layer (NPO-30719), NASA Tech Briefs, Vol. 28, No.7 (July 2004), page 59. The LES equations, which are derived by applying a spatial filter to the DNS set, govern the evolution of the larger scales of the flow and can therefore be solved on a coarser grid. Consistent with the reduction in grid points, the DNS drops would be represented by fewer drops, called computational drops in the LES context. The LES equations contain terms that cannot be directly computed on the coarser grid and that must instead be modeled. Two types of models are necessary: (1) those for the filtered source terms representing the effects of drops on the filtered flow field and (2) those for the sub-grid scale (SGS) fluxes arising from filtering the convective terms in the DNS equations. All of the filtered-sourceterm models that were developed were found to overestimate the filtered source terms. For modeling the SGS fluxes, constant-coefficient Smagorinsky, gradient, and scale-similarity models were assessed and calibrated on the DNS database. The Smagorinsky model correlated poorly with the SGS fluxes, whereas the gradient and scale-similarity models were well correlated with the SGS quantities that they represented.

Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.

Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

NASA Astrophysics Data System (ADS)

Chen, Jinduan; Boccelli, Dominic L.

2018-02-01

Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

A New Canopy Integration Factor

NASA Astrophysics Data System (ADS)

Badgley, G.; Anderegg, L. D. L.; Baker, I. T.; Berry, J. A.

2017-12-01

Ecosystem modelers have long debated how to best represent within-canopy heterogeneity. Can one big leaf represent the full range of canopy physiological responses? Or you need two leaves - sun and shade - to get things right? Is it sufficient to treat the canopy as a diffuse medium? Or would it be better to explicitly represent separate canopy layers? These are open questions that have been subject of an enormous amount of research and scrutiny. Yet regardless of how the canopy is represented, each model must grapple with correctly parameterizing its canopy in a way that properly translates leaf-level processes to the canopy and ecosystem scale. We present a new approach for integrating whole-canopy biochemistry by combining remote sensing with ecological theory. Using the Simple Biosphere model (SiB), we redefined how SiB scales photosynthetic processes from leaf-to-canopy as a function of satellite-derived measurements of solar-induced chlorophyll fluorescence (SIF). Across multiple long-term study sites, our approach improves the accuracy of daily modeled photosynthesis by as much as 25 percent. We share additional insights on how SIF might be more directly integrated into photosynthesis models, as well as present ideas for harnessing SIF to more accurately parameterize canopy biochemical variables.

ED(MF)n: Humidity-Convection Feedbacks in a Mass Flux Scheme Based on Resolved Size Densities

NASA Astrophysics Data System (ADS)

Neggers, R.

2014-12-01

Cumulus cloud populations remain at least partially unresolved in present-day numerical simulations of global weather and climate, and accordingly their impact on the larger-scale flow has to be represented through parameterization. Various methods have been developed over the years, ranging in complexity from the early bulk models relying on a single plume to more recent approaches that attempt to reconstruct the underlying probability density functions, such as statistical schemes and multiple plume approaches. Most of these "classic" methods capture key aspects of cumulus cloud populations, and have been successfully implemented in operational weather and climate models. However, the ever finer discretizations of operational circulation models, driven by advances in the computational efficiency of supercomputers, is creating new problems for existing sub-grid schemes. Ideally, a sub-grid scheme should automatically adapt its impact on the resolved scales to the dimension of the grid-box within which it is supposed to act. It can be argued that this is only possible when i) the scheme is aware of the range of scales of the processes it represents, and ii) it can distinguish between contributions as a function of size. How to conceptually represent this knowledge of scale in existing parameterization schemes remains an open question that is actively researched. This study considers a relatively new class of models for sub-grid transport in which ideas from the field of population dynamics are merged with the concept of multi plume modelling. More precisely, a multiple mass flux framework for moist convective transport is formulated in which the ensemble of plumes is created in "size-space". It is argued that thus resolving the underlying size-densities creates opportunities for introducing scale-awareness and scale-adaptivity in the scheme. The behavior of an implementation of this framework in the Eddy Diffusivity Mass Flux (EDMF) model, named ED(MF)n, is examined for a standard case of subtropical marine shallow cumulus. We ask if a system of multiple independently resolved plumes is able to automatically create the vertical profile of bulk (mass) flux at which the sub-grid scale transport balances the imposed larger-scale forcings in the cloud layer.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

A crystal plasticity model for slip in hexagonal close packed metals based on discrete dislocation simulations

NASA Astrophysics Data System (ADS)

Messner, Mark C.; Rhee, Moono; Arsenlis, Athanasios; Barton, Nathan R.

2017-06-01

This work develops a method for calibrating a crystal plasticity model to the results of discrete dislocation (DD) simulations. The crystal model explicitly represents junction formation and annihilation mechanisms and applies these mechanisms to describe hardening in hexagonal close packed metals. The model treats these dislocation mechanisms separately from elastic interactions among populations of dislocations, which the model represents through a conventional strength-interaction matrix. This split between elastic interactions and junction formation mechanisms more accurately reproduces the DD data and results in a multi-scale model that better represents the lower scale physics. The fitting procedure employs concepts of machine learning—feature selection by regularized regression and cross-validation—to develop a robust, physically accurate crystal model. The work also presents a method for ensuring the final, calibrated crystal model respects the physical symmetries of the crystal system. Calibrating the crystal model requires fitting two linear operators: one describing elastic dislocation interactions and another describing junction formation and annihilation dislocation reactions. The structure of these operators in the final, calibrated model reflect the crystal symmetry and slip system geometry of the DD simulations.

Development of a parallel FE simulator for modeling the whole trans-scale failure process of rock from meso- to engineering-scale

NASA Astrophysics Data System (ADS)

Li, Gen; Tang, Chun-An; Liang, Zheng-Zhao

2017-01-01

Multi-scale high-resolution modeling of rock failure process is a powerful means in modern rock mechanics studies to reveal the complex failure mechanism and to evaluate engineering risks. However, multi-scale continuous modeling of rock, from deformation, damage to failure, has raised high requirements on the design, implementation scheme and computation capacity of the numerical software system. This study is aimed at developing the parallel finite element procedure, a parallel rock failure process analysis (RFPA) simulator that is capable of modeling the whole trans-scale failure process of rock. Based on the statistical meso-damage mechanical method, the RFPA simulator is able to construct heterogeneous rock models with multiple mechanical properties, deal with and represent the trans-scale propagation of cracks, in which the stress and strain fields are solved for the damage evolution analysis of representative volume element by the parallel finite element method (FEM) solver. This paper describes the theoretical basis of the approach and provides the details of the parallel implementation on a Windows - Linux interactive platform. A numerical model is built to test the parallel performance of FEM solver. Numerical simulations are then carried out on a laboratory-scale uniaxial compression test, and field-scale net fracture spacing and engineering-scale rock slope examples, respectively. The simulation results indicate that relatively high speedup and computation efficiency can be achieved by the parallel FEM solver with a reasonable boot process. In laboratory-scale simulation, the well-known physical phenomena, such as the macroscopic fracture pattern and stress-strain responses, can be reproduced. In field-scale simulation, the formation process of net fracture spacing from initiation, propagation to saturation can be revealed completely. In engineering-scale simulation, the whole progressive failure process of the rock slope can be well modeled. It is shown that the parallel FE simulator developed in this study is an efficient tool for modeling the whole trans-scale failure process of rock from meso- to engineering-scale.

A Scalar Product Model for the Multidimensional Scaling of Choice

ERIC Educational Resources Information Center

Bechtel, Gordon G.; And Others

1971-01-01

Contains a solution for the multidimensional scaling of pairwise choice when individuals are represented as dimensional weights. The analysis supplies an exact least squares solution and estimates of group unscalability parameters. (DG)

The Edinburgh Postnatal Depression Scale: Screening Tool for Postpartum Anxiety as Well? Findings from a Confirmatory Factor Analysis of the Hebrew Version.

PubMed

Bina, Rena; Harrington, Donna

2016-04-01

The Edinburgh Postnatal Depression Scale (EPDS) was originally created as a uni-dimensional scale to screen for postpartum depression (PPD); however, evidence from various studies suggests that it is a multi-dimensional scale measuring mainly anxiety in addition to depression. The factor structure of the EPDS seems to differ across various language translations, raising questions regarding its stability. This study examined the factor structure of the Hebrew version of the EPDS to assess whether it is uni- or multi-dimensional. Seven hundred and fifteen (n = 715) women were screened at 6 weeks postpartum using the Hebrew version of the EPDS. Confirmatory factor analysis (CFA) was used to test four models derived from the literature. Of the four CFA models tested, a 9-item two factor model fit the data best, with one factor representing an underlying depression construct and the other representing an underlying anxiety construct. for Practice The Hebrew version of the EPDS appears to consist of depression and anxiety sub-scales. Given the widespread PPD screening initiatives, anxiety symptoms should be addressed in addition to depressive symptoms, and a short scale, such as the EPDS, assessing both may be efficient.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Obtaining Content Weights for Test Specifications from Job Analysis Task Surveys: An Application of the Many-Facets Rasch Model

ERIC Educational Resources Information Center

Wang, Ning; Stahl, John

2012-01-01

This article discusses the use of the Many-Facets Rasch Model, via the FACETS computer program (Linacre, 2006a), to scale job/practice analysis survey data as well as to combine multiple rating scales into single composite weights representing the tasks' relative importance. Results from the Many-Facets Rasch Model are compared with those…

Better models are more effectively connected models

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Bielders, Charles; Darboux, Frederic; Fiener, Peter; Finger, David; Turnbull-Lloyd, Laura; Wainwright, John

2016-04-01

The concept of hydrologic and geomorphologic connectivity describes the processes and pathways which link sources (e.g. rainfall, snow and ice melt, springs, eroded areas and barren lands) to accumulation areas (e.g. foot slopes, streams, aquifers, reservoirs), and the spatial variations thereof. There are many examples of hydrological and sediment connectivity on a watershed scale; in consequence, a process-based understanding of connectivity is crucial to help managers understand their systems and adopt adequate measures for flood prevention, pollution mitigation and soil protection, among others. Modelling is often used as a tool to understand and predict fluxes within a catchment by complementing observations with model results. Catchment models should therefore be able to reproduce the linkages, and thus the connectivity of water and sediment fluxes within the systems under simulation. In modelling, a high level of spatial and temporal detail is desirable to ensure taking into account a maximum number of components, which then enables connectivity to emerge from the simulated structures and functions. However, computational constraints and, in many cases, lack of data prevent the representation of all relevant processes and spatial/temporal variability in most models. In most cases, therefore, the level of detail selected for modelling is too coarse to represent the system in a way in which connectivity can emerge; a problem which can be circumvented by representing fine-scale structures and processes within coarser scale models using a variety of approaches. This poster focuses on the results of ongoing discussions on modelling connectivity held during several workshops within COST Action Connecteur. It assesses the current state of the art of incorporating the concept of connectivity in hydrological and sediment models, as well as the attitudes of modellers towards this issue. The discussion will focus on the different approaches through which connectivity can be represented in models: either by allowing it to emerge from model behaviour or by parameterizing it inside model structures; and on the appropriate scale at which processes should be represented explicitly or implicitly. It will also explore how modellers themselves approach connectivity through the results of a community survey. Finally, it will present the outline of an international modelling exercise aimed at assessing how different modelling concepts can capture connectivity in real catchments.

Non-Gaussian Multi-resolution Modeling of Magnetosphere-Ionosphere Coupling Processes

NASA Astrophysics Data System (ADS)

Fan, M.; Paul, D.; Lee, T. C. M.; Matsuo, T.

2016-12-01

The most dynamic coupling between the magnetosphere and ionosphere occurs in the Earth's polar atmosphere. Our objective is to model scale-dependent stochastic characteristics of high-latitude ionospheric electric fields that originate from solar wind magnetosphere-ionosphere interactions. The Earth's high-latitude ionospheric electric field exhibits considerable variability, with increasing non-Gaussian characteristics at decreasing spatio-temporal scales. Accurately representing the underlying stochastic physical process through random field modeling is crucial not only for scientific understanding of the energy, momentum and mass exchanges between the Earth's magnetosphere and ionosphere, but also for modern technological systems including telecommunication, navigation, positioning and satellite tracking. While a lot of efforts have been made to characterize the large-scale variability of the electric field in the context of Gaussian processes, no attempt has been made so far to model the small-scale non-Gaussian stochastic process observed in the high-latitude ionosphere. We construct a novel random field model using spherical needlets as building blocks. The double localization of spherical needlets in both spatial and frequency domains enables the model to capture the non-Gaussian and multi-resolutional characteristics of the small-scale variability. The estimation procedure is computationally feasible due to the utilization of an adaptive Gibbs sampler. We apply the proposed methodology to the computational simulation output from the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamics (MHD) magnetosphere model. Our non-Gaussian multi-resolution model results in characterizing significantly more energy associated with the small-scale ionospheric electric field variability in comparison to Gaussian models. By accurately representing unaccounted-for additional energy and momentum sources to the Earth's upper atmosphere, our novel random field modeling approach will provide a viable remedy to the current numerical models' systematic biases resulting from the underestimation of high-latitude energy and momentum sources.

A multi-scale modelling procedure to quantify hydrological impacts of upland land management

NASA Astrophysics Data System (ADS)

Wheater, H. S.; Jackson, B.; Bulygina, N.; Ballard, C.; McIntyre, N.; Marshall, M.; Frogbrook, Z.; Solloway, I.; Reynolds, B.

2008-12-01

Recent UK floods have focused attention on the effects of agricultural intensification on flood risk. However, quantification of these effects raises important methodological issues. Catchment-scale data have proved inadequate to support analysis of impacts of land management change, due to climate variability, uncertainty in input and output data, spatial heterogeneity in land use and lack of data to quantify historical changes in management practices. Manipulation experiments to quantify the impacts of land management change have necessarily been limited and small scale, and in the UK mainly focused on the lowlands and arable agriculture. There is a need to develop methods to extrapolate from small scale observations to predict catchment-scale response, and to quantify impacts for upland areas. With assistance from a cooperative of Welsh farmers, a multi-scale experimental programme has been established at Pontbren, in mid-Wales, an area of intensive sheep production. The data have been used to support development of a multi-scale modelling methodology to assess impacts of agricultural intensification and the potential for mitigation of flood risk through land use management. Data are available from replicated experimental plots under different land management treatments, from instrumented field and hillslope sites, including tree shelter belts, and from first and second order catchments. Measurements include climate variables, soil water states and hydraulic properties at multiple depths and locations, tree interception, overland flow and drainflow, groundwater levels, and streamflow from multiple locations. Fine resolution physics-based models have been developed to represent soil and runoff processes, conditioned using experimental data. The detailed models are used to calibrate simpler 'meta- models' to represent individual hydrological elements, which are then combined in a semi-distributed catchment-scale model. The methodology is illustrated using field and catchment-scale simulations to demonstrate the the response of improved and unimproved grassland, and the potential effects of land management interventions, including farm ponds, tree shelter belts and buffer strips. It is concluded that the methodology developed has the potential to represent and quantify catchment-scale effects of upland management; continuing research is extending the work to a wider range of upland environments and land use types, with the aim of providing generic simulation tools that can be used to provide strategic policy guidance.

Coupling scales for modelling heavy metal vaporization from municipal solid waste incineration in a fluid bed by CFD.

PubMed

Soria, José; Gauthier, Daniel; Flamant, Gilles; Rodriguez, Rosa; Mazza, Germán

2015-09-01

Municipal Solid Waste Incineration (MSWI) in fluidized bed is a very interesting technology mainly due to high combustion efficiency, great flexibility for treating several types of waste fuels and reduction in pollutants emitted with the flue gas. However, there is a great concern with respect to the fate of heavy metals (HM) contained in MSW and their environmental impact. In this study, a coupled two-scale CFD model was developed for MSWI in a bubbling fluidized bed. It presents an original scheme that combines a single particle model and a global fluidized bed model in order to represent the HM vaporization during MSW combustion. Two of the most representative HM (Cd and Pb) with bed temperatures ranging between 923 and 1073K have been considered. This new approach uses ANSYS FLUENT 14.0 as the modelling platform for the simulations along with a complete set of self-developed user-defined functions (UDFs). The simulation results are compared to the experimental data obtained previously by the research group in a lab-scale fluid bed incinerator. The comparison indicates that the proposed CFD model predicts well the evolution of the HM release for the bed temperatures analyzed. It shows that both bed temperature and bed dynamics have influence on the HM vaporization rate. It can be concluded that CFD is a rigorous tool that provides valuable information about HM vaporization and that the original two-scale simulation scheme adopted allows to better represent the actual particle behavior in a fluid bed incinerator. Copyright © 2015 Elsevier Ltd. All rights reserved.

Status of DSMT research program

NASA Technical Reports Server (NTRS)

Mcgowan, Paul E.; Javeed, Mehzad; Edighoffer, Harold H.

1991-01-01

The status of the Dynamic Scale Model Technology (DSMT) research program is presented. DSMT is developing scale model technology for large space structures as part of the Control Structure Interaction (CSI) program at NASA Langley Research Center (LaRC). Under DSMT a hybrid-scale structural dynamics model of Space Station Freedom was developed. Space Station Freedom was selected as the focus structure for DSMT since the station represents the first opportunity to obtain flight data on a complex, three-dimensional space structure. Included is an overview of DSMT including the development of the space station scale model and the resulting hardware. Scaling technology was developed for this model to achieve a ground test article which existing test facilities can accommodate while employing realistically scaled hardware. The model was designed and fabricated by the Lockheed Missile and Space Co., and is assembled at LaRc for dynamic testing. Also, results from ground tests and analyses of the various model components are presented along with plans for future subassembly and matted model tests. Finally, utilization of the scale model for enhancing analysis verification of the full-scale space station is also considered.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Preliminary design, analysis, and costing of a dynamic scale model of the NASA space station

NASA Technical Reports Server (NTRS)

Gronet, M. J.; Pinson, E. D.; Voqui, H. L.; Crawley, E. F.; Everman, M. R.

1987-01-01

The difficulty of testing the next generation of large flexible space structures on the ground places an emphasis on other means for validating predicted on-orbit dynamic behavior. Scale model technology represents one way of verifying analytical predictions with ground test data. This study investigates the preliminary design, scaling and cost trades for a Space Station dynamic scale model. The scaling of nonlinear joint behavior is studied from theoretical and practical points of view. Suspension system interaction trades are conducted for the ISS Dual Keel Configuration and Build-Up Stages suspended in the proposed NASA/LaRC Large Spacecraft Laboratory. Key issues addressed are scaling laws, replication vs. simulation of components, manufacturing, suspension interactions, joint behavior, damping, articulation capability, and cost. These issues are the subject of parametric trades versus the scale model factor. The results of these detailed analyses are used to recommend scale factors for four different scale model options, each with varying degrees of replication. Potential problems in constructing and testing the scale model are identified, and recommendations for further study are outlined.

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Development of the Ghent Multidimensional Somatic Complaints Scale

ERIC Educational Resources Information Center

Beirens, Koen; Fontaine, Johnny R. J.

2010-01-01

The present study aimed at developing a new scale that operationalizes a hierarchical model of somatic complaints. First, 63 items representing a wide range of symptoms and sensations were compiled from somatic complaints scales and emotion literature. These complaints were rated by Belgian students (n = 307) and Belgian adults (n = 603).…

Scaling Laws Applied to a Modal Formulation of the Aeroservoelastic Equations

NASA Technical Reports Server (NTRS)

Pototzky, Anthony S.

2002-01-01

A method of scaling is described that easily converts the aeroelastic equations of motion of a full-sized aircraft into ones of a wind-tunnel model. To implement the method, a set of rules is provided for the conversion process involving matrix operations with scale factors. In addition, a technique for analytically incorporating a spring mounting system into the aeroelastic equations is also presented. As an example problem, a finite element model of a full-sized aircraft is introduced from the High Speed Research (HSR) program to exercise the scaling method. With a set of scale factor values, a brief outline is given of a procedure to generate the first-order aeroservoelastic analytical model representing the wind-tunnel model. To verify the scaling process as applied to the example problem, the root-locus patterns from the full-sized vehicle and the wind-tunnel model are compared to see if the root magnitudes scale with the frequency scale factor value. Selected time-history results are given from a numerical simulation of an active-controlled wind-tunnel model to demonstrate the utility of the scaling process.

Sculpting Mountains: Interactive Terrain Modeling Based on Subsurface Geology.

PubMed

Cordonnier, Guillaume; Cani, Marie-Paule; Benes, Bedrich; Braun, Jean; Galin, Eric

2018-05-01

Most mountain ranges are formed by the compression and folding of colliding tectonic plates. Subduction of one plate causes large-scale asymmetry while their layered composition (or stratigraphy) explains the multi-scale folded strata observed on real terrains. We introduce a novel interactive modeling technique to generate visually plausible, large scale terrains that capture these phenomena. Our method draws on both geological knowledge for consistency and on sculpting systems for user interaction. The user is provided hands-on control on the shape and motion of tectonic plates, represented using a new geologically-inspired model for the Earth crust. The model captures their volume preserving and complex folding behaviors under collision, causing mountains to grow. It generates a volumetric uplift map representing the growth rate of subsurface layers. Erosion and uplift movement are jointly simulated to generate the terrain. The stratigraphy allows us to render folded strata on eroded cliffs. We validated the usability of our sculpting interface through a user study, and compare the visual consistency of the earth crust model with geological simulation results and real terrains.

Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.

PubMed

Inoue, Yasuhiro; Adachi, Taiji

2011-07-01

Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.

Simulating faults and plate boundaries with a transversely isotropic plasticity model

NASA Astrophysics Data System (ADS)

Sharples, W.; Moresi, L. N.; Velic, M.; Jadamec, M. A.; May, D. A.

2016-03-01

In mantle convection simulations, dynamically evolving plate boundaries have, for the most part, been represented using an visco-plastic flow law. These systems develop fine-scale, localized, weak shear band structures which are reminiscent of faults but it is a significant challenge to resolve the large- and the emergent, small-scale-behavior. We address this issue of resolution by taking into account the observation that a rock element with embedded, planar, failure surfaces responds as a non-linear, transversely isotropic material with a weak orientation defined by the plane of the failure surface. This approach partly accounts for the large-scale behavior of fine-scale systems of shear bands which we are not in a position to resolve explicitly. We evaluate the capacity of this continuum approach to model plate boundaries, specifically in the context of subduction models where the plate boundary interface has often been represented as a planar discontinuity. We show that the inclusion of the transversely isotropic plasticity model for the plate boundary promotes asymmetric subduction from initiation. A realistic evolution of the plate boundary interface and associated stresses is crucial to understanding inter-plate coupling, convergent margin driven topography, and earthquakes.

PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.

PubMed

Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold

2016-01-21

The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-scale genetic dynamic modelling I : an algorithm to compute generators.

PubMed

Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

2011-09-01

We present a new approach or framework to model dynamic regulatory genetic activity. The framework is using a multi-scale analysis based upon generic assumptions on the relative time scales attached to the different transitions of molecular states defining the genetic system. At micro-level such systems are regulated by the interaction of two kinds of molecular players: macro-molecules like DNA or polymerases, and smaller molecules acting as transcription factors. The proposed genetic model then represents the larger less abundant molecules with a finite discrete state space, for example describing different conformations of these molecules. This is in contrast to the representations of the transcription factors which are-like in classical reaction kinetics-represented by their particle number only. We illustrate the method by considering the genetic activity associated to certain configurations of interacting genes that are fundamental to modelling (synthetic) genetic clocks. A largely unknown question is how different molecular details incorporated via this more realistic modelling approach lead to different macroscopic regulatory genetic models which dynamical behaviour might-in general-be different for different model choices. The theory will be applied to a real synthetic clock in a second accompanying article (Kirkilioniset al., Theory Biosci, 2011).

An Eddy-Diffusivity Mass-flux (EDMF) closure for the unified representation of cloud and convective processes

NASA Astrophysics Data System (ADS)

Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G.

2014-12-01

Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of results verifies the capacity of this closure to realistically represent different cloud and convective processes. Implementation of the closure in an idealized GCM allows us to study cloud feedbacks to climate change and to study the interactions between clouds, convections, and the large-scale circulation.

Coupled land surface/hydrologic/atmospheric models

NASA Technical Reports Server (NTRS)

Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

1993-01-01

The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

Creative use of pilot points to address site and regional scale heterogeneity in a variable-density model

USGS Publications Warehouse

Dausman, Alyssa M.; Doherty, John; Langevin, Christian D.

2010-01-01

Pilot points for parameter estimation were creatively used to address heterogeneity at both the well field and regional scales in a variable-density groundwater flow and solute transport model designed to test multiple hypotheses for upward migration of fresh effluent injected into a highly transmissive saline carbonate aquifer. Two sets of pilot points were used within in multiple model layers, with one set of inner pilot points (totaling 158) having high spatial density to represent hydraulic conductivity at the site, while a second set of outer points (totaling 36) of lower spatial density was used to represent hydraulic conductivity further from the site. Use of a lower spatial density outside the site allowed (1) the total number of pilot points to be reduced while maintaining flexibility to accommodate heterogeneity at different scales, and (2) development of a model with greater areal extent in order to simulate proper boundary conditions that have a limited effect on the area of interest. The parameters associated with the inner pilot points were log transformed hydraulic conductivity multipliers of the conductivity field obtained by interpolation from outer pilot points. The use of this dual inner-outer scale parameterization (with inner parameters constituting multipliers for outer parameters) allowed smooth transition of hydraulic conductivity from the site scale, where greater spatial variability of hydraulic properties exists, to the regional scale where less spatial variability was necessary for model calibration. While the model is highly parameterized to accommodate potential aquifer heterogeneity, the total number of pilot points is kept at a minimum to enable reasonable calibration run times.

Application of the generalized vertical coordinate ocean model for better representing satellite data

NASA Technical Reports Server (NTRS)

Song, Y. T.

2002-01-01

It is found that two adaptive parametric functions can be introduced into the basic ocean equations for utilizing the optimal or hybrid features of commonly used z-level, terrain- following, isopycnal, and pressure coordinates in numerical ocean models. The two parametric functions are formulated by combining three techniques: the arbitrary vertical coordinate system of Kasahara (1 974), the Jacobian pressure gradient formulation of Song (1 998), and a newly developed metric factor that permits both compressible (non-Boussinesq) and incompressible (Boussinesq) approximations. Based on the new formulation, an adaptive modeling strategy is proposed and a staggered finite volume method is designed to ensure conservation of important physical properties and numerical accuracy. Implementation of the combined techniques to SCRUM (Song and Haidvogel1994) shows that the adaptive modeling strategy can be applied to any existing ocean model without incurring computational expense or altering the original numerical schemes. Such a generalized coordinate model is expected to benefit diverse ocean modelers for easily choosing optimal vertical structures and sharing modeling resources based on a common model platform. Several representing oceanographic problems with different scales and characteristics, such as coastal canyons, basin-scale circulation, and global ocean circulation, are used to demonstrate the model's capability for multiple applications. New results show that the model is capable of simultaneously resolving both Boussinesq and non-Boussinesq, and both small- and large-scale processes well. This talk will focus on its applications of multiple satellite sensing data in eddy-resolving simulations of Asian Marginal Sea and Kurosio. Attention will be given to how Topex/Poseidon SSH, TRMM SST; and GRACE ocean bottom pressure can be correctly represented in a non- Boussinesq model.

Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations

PubMed Central

Schwen, Lars Ole; Schenk, Arne; Kreutz, Clemens; Timmer, Jens; Bartolomé Rodríguez, María Matilde; Kuepfer, Lars; Preusser, Tobias

2015-01-01

The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale. PMID:26222615

Nonlinear Analysis and Scaling Laws for Noncircular Composite Structures Subjected to Combined Loads

NASA Technical Reports Server (NTRS)

Hilburger, Mark W.; Rose, Cheryl A.; Starnes, James H., Jr.

2001-01-01

Results from an analytical study of the response of a built-up, multi-cell noncircular composite structure subjected to combined internal pressure and mechanical loads are presented. Nondimensional parameters and scaling laws based on a first-order shear-deformation plate theory are derived for this noncircular composite structure. The scaling laws are used to design sub-scale structural models for predicting the structural response of a full-scale structure representative of a portion of a blended-wing-body transport aircraft. Because of the complexity of the full-scale structure, some of the similitude conditions are relaxed for the sub-scale structural models. Results from a systematic parametric study are used to determine the effects of relaxing selected similitude conditions on the sensitivity of the effectiveness of using the sub-scale structural model response characteristics for predicting the full-scale structure response characteristics.

Bridging the scales in a eulerian air quality model to assess megacity export of pollution

NASA Astrophysics Data System (ADS)

Siour, G.; Colette, A.; Menut, L.; Bessagnet, B.; Coll, I.; Meleux, F.

2013-08-01

In Chemistry Transport Models (CTMs), spatial scale interactions are often represented through off-line coupling between large and small scale models. However, those nested configurations cannot give account of the impact of the local scale on its surroundings. This issue can be critical in areas exposed to air mass recirculation (sea breeze cells) or around regions with sharp pollutant emission gradients (large cities). Such phenomena can still be captured by the mean of adaptive gridding, two-way nesting or using model nudging, but these approaches remain relatively costly. We present here the development and the results of a simple alternative multi-scale approach making use of a horizontal stretched grid, in the Eulerian CTM CHIMERE. This method, called "stretching" or "zooming", consists in the introduction of local zooms in a single chemistry-transport simulation. It allows bridging online the spatial scales from the city (∼1 km resolution) to the continental area (∼50 km resolution). The CHIMERE model was run over a continental European domain, zoomed over the BeNeLux (Belgium, Netherlands and Luxembourg) area. We demonstrate that, compared with one-way nesting, the zooming method allows the expression of a significant feedback of the refined domain towards the large scale: around the city cluster of BeNeLuX, NO2 and O3 scores are improved. NO2 variability around BeNeLux is also better accounted for, and the net primary pollutant flux transported back towards BeNeLux is reduced. Although the results could not be validated for ozone over BeNeLux, we show that the zooming approach provides a simple and immediate way to better represent scale interactions within a CTM, and constitutes a useful tool for apprehending the hot topic of megacities within their continental environment.

Prospects for improving the representation of coastal and shelf seas in global ocean models

NASA Astrophysics Data System (ADS)

Holt, Jason; Hyder, Patrick; Ashworth, Mike; Harle, James; Hewitt, Helene T.; Liu, Hedong; New, Adrian L.; Pickles, Stephen; Porter, Andrew; Popova, Ekaterina; Icarus Allen, J.; Siddorn, John; Wood, Richard

2017-02-01

Accurately representing coastal and shelf seas in global ocean models represents one of the grand challenges of Earth system science. They are regions of immense societal importance through the goods and services they provide, hazards they pose and their role in global-scale processes and cycles, e.g. carbon fluxes and dense water formation. However, they are poorly represented in the current generation of global ocean models. In this contribution, we aim to briefly characterise the problem, and then to identify the important physical processes, and their scales, needed to address this issue in the context of the options available to resolve these scales globally and the evolving computational landscape.We find barotropic and topographic scales are well resolved by the current state-of-the-art model resolutions, e.g. nominal 1/12°, and still reasonably well resolved at 1/4°; here, the focus is on process representation. We identify tides, vertical coordinates, river inflows and mixing schemes as four areas where modelling approaches can readily be transferred from regional to global modelling with substantial benefit. In terms of finer-scale processes, we find that a 1/12° global model resolves the first baroclinic Rossby radius for only ˜ 8 % of regions < 500 m deep, but this increases to ˜ 70 % for a 1/72° model, so resolving scales globally requires substantially finer resolution than the current state of the art.We quantify the benefit of improved resolution and process representation using 1/12° global- and basin-scale northern North Atlantic nucleus for a European model of the ocean (NEMO) simulations; the latter includes tides and a k-ɛ vertical mixing scheme. These are compared with global stratification observations and 19 models from CMIP5. In terms of correlation and basin-wide rms error, the high-resolution models outperform all these CMIP5 models. The model with tides shows improved seasonal cycles compared to the high-resolution model without tides. The benefits of resolution are particularly apparent in eastern boundary upwelling zones.To explore the balance between the size of a globally refined model and that of multiscale modelling options (e.g. finite element, finite volume or a two-way nesting approach), we consider a simple scale analysis and a conceptual grid refining approach. We put this analysis in the context of evolving computer systems, discussing model turnaround time, scalability and resource costs. Using a simple cost model compared to a reference configuration (taken to be a 1/4° global model in 2011) and the increasing performance of the UK Research Councils' computer facility, we estimate an unstructured mesh multiscale approach, resolving process scales down to 1.5 km, would use a comparable share of the computer resource by 2021, the two-way nested multiscale approach by 2022, and a 1/72° global model by 2026. However, we also note that a 1/12° global model would not have a comparable computational cost to a 1° global model in 2017 until 2027. Hence, we conclude that for computationally expensive models (e.g. for oceanographic research or operational oceanography), resolving scales to ˜ 1.5 km would be routinely practical in about a decade given substantial effort on numerical and computational development. For complex Earth system models, this extends to about 2 decades, suggesting the focus here needs to be on improved process parameterisation to meet these challenges.

Improving National Water Modeling: An Intercomparison of two High-Resolution, Continental Scale Models, CONUS-ParFlow and the National Water Model

NASA Astrophysics Data System (ADS)

Tijerina, D.; Gochis, D.; Condon, L. E.; Maxwell, R. M.

2017-12-01

Development of integrated hydrology modeling systems that couple atmospheric, land surface, and subsurface flow is growing trend in hydrologic modeling. Using an integrated modeling framework, subsurface hydrologic processes, such as lateral flow and soil moisture redistribution, are represented in a single cohesive framework with surface processes like overland flow and evapotranspiration. There is a need for these more intricate models in comprehensive hydrologic forecasting and water management over large spatial areas, specifically the Continental US (CONUS). Currently, two high-resolution, coupled hydrologic modeling applications have been developed for this domain: CONUS-ParFlow built using the integrated hydrologic model ParFlow and the National Water Model that uses the NCAR Weather Research and Forecasting hydrological extension package (WRF-Hydro). Both ParFlow and WRF-Hydro include land surface models, overland flow, and take advantage of parallelization and high-performance computing (HPC) capabilities; however, they have different approaches to overland subsurface flow and groundwater-surface water interactions. Accurately representing large domains remains a challenge considering the difficult task of representing complex hydrologic processes, computational expense, and extensive data needs; both models have accomplished this, but have differences in approach and continue to be difficult to validate. A further exploration of effective methodology to accurately represent large-scale hydrology with integrated models is needed to advance this growing field. Here we compare the outputs of CONUS-ParFlow and the National Water Model to each other and with observations to study the performance of hyper-resolution models over large domains. Models were compared over a range of scales for major watersheds within the CONUS with a specific focus on the Mississippi, Ohio, and Colorado River basins. We use a novel set of approaches and analysis for this comparison to better understand differences in process and bias. This intercomparison is a step toward better understanding how much water we have and interactions between surface and subsurface. Our goal is to advance our understanding and simulation of the hydrologic system and ultimately improve hydrologic forecasts.

Climate model biases in jet streams, blocking and storm tracks resulting from missing orographic drag

NASA Astrophysics Data System (ADS)

Pithan, Felix; Shepherd, Theodore G.; Zappa, Giuseppe; Sandu, Irina

2016-07-01

State-of-the art climate models generally struggle to represent important features of the large-scale circulation. Common model deficiencies include an equatorward bias in the location of the midlatitude westerlies and an overly zonal orientation of the North Atlantic storm track. Orography is known to strongly affect the atmospheric circulation and is notoriously difficult to represent in coarse-resolution climate models. Yet how the representation of orography affects circulation biases in current climate models is not understood. Here we show that the effects of switching off the parameterization of drag from low-level orographic blocking in one climate model resemble the biases of the Coupled Model Intercomparison Project Phase 5 ensemble: An overly zonal wintertime North Atlantic storm track and less European blocking events, and an equatorward shift in the Southern Hemispheric jet and increase in the Southern Annular Mode time scale. This suggests that typical circulation biases in coarse-resolution climate models may be alleviated by improved parameterizations of low-level drag.

Structural assessment of "d" regions affected by premature concrete deterioration : technical report.

DOT National Transportation Integrated Search

2012-11-01

The effects of ASR/DEF on the D-regions of structures are investigated by means of a dual experimental and : analytical modeling program. Four near full scale specimens that represent cantilever and straddle pier bents, : that are representative of t...

A dual theory of price and value in a meso-scale economic model with stochastic profit rate

NASA Astrophysics Data System (ADS)

Greenblatt, R. E.

2014-12-01

The problem of commodity price determination in a market-based, capitalist economy has a long and contentious history. Neoclassical microeconomic theories are based typically on marginal utility assumptions, while classical macroeconomic theories tend to be value-based. In the current work, I study a simplified meso-scale model of a commodity capitalist economy. The production/exchange model is represented by a network whose nodes are firms, workers, capitalists, and markets, and whose directed edges represent physical or monetary flows. A pair of multivariate linear equations with stochastic input parameters represent physical (supply/demand) and monetary (income/expense) balance. The input parameters yield a non-degenerate profit rate distribution across firms. Labor time and price are found to be eigenvector solutions to the respective balance equations. A simple relation is derived relating the expected value of commodity price to commodity labor content. Results of Monte Carlo simulations are consistent with the stochastic price/labor content relation.

Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to themore » continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.« less

Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS andmore » AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.« less

A novel VLES model accounting for near-wall turbulence: physical rationale and applications

NASA Astrophysics Data System (ADS)

Jakirlic, Suad; Chang, Chi-Yao; Kutej, Lukas; Tropea, Cameron

2014-11-01

A novel VLES (Very Large Eddy Simulation) model whose non-resolved residual turbulence is modelled by using an advanced near-wall eddy-viscosity model accounting for the near-wall Reynolds stress anisotropy influence on the turbulence viscosity by modelling appropriately the velocity scale in the relevant formulation (Hanjalic et al., 2004) is proposed. It represents a variable resolution Hybrid LES/RANS (Reynolds-Averaged Navier-Stokes) computational scheme enabling a seamless transition from RANS to LES depending on the ratio of the turbulent viscosities associated with the unresolved scales corresponding to the LES cut-off and the `unsteady' scales pertinent to the turbulent properties of the VLES residual motion, which varies within the flow domain. The VLES method is validated interactively in the process of the model derivation by computing fully-developed flow in a plane channel (important representative of wall-bounded flows, underlying the log-law for the velocity field, for studying near-wall Reynolds stress anisotropy) and a separating flow over a periodic arrangement of smoothly-contoured 2-D hills. The model performances are also assessed in capturing the natural decay of the homogeneous isotropic turbulence. The model is finally applied to swirling flow in a vortex tube, flow in an IC-engine configuration and flow past a realistic car model.

Modelling tendon excursions and moment arms of the finger flexors: anatomic fidelity versus function.

PubMed

Kociolek, Aaron M; Keir, Peter J

2011-07-07

A detailed musculoskeletal model of the human hand is needed to investigate the pathomechanics of tendon disorders and carpal tunnel syndrome. The purpose of this study was to develop a biomechanical model with realistic flexor tendon excursions and moment arms. An existing upper extremity model served as a starting point, which included programmed movement of the index finger. Movement capabilities were added for the other fingers. Metacarpophalangeal articulations were modelled as universal joints to simulate flexion/extension and abduction/adduction while interphalangeal articulations used hinges to represent flexion. Flexor tendon paths were modelled using two approaches. The first method constrained tendons with control points, representing annular pulleys. The second technique used wrap objects at the joints as tendon constraints. Both control point and joint wrap models were iteratively adjusted to coincide with tendon excursions and moment arms from a anthropometric regression model using inputs for a 50th percentile male. Tendon excursions from the joint wrap method best matched the regression model even though anatomic features of the tendon paths were not preserved (absolute differences: mean<0.33 mm, peak<0.74 mm). The joint wrap model also produced similar moment arms to the regression (absolute differences: mean<0.63 mm, peak<1.58 mm). When a scaling algorithm was used to test anthropometrics, the scaled joint wrap models better matched the regression than the scaled control point models. Detailed patient-specific anatomical data will improve model outcomes for clinical use; however, population studies may benefit from simplified geometry, especially with anthropometric scaling. Copyright © 2011 Elsevier Ltd. All rights reserved.

Analogue modeling for science outreach: glacier flows at Antarctic National Museum, Italy

NASA Astrophysics Data System (ADS)

Zeoli, A.; Corti, G.; Folco, L.; Ossola, C.

2012-12-01

Comprehension of internal deformation and of ice flow in the Antarctic ice sheet in relation with the bedrock topography and with the thickness variation induced by climatic variations represent an important target for the scientific community. Analogue modelling technique aims to analyze geological or geomorphological processes through physical models built at a reduced geometrical scale in laboratory and deformed at reasonable scale of times. Corti et al. (2003 and 2008) have shown that this technique could also be used successfully for ice flow dynamic. Moreover, this technique gives a three-dimensional view of the processes. The models, that obviously simplify the geometry and rheology of natural processes, represent a geometrically, cinematically, dynamically and rheologically scaled analogue of the natural glacial environment. Following a procedure described in previous papers, proper materials have been selected to simulate the rheological behaviour of ice. In particular, during the experiments a Polydimethilsyloxane (PDMS) has been used to simulate glacial flow. PDMS is a transparent Newtonian silicone with a viscosity of 1.4 104 Pa s and a density of 965 kg m-3 (see material properties in Weijermars, 1986). The scaling of the model to natural conditions let to obtain reliable results for a correct comparison with the glacial processes under investigation. Models have been built with a with a geometrical scaling ratio of ~1.5 10-5, such that 1 cm in the model represents ~700 m in nature. The physical models have been deformed in terrestrial gravity field by allowing the PDMS to flow inside a Plexiglas box. In particular, the silicone has been poured inside the Plexiglas box and allowed to settle in order to obtain a flat free surface; the box has been then inclined of some degrees in order to allow the silicone to flow. Several boxes illustrating different glacial processes have been realized; each of them could be easily performed in short time and in standard laboratories. One of the main aims of the Antarctic National Museum in Siena (Italy) is to establish a strategy to deliver results to a broader scientific community. Time and spatial small scale of the experiments lead the analogue modeling technique easy to be shown to non-technical audiences through direct participation during Museum visits. All these experiments engage both teachers and students from primary and secondary schools and the general public.

Scale and the representation of human agency in the modeling of agroecosystems

DOE PAGES

Preston, Benjamin L.; King, Anthony W.; Ernst, Kathleen M.; ...

2015-07-17

Human agency is an essential determinant of the dynamics of agroecosystems. However, the manner in which agency is represented within different approaches to agroecosystem modeling is largely contingent on the scales of analysis and the conceptualization of the system of interest. While appropriate at times, narrow conceptualizations of agroecosystems can preclude consideration for how agency manifests at different scales, thereby marginalizing processes, feedbacks, and constraints that would otherwise affect model results. Modifications to the existing modeling toolkit may therefore enable more holistic representations of human agency. Model integration can assist with the development of multi-scale agroecosystem modeling frameworks that capturemore » different aspects of agency. In addition, expanding the use of socioeconomic scenarios and stakeholder participation can assist in explicitly defining context-dependent elements of scale and agency. Finally, such approaches, however, should be accompanied by greater recognition of the meta agency of model users and the need for more critical evaluation of model selection and application.« less

Infection Threshold for an Epidemic Model in Site and Bond Percolation Worlds

NASA Astrophysics Data System (ADS)

Sakisaka, Yukio; Yoshimura, Jin; Takeuchi, Yasuhiro; Sugiura, Koji; Tainaka, Kei-ichi

2010-02-01

We investigate an epidemic model on a square lattice with two protection treatments: prevention and quarantine. To explore the effects of both treatments, we apply the site and bond percolations. Computer simulations reveal that the threshold between endemic and disease-free phases can be represented by a single scaling law. The mean-field theory qualitatively predicts such infection dynamics and the scaling law.

From the Scale Model of the Sky to the Armillary Sphere

ERIC Educational Resources Information Center

Gangui, Alejandro; Casazza, Roberto; Paex, Carlos

2014-01-01

It is customary to employ a semi-spherical scale model to describe the apparent path of the Sun across the sky, whether it be its diurnal motion or its variation throughout the year. A flat surface and three bent semi-rigid wires (representing the three solar arcs during solstices and equinoxes) will do the job. On the other hand, since very early…

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

PubMed Central

Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

2018-01-01

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

NASA Astrophysics Data System (ADS)

Dickson, N. C.; Gierens, K. M.; Rogers, H. L.; Jones, R. L.

2010-07-01

The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensation trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve which empirically describes the ISS fraction in any average relative humidity pressure layer. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Bridging the Knowledge Gaps between Richards' Equation and Budyko Equation

NASA Astrophysics Data System (ADS)

Wang, D.

2017-12-01

The empirical Budyko equation represents the partitioning of mean annual precipitation into evaporation and runoff. Richards' equation, based on Darcy's law, represents the movement of water in unsaturated soils. The linkage between Richards' equation and Budyko equation is presented by invoking the empirical Soil Conservation Service curve number (SCS-CN) model for computing surface runoff at the event-scale. The basis of the SCS-CN method is the proportionality relationship, i.e., the ratio of continuing abstraction to its potential is equal to the ratio of surface runoff to its potential value. The proportionality relationship can be derived from the Richards' equation for computing infiltration excess and saturation excess models at the catchment scale. Meanwhile, the generalized proportionality relationship is demonstrated as the common basis of SCS-CN method, monthly "abcd" model, and Budyko equation. Therefore, the linkage between Darcy's law and the emergent pattern of mean annual water balance at the catchment scale is presented through the proportionality relationship.

Simulating the Impact Response of Three Full-Scale Crash Tests of Cessna 172 Aircraft

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.; Littell, Justin D.; Annett, Martin S.; Stimson, Chad M.

2017-01-01

During the summer of 2015, a series of three full-scale crash tests were performed at the Landing and Impact Research Facility located at NASA Langley Research Center of Cessna 172 aircraft. The first test (Test 1) represented a flare-to-stall emergency or hard landing onto a rigid surface. The second test (Test 2) represented a controlled-flight- into-terrain (CFIT) with a nose down pitch attitude of the aircraft, which impacted onto soft soil. The third test (Test 3) also represented a CFIT with a nose up pitch attitude of the aircraft, which resulted in a tail strike condition. Test 3 was also conducted onto soft soil. These crash tests were performed for the purpose of evaluating the performance of Emergency Locator Transmitters and to generate impact test data for model calibration. Finite element models were generated and impact analyses were conducted to simulate the three impact conditions using the commercial nonlinear, transient dynamic finite element code, LS-DYNA®. The objective of this paper is to summarize test-analysis results for the three full-scale crash tests.

Development of the Transport Class Model (TCM) Aircraft Simulation From a Sub-Scale Generic Transport Model (GTM) Simulation

NASA Technical Reports Server (NTRS)

Hueschen, Richard M.

2011-01-01

A six degree-of-freedom, flat-earth dynamics, non-linear, and non-proprietary aircraft simulation was developed that is representative of a generic mid-sized twin-jet transport aircraft. The simulation was developed from a non-proprietary, publicly available, subscale twin-jet transport aircraft simulation using scaling relationships and a modified aerodynamic database. The simulation has an extended aerodynamics database with aero data outside the normal transport-operating envelope (large angle-of-attack and sideslip values). The simulation has representative transport aircraft surface actuator models with variable rate-limits and generally fixed position limits. The simulation contains a generic 40,000 lb sea level thrust engine model. The engine model is a first order dynamic model with a variable time constant that changes according to simulation conditions. The simulation provides a means for interfacing a flight control system to use the simulation sensor variables and to command the surface actuators and throttle position of the engine model.

A Mixed-dimensional Model for Determining the Impact of Permafrost Polygonal Ground Degradation on Arctic Hydrology.

NASA Astrophysics Data System (ADS)

Coon, E.; Jan, A.; Painter, S. L.; Moulton, J. D.; Wilson, C. J.

2017-12-01

Many permafrost-affected regions in the Arctic manifest a polygonal patterned ground, which contains large carbon stores and is vulnerability to climate change as warming temperatures drive melting ice wedges, polygon degradation, and thawing of the underlying carbon-rich soils. Understanding the fate of this carbon is difficult. The system is controlled by complex, nonlinear physics coupling biogeochemistry, thermal-hydrology, and geomorphology, and there is a strong spatial scale separation between microtopograpy (at the scale of an individual polygon) and the scale of landscape change (at the scale of many thousands of polygons). Physics-based models have come a long way, and are now capable of representing the diverse set of processes, but only on individual polygons or a few polygons. Empirical models have been used to upscale across land types, including ecotypes evolving from low-centered (pristine) polygons to high-centered (degraded) polygon, and do so over large spatial extent, but are limited in their ability to discern causal process mechanisms. Here we present a novel strategy that looks to use physics-based models across scales, bringing together multiple capabilities to capture polygon degradation under a warming climate and its impacts on thermal-hydrology. We use fine-scale simulations on individual polygons to motivate a mixed-dimensional strategy that couples one-dimensional columns representing each individual polygon through two-dimensional surface flow. A subgrid model is used to incorporate the effects of surface microtopography on surface flow; this model is described and calibrated to fine-scale simulations. And critically, a subsidence model that tracks volume loss in bulk ice wedges is used to alter the subsurface structure and subgrid parameters, enabling the inclusion of the feedbacks associated with polygon degradation. This combined strategy results in a model that is able to capture the key features of polygon permafrost degradation, but in a simulation across a large spatial extent of polygonal tundra.

Multiscale modeling methods in biomechanics.

PubMed

Bhattacharya, Pinaki; Viceconti, Marco

2017-05-01

More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. WIREs Syst Biol Med 2017, 9:e1375. doi: 10.1002/wsbm.1375 For further resources related to this article, please visit the WIREs website. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

A Two-Factor Model Better Explains Heterogeneity in Negative Symptoms: Evidence from the Positive and Negative Syndrome Scale.

PubMed

Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong

2016-01-01

Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preston, Benjamin L.; King, Anthony W.; Ernst, Kathleen M.

Human agency is an essential determinant of the dynamics of agroecosystems. However, the manner in which agency is represented within different approaches to agroecosystem modeling is largely contingent on the scales of analysis and the conceptualization of the system of interest. While appropriate at times, narrow conceptualizations of agroecosystems can preclude consideration for how agency manifests at different scales, thereby marginalizing processes, feedbacks, and constraints that would otherwise affect model results. Modifications to the existing modeling toolkit may therefore enable more holistic representations of human agency. Model integration can assist with the development of multi-scale agroecosystem modeling frameworks that capturemore » different aspects of agency. In addition, expanding the use of socioeconomic scenarios and stakeholder participation can assist in explicitly defining context-dependent elements of scale and agency. Finally, such approaches, however, should be accompanied by greater recognition of the meta agency of model users and the need for more critical evaluation of model selection and application.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hong -Yi; Leung, L. Ruby; Tesfa, Teklu

A new large-scale stream temperature model has been developed within the Community Earth System Model (CESM) framework. The model is coupled with the Model for Scale Adaptive River Transport (MOSART) that represents river routing and a water management model (WM) that represents the effects of reservoir operations and water withdrawals on flow regulation. The coupled models allow the impacts of reservoir operations and withdrawals on stream temperature to be explicitly represented in a physically based and consistent way. The models have been applied to the Contiguous United States driven by observed meteorological forcing. It is shown that the model ismore » capable of reproducing stream temperature spatiotemporal variation satisfactorily by comparison against the observed streamflow from over 320 USGS stations. Including water management in the models improves the agreement between the simulated and observed streamflow at a large number of stream gauge stations. Both climate and water management are found to have important influence on the spatiotemporal patterns of stream temperature. More interestingly, it is quantitatively estimated that reservoir operation could cool down stream temperature in the summer low-flow season (August – October) by as much as 1~2oC over many places, as water management generally mitigates low flow, which has important implications to aquatic ecosystems. In conclusion, sensitivity of the simulated stream temperature to input data and reservoir operation rules used in the WM model motivates future directions to address some limitations in the current modeling framework.« less

Cross-Domain Multi-View Object Retrieval via Multi-Scale Topic Models.

PubMed

Hong, Richang; Hu, Zhenzhen; Wang, Ruxin; Wang, Meng; Tao, Dacheng

2016-09-27

The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respected to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two datasets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two datasets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

2011-11-01

There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

Order Matters: Sequencing Scale-Realistic Versus Simplified Models to Improve Science Learning

NASA Astrophysics Data System (ADS)

Chen, Chen; Schneps, Matthew H.; Sonnert, Gerhard

2016-10-01

Teachers choosing between different models to facilitate students' understanding of an abstract system must decide whether to adopt a model that is simplified and striking or one that is realistic and complex. Only recently have instructional technologies enabled teachers and learners to change presentations swiftly and to provide for learning based on multiple models, thus giving rise to questions about the order of presentation. Using disjoint individual growth modeling to examine the learning of astronomical concepts using a simulation of the solar system on tablets for 152 high school students (age 15), the authors detect both a model effect and an order effect in the use of the Orrery, a simplified model that exaggerates the scale relationships, and the True-to-scale, a proportional model that more accurately represents the realistic scale relationships. Specifically, earlier exposure to the simplified model resulted in diminution of the conceptual gain from the subsequent realistic model, but the realistic model did not impede learning from the following simplified model.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

“Modeling Trends in Air Pollutant Concentrations over the Northern Hemisphere Using the Coupled WRF-CMAQ Model”

EPA Science Inventory

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculatio...

Fire modeling in the Brazilian arc of deforestation through nested coupling of atmosphere, dynamic vegetation, LUCC and fire spread models

NASA Astrophysics Data System (ADS)

Tourigny, E.; Nobre, C.; Cardoso, M. F.

2012-12-01

Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

Scale Reliability Evaluation with Heterogeneous Populations

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling approach for scale reliability evaluation in heterogeneous populations is discussed. The method can be used for point and interval estimation of reliability of multicomponent measuring instruments in populations representing mixtures of an unknown number of latent classes or subpopulations. The procedure is helpful also…

SENSITIVITY OF OZONE AND AEROSOL PREDICTIONS TO THE TRANSPORT ALGORITHMS IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

EPA's Models-3 CMAQ system is intended to provide a community modeling paradigm that allows continuous improvement of the one-atmosphere modeling capability in a unified fashion. CMAQ's modular design promotes incorporation of several sets of science process modules representing ...

A short generic measure of work stress in the era of globalization: effort-reward imbalance.

PubMed

Siegrist, Johannes; Wege, Natalia; Pühlhofer, Frank; Wahrendorf, Morten

2009-08-01

We evaluate psychometric properties of a short version of the original effort-reward imbalance (ERI) questionnaire. This measure is of interest in the context of assessing stressful work conditions in the era of economic globalization. In a representative sample of 10,698 employed men and women participating in the longitudinal Socio-Economic Panel (SOEP) in Germany, a short version of the ERI questionnaire was included in the 2006 panel wave. Structural equation modeling and logistic regression analysis were applied. In addition to satisfactory internal consistency of scales, a model representing the theoretical structure of the scales provided the best data fit in a competitive test (RMSEA = 0.059, CAIC = 4124.19). Scoring high on the ERI scales was associated with elevated risks of poor self-rated health. This short version of the ERI questionnaire reveals satisfactory psychometric properties, and can be recommended for further use in research and practice.

Universal behavior of the interoccurrence times between losses in financial markets: independence of the time resolution.

PubMed

Ludescher, Josef; Bunde, Armin

2014-12-01

We consider representative financial records (stocks and indices) on time scales between one minute and one day, as well as historical monthly data sets, and show that the distribution P(Q)(r) of the interoccurrence times r between losses below a negative threshold -Q, for fixed mean interoccurrence times R(Q) in multiples of the corresponding time resolutions, can be described on all time scales by the same q exponentials, P(Q)(r)∝1/{[1+(q-1)βr](1/(q-1))}. We propose that the asset- and time-scale-independent analytic form of P(Q)(r) can be regarded as an additional stylized fact of the financial markets and represents a nontrivial test for market models. We analyze the distribution P(Q)(r) as well as the autocorrelation C(Q)(s) of the interoccurrence times for three market models: (i) multiplicative random cascades, (ii) multifractal random walks, and (iii) the generalized autoregressive conditional heteroskedasticity [GARCH(1,1)] model. We find that only one of the considered models, the multifractal random walk model, approximately reproduces the q-exponential form of P(Q)(r) and the power-law decay of C(Q)(s).

Universal behavior of the interoccurrence times between losses in financial markets: Independence of the time resolution

NASA Astrophysics Data System (ADS)

Ludescher, Josef; Bunde, Armin

2014-12-01

We consider representative financial records (stocks and indices) on time scales between one minute and one day, as well as historical monthly data sets, and show that the distribution PQ(r ) of the interoccurrence times r between losses below a negative threshold -Q , for fixed mean interoccurrence times RQ in multiples of the corresponding time resolutions, can be described on all time scales by the same q exponentials, PQ(r ) ∝1 /{[1+(q -1 ) β r ] 1 /(q -1 )} . We propose that the asset- and time-scale-independent analytic form of PQ(r ) can be regarded as an additional stylized fact of the financial markets and represents a nontrivial test for market models. We analyze the distribution PQ(r ) as well as the autocorrelation CQ(s ) of the interoccurrence times for three market models: (i) multiplicative random cascades, (ii) multifractal random walks, and (iii) the generalized autoregressive conditional heteroskedasticity [GARCH(1,1)] model. We find that only one of the considered models, the multifractal random walk model, approximately reproduces the q -exponential form of PQ(r ) and the power-law decay of CQ(s ) .

Rare b-hadron decays as probe of new physics

NASA Astrophysics Data System (ADS)

Lanfranchi, Gaia

2018-05-01

The unexpected absence of unambiguous signals of New Physics (NP) at the TeV scale at the Large Hadron Collider (LHC) puts today flavor physics at the forefront. In particular, rare decays of b-hadrons represent a unique probe to challenge the Standard Model (SM) paradigm and test models of NP at a scale much higher than that accessible by direct searches. This article reviews the status of the field.

Flume experimentation and simulation of bedrock channel processes

NASA Astrophysics Data System (ADS)

Thompson, Douglas; Wohl, Ellen

Flume experiments can provide cost effective, physically manageable miniature representations of complex bedrock channels. The inherent change in scale in such experiments requires a corresponding change in the scale of the forces represented in the flume system. Three modeling approaches have been developed that either ignore the scaling effects, utilize the change in scaled forces, or assume similarity of process between scales. An understanding of the nonlinear influence of a change in scale on all the forces involved is important to correctly analyze model results. Similarly, proper design and operation of flume experiments requires knowledge of the fundamental components of flume systems. Entrance and exit regions of the flume are used to provide good experimental conditions in the measurement region of the flume where data are collected. To insure reproducibility, large-scale turbulence must be removed in the head of the flume and velocity profiles must become fully developed in the entrance region. Water-surface slope and flow acceleration effects from downstream water-depth control must also be isolated in the exit region. Statistical design and development of representative channel substrate also influence model results in these systems. With proper experimental design, flumes may be used to investigate bedrock channel hydraulics, sediment-transport relations, and morphologic evolution. In particular, researchers have successfully used flume experiments to demonstrate the importance of turbulence and substrate characteristics in bedrock channel evolution. Turbulence often operates in a self perpetuating fashion, can erode bedrock walls with clear water and increase the mobility of sediment particles. Bedrock substrate influences channel evolution by offering varying resistance to erosion, controlling the location or type of incision and modifying the local influence of turbulence. An increased usage of scaled flume models may help to clarify the remaining uncertainties involving turbulence, channel substrate and bedrock channel evolution.

Assessment of the LV-C2 Stack Sampling Probe Location for Compliance with ANSI/HPS N13.1-1999

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glissmeyer, John A.; Antonio, Ernest J.; Flaherty, Julia E.

2015-09-01

This document reports on a series of tests conducted to assess the proposed air sampling location for the Hanford Tank Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) C2V (LV-C2) exhaust stack with respect to the applicable criteria regarding the placement of an air sampling probe. Federal regulations require that a sampling probe be located in the exhaust stack according to the criteria established by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999, Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stack and Ducts of Nuclear Facilities. These criteria address the capability of the sampling probemore » to extract a sample that represents the effluent stream. The tests were conducted on the LV-C2 scale model system. Based on the scale model tests, the location proposed for the air sampling probe in the scale model stack meets the requirements of the ANSI/HPS N13.1-1999 standard for velocity uniformity, flow angle, gas tracer and particle tracer uniformity. Additional velocity uniformity and flow angle tests on the actual stack will be necessary during cold startup to confirm the validity of the scale model results in representing the actual stack.« less

Force Characteristics in the Submerged and Planing Condition of a 1/5.78-Scale Model of a Hydro-Ski-Wheel Combination for the Grumman JRF-5 Airplane. TED No. NACA DE 357

NASA Technical Reports Server (NTRS)

Land, Norman S.; Pelz, Charles A.

1952-01-01

Force characteristics determined from tank tests of a 1/5.78 scale model of a hydro-ski-wheel combination for the Grumman JRF-5 airplane are presented. The model was tested in both the submerged and planing conditions over a range of trim, speed, and load sufficiently large to represent the most probable full-size conditions.

Global Modeling, Field Campaigns, Upscaling and Ray Desjardins

NASA Technical Reports Server (NTRS)

Sellers, P. J.; Hall, F. G.

2012-01-01

In the early 1980's, it became apparent that land surface radiation and energy budgets were unrealistically represented in Global Circulation models (GCM's), Shortly thereafter, it became clear that the land carbon budget was also poorly represented in Earth System Models (ESM's), A number of scientific communities, including GCM/ESM modelers, micrometeorologists, satellite data specialists and plant physiologists, came together to design field experiments that could be used to develop and validate the contemporary prototype land surface models. These experiments were designed to measure land surface fluxes of radiation, heat, water vapor and CO2 using a network of flux towers and other plot-scale techniques, coincident with satellite measurements of related state variables, The interdisciplinary teams involved in these experiments quickly became aware of the scale gap between plot-scale measurements (approx 10 - 100m), satellite measurements (100m - 10 km), and GCM grid areas (l0 - 200km). At the time, there was no established flux measurement capability to bridge these scale gaps. Then, a Canadian science learn led by Ray Desjardins started to actively participate in the design and execution of the experiments, with airborne eddy correlation providing the radically innovative bridge across the scale gaps, In a succession of brilliantly executed field campaigns followed up by convincing scientific analyses, they demonstrated that airborne eddy correlation allied with satellite data was the most powerful upscaling tool available to the community, The rest is history: the realism and credibility of weather and climate models has been enormously improved enormously over the last 25 years with immense benefits to the public and policymakers.

National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change

NASA Astrophysics Data System (ADS)

Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.

2006-12-01

Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to be 36% higher than those predicted during the second period. The climate projections of the PCM model had more positive impact on soil C sequestration than those predicted with the HadCM3 model.

Similarity and scale in catchment storm response

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Sivapalan, Murugesu; Beven, Keith

1993-01-01

Until recently, very little progress had been made in understanding the relationship between small-scale variability of topography, soil, and rainfalls and the storm response seen at the catchment scale. The work reviewed here represents the first attempt at a systematic theoretical framework for such understanding in the context of surface runoff generation by different processes. The parameterization of hydrological processes over a range of scales is examined, and the concept of the 'representative elementary area' (REA) is introduced. The REA is a fundamental scale for catchment modeling at which continuum assumptions can be applied for the spatially variable controls and parameters, and spatial patterns no longer have to be considered explicitly. The investigation of scale leads into the concept of hydrologic similarity in which the effects of the environmental controls on runoff generation and flood frequency response be investigated independently of catchment scale. The paper reviews the authors' initial results and hopefully will motivate others to also investigate the issues of hydrologic scale and similarity.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

Modelling potential changes in marine biogeochemistry due to large-scale offshore tidal energy extraction

NASA Astrophysics Data System (ADS)

van der Molen, Johan

2015-04-01

Tidal power generation through submerged turbine-type devices is in an advanced stage of testing, and large-scale applications are being planned in areas with high tidal current speeds. The potential impact of such large-scale applications on the hydrography can be investigated using hydrodynamical models. In addition, aspects of the potential impact on the marine ecosystem can be studied using biogeochemical models. In this study, the coupled hydrodynamics-biogeochemistry model GETM-ERSEM is used in a shelf-wide application to investigate the potential impact of large-scale tidal power generation in the Pentland Firth. A scenario representing the currently licensed power extraction suggested i) an average reduction in M2 tidal current velocities of several cm/s within the Pentland Firth, ii) changes in the residual circulation of several mm/s in the vicinity of the Pentland Firth, iii) an increase in M2 tidal amplitude of up to 1 cm to the west of the Pentland Firth, and iv) a reduction of several mm in M2 tidal amplitude along the east coast of the UK. A second scenario representing 10 times the currently licensed power extraction resulted in changes that were approximately 10 times as large. Simulations including the biogeochemistry model for these scenarios are currently in preparation, and first results will be presented at the the conference, aiming at impacts on primary production and benthic production.

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

Influence of Boundary Conditions on Simulated U.S. Air Quality

EPA Science Inventory

One of the key inputs to regional-scale photochemical models frequently used in air quality planning and forecasting applications are chemical boundary conditions representing background pollutant concentrations originating outside the regional modeling domain. A number of studie...

Statewide mesoscopic simulation for Wyoming.

DOT National Transportation Integrated Search

2013-10-01

This study developed a mesoscopic simulator which is capable of representing both city-level and statewide roadway : networks. The key feature of such models are the integration of (i) a traffic flow model which is efficient enough to : scale to larg...

Deriving the Characteristic Scale for Effectively Monitoring Heavy Metal Stress in Rice by Assimilation of GF-1 Data with the WOFOST Model

PubMed Central

Huang, Zhi; Liu, Xiangnan; Jin, Ming; Ding, Chao; Jiang, Jiale; Wu, Ling

2016-01-01

Accurate monitoring of heavy metal stress in crops is of great importance to assure agricultural productivity and food security, and remote sensing is an effective tool to address this problem. However, given that Earth observation instruments provide data at multiple scales, the choice of scale for use in such monitoring is challenging. This study focused on identifying the characteristic scale for effectively monitoring heavy metal stress in rice using the dry weight of roots (WRT) as the representative characteristic, which was obtained by assimilation of GF-1 data with the World Food Studies (WOFOST) model. We explored and quantified the effect of the important state variable LAI (leaf area index) at various spatial scales on the simulated rice WRT to find the critical scale for heavy metal stress monitoring using the statistical characteristics. Furthermore, a ratio analysis based on the varied heavy metal stress levels was conducted to identify the characteristic scale. Results indicated that the critical threshold for investigating the rice WRT in monitoring studies of heavy metal stress was larger than 64 m but smaller than 256 m. This finding represents a useful guideline for choosing the most appropriate imagery. PMID:26959033

Preliminary Tests in the NACA Free-Spinning Wind Tunnel

NASA Technical Reports Server (NTRS)

Zimmerman, C H

1937-01-01

Typical models and the testing technique used in the NACA free-spinning wind tunnel are described in detail. The results of tests on two models afford a comparison between the spinning characteristics of scale models in the tunnel and of the airplanes that they represent.

A model framework to represent plant-physiology and rhizosphere processes in soil profile simulation models

NASA Astrophysics Data System (ADS)

Vanderborght, J.; Javaux, M.; Couvreur, V.; Schröder, N.; Huber, K.; Abesha, B.; Schnepf, A.; Vereecken, H.

2013-12-01

Plant roots play a crucial role in several key processes in soils. Besides their impact on biogeochemical cycles and processes, they also have an important influence on physical processes such as water flow and transport of dissolved substances in soils. Interaction between plant roots and soil processes takes place at different scales and ranges from the scale of an individual root and its directly surrounding soil or rhizosphere over the scale of a root system of an individual plant in a soil profile to the scale of vegetation patterns in landscapes. Simulation models that are used to predict water flow and solute transport in soil-plant systems mainly focus on the individual plant root system scale, parameterize single-root scale phenomena, and aggregate the root system scale to the vegetation scale. In this presentation, we will focus on the transition from the single root to the root system scale. Using high resolution non-invasive imaging techniques and methods, gradients in soil properties and states around roots and their difference from the bulk soil properties could be demonstrated. Recent developments in plant sciences provide new insights in the mechanisms that control water fluxes in plants and in the adaptation of root properties or root plasticity to changing soil conditions. However, since currently used approaches to simulate root water uptake neither resolve these small scale processes nor represent processes and controls within the root system, transferring this information to the whole soil-plant system scale is a challenge. Using a simulation model that describes flow and transport processes in the soil, resolves flow and transport towards individual roots, and describes flow and transport within the root system, such a transfer could be achieved. We present a few examples that illustrate: (i) the impact of changed rhizosphere hydraulic properties, (ii) the effect of root hydraulic properties and root system architecture, (iii) the regulation of plant transpiration by root-zone produced plant hormones, and (iv) the impact of salt accumulation at the soil-root interface on root water uptake. We further propose a framework how this process knowledge could be implemented in root zone simulation models that do not resolve small scale processes.

Experiments with data assimilation in comprehensive air quality models: Impacts on model predictions and observation requirements (Invited)

NASA Astrophysics Data System (ADS)

Mathur, R.

2009-12-01

Emerging regional scale atmospheric simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions. Sophisticated air quality modeling systems are needed to develop effective abatement strategies that focus on simultaneously controlling multiple criteria pollutants as well as use in providing short term air quality forecasts. In recent years the applications of such models is continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physical and chemical atmospheric processes occurring at these disparate spatial and temporal scales requires the use of observation data beyond traditional in-situ networks so that the model simulations can be reasonably constrained. Preliminary applications of assimilation of remote sensing and aloft observations within a comprehensive regional scale atmospheric chemistry-transport modeling system will be presented: (1) A methodology is developed to assimilate MODIS aerosol optical depths in the model to represent the impacts long-range transport associated with the summer 2004 Alaskan fires on surface-level regional fine particulate matter (PM2.5) concentrations across the Eastern U.S. The episodic impact of this pollution transport event on PM2.5 concentrations over the eastern U.S. during mid-July 2004, is quantified through the complementary use of the model with remotely-sensed, aloft, and surface measurements; (2) Simple nudging experiments with limited aloft measurements are performed to identify uncertainties in model representations of physical processes and assess the potential use of such measurements in improving the predictive capability of atmospheric chemistry-transport models. The results from these early applications will be discussed in context of uncertainties in the model and in the remote sensing data and needs for defining a future optimum observing strategy.

Modeling stream temperature in the Anthropocene: An earth system modeling approach

DOE PAGES

Li, Hong -Yi; Leung, L. Ruby; Tesfa, Teklu; ...

2015-10-29

A new large-scale stream temperature model has been developed within the Community Earth System Model (CESM) framework. The model is coupled with the Model for Scale Adaptive River Transport (MOSART) that represents river routing and a water management model (WM) that represents the effects of reservoir operations and water withdrawals on flow regulation. The coupled models allow the impacts of reservoir operations and withdrawals on stream temperature to be explicitly represented in a physically based and consistent way. The models have been applied to the Contiguous United States driven by observed meteorological forcing. It is shown that the model ismore » capable of reproducing stream temperature spatiotemporal variation satisfactorily by comparison against the observed streamflow from over 320 USGS stations. Including water management in the models improves the agreement between the simulated and observed streamflow at a large number of stream gauge stations. Both climate and water management are found to have important influence on the spatiotemporal patterns of stream temperature. More interestingly, it is quantitatively estimated that reservoir operation could cool down stream temperature in the summer low-flow season (August – October) by as much as 1~2oC over many places, as water management generally mitigates low flow, which has important implications to aquatic ecosystems. In conclusion, sensitivity of the simulated stream temperature to input data and reservoir operation rules used in the WM model motivates future directions to address some limitations in the current modeling framework.« less

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

Acoustic Treatment Design Scaling Methods. Phase 2

NASA Technical Reports Server (NTRS)

Clark, L. (Technical Monitor); Parrott, T. (Technical Monitor); Jones, M. (Technical Monitor); Kraft, R. E.; Yu, J.; Kwan, H. W.; Beer, B.; Seybert, A. F.; Tathavadekar, P.

2003-01-01

The ability to design, build and test miniaturized acoustic treatment panels on scale model fan rigs representative of full scale engines provides not only cost-savings, but also an opportunity to optimize the treatment by allowing multiple tests. To use scale model treatment as a design tool, the impedance of the sub-scale liner must be known with confidence. This study was aimed at developing impedance measurement methods for high frequencies. A normal incidence impedance tube method that extends the upper frequency range to 25,000 Hz. without grazing flow effects was evaluated. The free field method was investigated as a potential high frequency technique. The potential of the two-microphone in-situ impedance measurement method was evaluated in the presence of grazing flow. Difficulties in achieving the high frequency goals were encountered in all methods. Results of developing a time-domain finite difference resonator impedance model indicated that a re-interpretation of the empirical fluid mechanical models used in the frequency domain model for nonlinear resistance and mass reactance may be required. A scale model treatment design that could be tested on the Universal Propulsion Simulator vehicle was proposed.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Forgetting in Immediate Serial Recall: Decay, Temporal Distinctiveness, or Interference?

ERIC Educational Resources Information Center

Oberauer, Klaus; Lewandowsky, Stephan

2008-01-01

Three hypotheses of forgetting from immediate memory were tested: time-based decay, decreasing temporal distinctiveness, and interference. The hypotheses were represented by 3 models of serial recall: the primacy model, the SIMPLE (scale-independent memory, perception, and learning) model, and the SOB (serial order in a box) model, respectively.…

Acoustic Treatment Design Scaling Methods. Volume 3; Test Plans, Hardware, Results, and Evaluation

NASA Technical Reports Server (NTRS)

Yu, J.; Kwan, H. W.; Echternach, D. K.; Kraft, R. E.; Syed, A. A.

1999-01-01

The ability to design, build, and test miniaturized acoustic treatment panels on scale-model fan rigs representative of the full-scale engine provides not only a cost-savings, but an opportunity to optimize the treatment by allowing tests of different designs. To be able to use scale model treatment as a full-scale design tool, it is necessary that the designer be able to reliably translate the scale model design and performance to an equivalent full-scale design. The primary objective of the study presented in this volume of the final report was to conduct laboratory tests to evaluate liner acoustic properties and validate advanced treatment impedance models. These laboratory tests include DC flow resistance measurements, normal incidence impedance measurements, DC flow and impedance measurements in the presence of grazing flow, and in-duct liner attenuation as well as modal measurements. Test panels were fabricated at three different scale factors (i.e., full-scale, half-scale, and one-fifth scale) to support laboratory acoustic testing. The panel configurations include single-degree-of-freedom (SDOF) perforated sandwich panels, SDOF linear (wire mesh) liners, and double-degree-of-freedom (DDOF) linear acoustic panels.

Numerical Upscaling of Solute Transport in Fractured Porous Media Based on Flow Aligned Blocks

NASA Astrophysics Data System (ADS)

Leube, P.; Nowak, W.; Sanchez-Vila, X.

2013-12-01

High-contrast or fractured-porous media (FPM) pose one of the largest unresolved challenges for simulating large hydrogeological systems. The high contrast in advective transport between fast conduits and low-permeability rock matrix, including complex mass transfer processes, leads to the typical complex characteristics of early bulk arrivals and long tailings. Adequate direct representation of FPM requires enormous numerical resolutions. For large scales, e.g. the catchment scale, and when allowing for uncertainty in the fracture network architecture or in matrix properties, computational costs quickly reach an intractable level. In such cases, multi-scale simulation techniques have become useful tools. They allow decreasing the complexity of models by aggregating and transferring their parameters to coarser scales and so drastically reduce the computational costs. However, these advantages come at a loss of detail and accuracy. In this work, we develop and test a new multi-scale or upscaled modeling approach based on block upscaling. The novelty is that individual blocks are defined by and aligned with the local flow coordinates. We choose a multi-rate mass transfer (MRMT) model to represent the remaining sub-block non-Fickian behavior within these blocks on the coarse scale. To make the scale transition simple and to save computational costs, we capture sub-block features by temporal moments (TM) of block-wise particle arrival times to be matched with the MRMT model. By predicting spatial mass distributions of injected tracers in a synthetic test scenario, our coarse-scale solution matches reasonably well with the corresponding fine-scale reference solution. For predicting higher TM-orders (such as arrival time and effective dispersion), the prediction accuracy steadily decreases. This is compensated to some extent by the MRMT model. If the MRMT model becomes too complex, it loses its effect. We also found that prediction accuracy is sensitive to the choice of the effective dispersion coefficients and on the block resolution. A key advantage of the flow-aligned blocks is that the small-scale velocity field is reproduced quite accurately on the block-scale through their flow alignment. Thus, the block-scale transverse dispersivities remain in the similar magnitude as local ones, and they do not have to represent macroscopic uncertainty. Also, the flow-aligned blocks minimize numerical dispersion when solving the large-scale transport problem.

Modeling the Distribution of Migratory Bird Stopovers to Inform Landscape-Scale Siting of Wind Development

PubMed Central

Pocewicz, Amy; Estes-Zumpf, Wendy A.; Andersen, Mark D.; Copeland, Holly E.; Keinath, Douglas A.; Griscom, Hannah R.

2013-01-01

Conservation of migratory birds requires understanding the distribution of and potential threats to their migratory habitats. However, although migratory birds are protected under international treaties, few maps have been available to represent migration at a landscape scale useful to target conservation efforts or inform the siting of wind energy developments that may affect migratory birds. To fill this gap, we developed models that predict where four groups of birds concentrate or stopover during their migration through the state of Wyoming, USA: raptors, wetland, riparian and sparse grassland birds. The models were based on existing literature and expert knowledge concerning bird migration behavior and ecology and validated using expert ratings and known occurrences. There was significant agreement between migratory occurrence data and migration models for all groups except raptors, and all models ranked well with experts. We measured the overlap between the migration concentration models and a predictive model of wind energy development to assess the potential exposure of migratory birds to wind development and illustrate the utility of migratory concentration models for landscape-scale planning. Wind development potential is high across 15% of Wyoming, and 73% of this high potential area intersects important migration concentration areas. From 5.2% to 18.8% of each group’s important migration areas was represented within this high wind potential area, with the highest exposures for sparse grassland birds and the lowest for riparian birds. Our approach could be replicated elsewhere to fill critical data gaps and better inform conservation priorities and landscape-scale planning for migratory birds. PMID:24098379

Topside Electron Density Representations for Middle and High Latitudes: A Topside Parameterization for E-CHAIM Based On the NeQuick

NASA Astrophysics Data System (ADS)

Themens, David R.; Jayachandran, P. T.; Bilitza, Dieter; Erickson, Philip J.; Häggström, Ingemar; Lyashenko, Mykhaylo V.; Reid, Benjamin; Varney, Roger H.; Pustovalova, Ljubov

2018-02-01

In this study, we present a topside model representation to be used by the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM). In the process of this, we also present a comprehensive evaluation of the NeQuick's, and by extension the International Reference Ionosphere's, topside electron density model for middle and high latitudes in the Northern Hemisphere. Using data gathered from all available incoherent scatter radars, topside sounders, and Global Navigation Satellite System Radio Occultation satellites, we show that the current NeQuick parameterization suboptimally represents the shape of the topside electron density profile at these latitudes and performs poorly in the representation of seasonal and solar cycle variations of the topside scale thickness. Despite this, the simple, one variable, NeQuick model is a powerful tool for modeling the topside ionosphere. By refitting the parameters that define the maximum topside scale thickness and the rate of increase of the scale height within the NeQuick topside model function, r and g, respectively, and refitting the model's parameterization of the scale height at the F region peak, H0, we find considerable improvement in the NeQuick's ability to represent the topside shape and behavior. Building on these results, we present a new topside model extension of the E-CHAIM based on the revised NeQuick function. Overall, root-mean-square errors in topside electron density are improved over the traditional International Reference Ionosphere/NeQuick topside by 31% for a new NeQuick parameterization and by 36% for a newly proposed topside for E-CHAIM.

Integrated Modeling for Watershed Ecosystem Services Assessment and Forecasting

EPA Science Inventory

Regional scale watershed management decisions must be informed by the science-based relationship between anthropogenic activities on the landscape and the change in ecosystem structure, function, and services that occur as a result. We applied process-based models that represent...

Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

NASA Astrophysics Data System (ADS)

Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

2018-01-01

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

A Temporal Ratio Model of Memory

ERIC Educational Resources Information Center

Brown, Gordon D. A.; Neath, Ian; Chater, Nick

2007-01-01

A model of memory retrieval is described. The model embodies four main claims: (a) temporal memory--traces of items are represented in memory partly in terms of their temporal distance from the present; (b) scale-similarity--similar mechanisms govern retrieval from memory over many different timescales; (c) local distinctiveness--performance on a…

A scalable plant-resolving radiative transfer model based on optimized GPU ray tracing

USDA-ARS?s Scientific Manuscript database

A new model for radiative transfer in participating media and its application to complex plant canopies is presented. The goal was to be able to efficiently solve complex canopy-scale radiative transfer problems while also representing sub-plant heterogeneity. In the model, individual leaf surfaces ...

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modeled processes were examined and enhanced to suitably represent the extended space and timesca...

Test Report for MSFC Test No. 83-2: Pressure scaled water impact test of a 12.5 inch diameter model of the Space Shuttle solid rocket booster filament wound case and external TVC PCD

NASA Technical Reports Server (NTRS)

1983-01-01

Water impact tests using a 12.5 inch diameter model representing a 8.56 percent scale of the Space Shuttle Solid Rocket Booster configuration were conducted. The two primary objectives of this SRB scale model water impact test program were: 1. Obtain cavity collapse applied pressure distributions for the 8.56 percent rigid body scale model FWC pressure magnitudes as a function of full-scale initial impact conditions at vertical velocities from 65 to 85 ft/sec, horizontal velocities from 0 to 45 ft/sec, and angles from -10 to +10 degrees. 2. Obtain rigid body applied pressures on the TVC pod and aft skirt internal stiffener rings at initial impact and cavity collapse loading events. In addition, nozzle loads were measured. Full scale vertical velocities of 65 to 85 ft/sec, horizontal velocities of 0 to 45 ft/sec, and impact angles from -10 to +10 degrees simulated.

The sense and non-sense of plot-scale, catchment-scale, continental-scale and global-scale hydrological modelling

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Heistermann, Maik; Francke, Till

2017-04-01

Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, D.; Bellugi, D.; McKean, J. A.; Dietrich, W.

2012-12-01

The infinite slope model is the basis for almost all watershed scale slope stability models. However, it assumes that a potential landslide is infinitely long and wide. As a result, it cannot represent resistance at the margins of a potential landslide (e.g. from lateral roots), and is unable to predict the size of a potential landslide. Existing three-dimensional models generally require computationally expensive numerical solutions and have previously been applied only at the hillslope scale. Here we derive an alternative analytical treatment that accounts for lateral resistance by representing the forces acting on each margin of an unstable block. We apply 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure using a log-spiral method on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion is an exponential function of soil depth. We benchmark this treatment against other more complete approaches (Finite Element (FE) and closed form solutions) and find that our model: 1) converges on the infinite slope predictions as length / depth and width / depth ratios become large; 2) agrees with the predictions from state-of-the-art FE models to within +/- 30% error, for the specific cases in which these can be applied. We then test our model's ability to predict failure of an actual (mapped) landslide where the relevant parameters are relatively well constrained. We find that our model predicts failure at the observed location with a nearly identical shape and predicts that larger or smaller shapes conformal to the observed shape are indeed more stable. Finally, we perform a sensitivity analysis using our model to show that lateral reinforcement sets a minimum landslide size, while the additional strength at the downslope boundary means that the optimum shape for a given size is longer in a downslope direction. However, reinforcement effects cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of spatial patterns of key parameters (e.g. pore water pressure) and motivating the model's watershed scale application. This watershed scale application requires an efficient method to find the least stable shapes among an almost infinite set. However, when applied in this context, it allows a more complete examination of the controls on landslide size, shape and location.

Landscape-scale soil moisture heterogeneity and its influence on surface fluxes at the Jornada LTER site: Evaluating a new model parameterization for subgrid-scale soil moisture variability

NASA Astrophysics Data System (ADS)

Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.

2017-12-01

Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting events and more prolonged response to drying cycles, as opposed to binary behavior in the control.

A new surface-process model for landscape evolution at a mountain belt scale

NASA Astrophysics Data System (ADS)

Willett, Sean D.; Braun, Jean; Herman, Frederic

2010-05-01

We present a new surface process model designed for modeling surface erosion and mass transport at an orogenic scale. Modeling surface processes at a large-scale is difficult because surface geomorphic processes are frequently described at the scale of a few meters, and such resolution cannot be represented in orogen-scale models operating over hundreds of square kilometers. We circumvent this problem by implementing a hybrid numerical -- analytical model. Like many previous models, the model is based on a numerical fluvial network represented by a series of nodes linked by model rivers in a descending network, with fluvial incision and sediment transport defined by laws operating on this network. However we only represent the largest rivers in the landscape by nodes in this model. Low-order rivers and water divides between large rivers are determined from analytical solutions assuming steady-state conditions with respect to the local river channel. The analytical solution includes the same fluvial incision law as the large rivers and a channel head with a specified size and mean slope. This permits a precise representation of the position of water divides between river basins. This is a key characteristic in landscape evolution as divide migration provides a positive feedback between river incision and a consequent increase in drainage area. The analytical solution also provides an explicit criterion for river capture, which occurs once a water divide migrates to its neighboring channel. This algorithm avoids the artificial network organization that often results from meshing and remeshing algorithms in numerical models. We demonstrate the use of this model with several simple examples including uniform uplift of a block, simultaneous uplift and shortening of a block, and a model involving strike slip faulting. We find a strong dependence on initial condition, but also a surprisingly strong dependence on channel head height parameters. Low channel heads, as expected, lead to more fluvial capture, but with low initial relief initial and a small channel-head height, runaway capture is common, with a few rivers capturing much of the available drainage area. With larger channel-head relief, lateral capture of rivers is less common, resulting in evenly spaced river basins. Basin spacing ratios matching those observed in nature are obtained for specific channel head parameters. These models thus demonstrate the mixed control on basin characteristics by antecedent river networks and channel-head parameters, which control the mobility of drainage basin water divides.

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lackmann, Gary

2013-06-10

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured withmore » sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance activity. This will allow (i) a direct comparison of future TC activity that could be expected for an active or inactive season in an altered climate regime, and (ii) a measure of the level of uncertainty and variability in TC activity resulting from different carbon emission scenarios.« less

Residence-time framework for modeling multicomponent reactive transport in stream hyporheic zones

NASA Astrophysics Data System (ADS)

Painter, S. L.; Coon, E. T.; Brooks, S. C.

2017-12-01

Process-based models for transport and transformation of nutrients and contaminants in streams require tractable representations of solute exchange between the stream channel and biogeochemically active hyporheic zones. Residence-time based formulations provide an alternative to detailed three-dimensional simulations and have had good success in representing hyporheic exchange of non-reacting solutes. We extend the residence-time formulation for hyporheic transport to accommodate general multicomponent reactive transport. To that end, the integro-differential form of previous residence time models is replaced by an equivalent formulation based on a one-dimensional advection dispersion equation along the channel coupled at each channel location to a one-dimensional transport model in Lagrangian travel-time form. With the channel discretized for numerical solution, the associated Lagrangian model becomes a subgrid model representing an ensemble of streamlines that are diverted into the hyporheic zone before returning to the channel. In contrast to the previous integro-differential forms of the residence-time based models, the hyporheic flowpaths have semi-explicit spatial representation (parameterized by travel time), thus allowing coupling to general biogeochemical models. The approach has been implemented as a stream-corridor subgrid model in the open-source integrated surface/subsurface modeling software ATS. We use bedform-driven flow coupled to a biogeochemical model with explicit microbial biomass dynamics as an example to show that the subgrid representation is able to represent redox zonation in sediments and resulting effects on metal biogeochemical dynamics in a tractable manner that can be scaled to reach scales.

Determining Representative Elementary Volume For Multiple Petrophysical Parameters using a Convex Hull Analysis of Digital Rock Data

NASA Astrophysics Data System (ADS)

Shah, S.; Gray, F.; Yang, J.; Crawshaw, J.; Boek, E.

2016-12-01

Advances in 3D pore-scale imaging and computational methods have allowed an exceptionally detailed quantitative and qualitative analysis of the fluid flow in complex porous media. A fundamental problem in pore-scale imaging and modelling is how to represent and model the range of scales encountered in porous media, starting from the smallest pore spaces. In this study, a novel method is presented for determining the representative elementary volume (REV) of a rock for several parameters simultaneously. We calculate the two main macroscopic petrophysical parameters, porosity and single-phase permeability, using micro CT imaging and Lattice Boltzmann (LB) simulations for 14 different porous media, including sandpacks, sandstones and carbonates. The concept of the `Convex Hull' is then applied to calculate the REV for both parameters simultaneously using a plot of the area of the convex hull as a function of the sub-volume, capturing the different scales of heterogeneity from the pore-scale imaging. The results also show that the area of the convex hull (for well-chosen parameters such as the log of the permeability and the porosity) decays exponentially with sub-sample size suggesting a computationally efficient way to determine the system size needed to calculate the parameters to high accuracy (small convex hull area). Finally we propose using a characteristic length such as the pore size to choose an efficient absolute voxel size for the numerical rock.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

Finite Element Multi-scale Modeling of Chemical Segregation in Steel Solidification Taking into Account the Transport of Equiaxed Grains

NASA Astrophysics Data System (ADS)

Nguyen, Thi-Thuy-My; Gandin, Charles-André; Combeau, Hervé; Založnik, Miha; Bellet, Michel

2018-02-01

The transport of solid crystals in the liquid pool during solidification of large ingots is known to have a significant effect on their final grain structure and macrosegregation. Numerical modeling of the associated physics is challenging since complex and strong interactions between heat and mass transfer at the microscopic and macroscopic scales must be taken into account. The paper presents a finite element multi-scale solidification model coupling nucleation, growth, and solute diffusion at the microscopic scale, represented by a single unique grain, while also including transport of the liquid and solid phases at the macroscopic scale of the ingots. The numerical resolution is based on a splitting method which sequentially describes the evolution and interaction of quantities into a transport and a growth stage. This splitting method reduces the non-linear complexity of the set of equations and is, for the first time, implemented using the finite element method. This is possible due to the introduction of an artificial diffusion in all conservation equations solved by the finite element method. Simulations with and without grain transport are compared to demonstrate the impact of solid phase transport on the solidification process as well as the formation of macrosegregation in a binary alloy (Sn-5 wt pct Pb). The model is also applied to the solidification of the binary alloy Fe-0.36 wt pct C in a domain representative of a 3.3-ton steel ingot.

Multi-scale Pore Imaging Techniques to Characterise Heterogeneity Effects on Flow in Carbonate Rock

NASA Astrophysics Data System (ADS)

Shah, S. M.

2017-12-01

Digital rock analysis and pore-scale studies have become an essential tool in the oil and gas industry to understand and predict the petrophysical and multiphase flow properties for the assessment and exploitation of hydrocarbon reserves. Carbonate reservoirs, accounting for majority of the world's hydrocarbon reserves, are well known for their heterogeneity and multiscale pore characteristics. The pore sizes in carbonate rock can vary over orders of magnitudes, the geometry and topology parameters of pores at different scales have a great impact on flow properties. A pore-scale study is often comprised of two key procedures: 3D pore-scale imaging and numerical modelling techniques. The fundamental problem in pore-scale imaging and modelling is how to represent and model the different range of scales encountered in porous media, from the pore-scale to macroscopic petrophysical and multiphase flow properties. However, due to the restrictions of image size vs. resolution, the desired detail is rarely captured at the relevant length scales using any single imaging technique. Similarly, direct simulations of transport properties in heterogeneous rocks with broad pore size distributions are prohibitively expensive computationally. In this study, we present the advances and review the practical limitation of different imaging techniques varying from core-scale (1mm) using Medical Computed Tomography (CT) to pore-scale (10nm - 50µm) using Micro-CT, Confocal Laser Scanning Microscopy (CLSM) and Focussed Ion Beam (FIB) to characterise the complex pore structure in Ketton carbonate rock. The effect of pore structure and connectivity on the flow properties is investigated using the obtained pore scale images of Ketton carbonate using Pore Network and Lattice-Boltzmann simulation methods in comparison with experimental data. We also shed new light on the existence and size of the Representative Element of Volume (REV) capturing the different scales of heterogeneity from the pore-scale imaging.

Uncertainty prediction for PUB

NASA Astrophysics Data System (ADS)

Mendiondo, E. M.; Tucci, C. M.; Clarke, R. T.; Castro, N. M.; Goldenfum, J. A.; Chevallier, P.

2003-04-01

IAHS’ initiative of Prediction in Ungaged Basins (PUB) attempts to integrate monitoring needs and uncertainty prediction for river basins. This paper outlines alternative ways of uncertainty prediction which could be linked with new blueprints for PUB, thereby showing how equifinality-based models should be grasped using practical strategies of gauging like the Nested Catchment Experiment (NCE). Uncertainty prediction is discussed from observations of Potiribu Project, which is a NCE layout at representative basins of a suptropical biome of 300,000 km2 in South America. Uncertainty prediction is assessed at the microscale (1 m2 plots), at the hillslope (0,125 km2) and at the mesoscale (0,125 - 560 km2). At the microscale, uncertainty-based models are constrained by temporal variations of state variables with changing likelihood surfaces of experiments using Green-Ampt model. Two new blueprints emerged from this NCE for PUB: (1) the Scale Transferability Scheme (STS) at the hillslope scale and the Integrating Process Hypothesis (IPH) at the mesoscale. The STS integrates a multi-dimensional scaling with similarity thresholds, as a generalization of the Representative Elementary Area (REA), using spatial correlation from point (distributed) to area (lumped) process. In this way, STS addresses uncertainty-bounds of model parameters, into an upscaling process at the hillslope. In the other hand, the IPH approach regionalizes synthetic hydrographs, thereby interpreting the uncertainty bounds of streamflow variables. Multiscale evidences from Potiribu NCE layout show novel pathways of uncertainty prediction under a PUB perspective in representative basins of world biomes.

The Prosocial and Antisocial Behavior in Sport Scale.

PubMed

Kavussanu, Maria; Boardley, Ian D

2009-02-01

This research aimed to (a) develop a measure of prosocial and antisocial behavior in sport, (b) examine its invariance across sex and sport, and (c) provide evidence for its discriminant and concurrent validity. We conducted two studies. In study 1, team sport athletes (N=1,213) recruited from 103 teams completed questionnaires assessing demographics and prosocial and antisocial behaviors in sport. Factor analyses revealed two factors representing prosocial behavior and two factors representing antisocial behavior. The model had a very good fit to the data and showed configural, metric, and scalar invariance across sex and sport. The final scale consisted of 20 items. In Study 2, team-sport athletes (N=106) completed the scale and measures of empathy and goal orientation. Analyses provided support for the discriminant and concurrent validity of the scale. In conclusion, the new scale can be used to measure prosocial and antisocial behaviors in team sport.

Investigation of Coupled model of Pore network and Continuum in shale gas

NASA Astrophysics Data System (ADS)

Cao, G.; Lin, M.

2016-12-01

Flow in shale spanning over many scales, makes the majority of conventional treatment methods disabled. For effectively simulating, a coupled model of pore-scale and continuum-scale was proposed in this paper. Based on the SEM image, we decompose organic-rich-shale into two subdomains: kerogen and inorganic matrix. In kerogen, the nanoscale pore-network is the main storage space and migration pathway so that the molecular phenomena (slip and diffusive transport) is significant. Whereas, inorganic matrix, with relatively large pores and micro fractures, the flow is approximate to Darcy. We use pore-scale network models (PNM) to represent kerogen and continuum-scale models (FVM or FEM) to represent matrix. Finite element mortars are employed to couple pore- and continuum-scale models by enforcing continuity of pressures and fluxes at shared boundary interfaces. In our method, the process in the coupled model is described by pressure square equation, and uses Dirichlet boundary conditions. We discuss several problems: the optimal element number of mortar faces, two categories boundary faces of pore network, the difference between 2D and 3D models, and the difference between continuum models FVM and FEM in mortars. We conclude that: (1) too coarse mesh in mortars will decrease the accuracy, while too fine mesh will lead to an ill-condition even singular system, the optimal element number is depended on boundary pores and nodes number. (2) pore network models are adjacent to two different mortar faces (PNM to PNM, PNM to continuum model), incidental repeated mortar nodes must be deleted. (3) 3D models can be replaced by 2D models under certain condition. (4) FVM is more convenient than FEM, for its simplicity in assigning interface nodes pressure and calculating interface fluxes. This work is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB10020302), the 973 Program (2014CB239004), the Key Instrument Developing Project of the CAS (ZDYZ2012-1-08-02), the National Natural Science Foundation of China (41574129).

On the dimensionality of the stress-related growth scale: one, three, or seven factors?

PubMed

Roesch, Scott C; Rowley, Anthony A; Vaughn, Allison A

2004-06-01

We examined the factorial validity and dimensionality of the Stress-Related Growth Scale (SRGS; Park, Cohen, & Murch, 1996) using a large multiethnic sample (n = 1,070). Exploratory and confirmatory factor analyses suggested that a multidimensional representation of the SRGS fit better than a unidimensional representation. Specifically, we cross-validated both a 3-factor model and a 7-factor model using confirmatory factor analysis and were shown to be invariant across gender and ethnic groups. The 3-factor model was represented by global dimensions of growth that included rational/mature thinking, affective/emotional growth, and religious/spiritual growth. We replicated the 7-factor model of Armeli, Gunthert, and Cohen (2001) and it represented more specific components of growth such as Self-Understanding and Treatment of Others. However, some factors of the 7-factor model had questionable internal consistency and were strongly intercorrelated, suggesting redundancy. The findings support the notion that the factor structure of both the original 1-factor and revised 7-factor models are unstable and that the 3-factor model developed in this research has more reliable psychometric properties and structure.

A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-04-01

The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove-compute-restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets.

Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems

NASA Astrophysics Data System (ADS)

Travers, M.; Shin, Y.-J.; Jennings, S.; Cury, P.

2007-12-01

End-to-end models that represent ecosystem components from primary producers to top predators, linked through trophic interactions and affected by the abiotic environment, are expected to provide valuable tools for assessing the effects of climate change and fishing on ecosystem dynamics. Here, we review the main process-based approaches used for marine ecosystem modelling, focusing on the extent of the food web modelled, the forcing factors considered, the trophic processes represented, as well as the potential use and further development of the models. We consider models of a subset of the food web, models which represent the first attempts to couple low and high trophic levels, integrated models of the whole ecosystem, and size spectrum models. Comparisons within and among these groups of models highlight the preferential use of functional groups at low trophic levels and species at higher trophic levels and the different ways in which the models account for abiotic processes. The model comparisons also highlight the importance of choosing an appropriate spatial dimension for representing organism dynamics. Many of the reviewed models could be extended by adding components and by ensuring that the full life cycles of species components are represented, but end-to-end models should provide full coverage of ecosystem components, the integration of physical and biological processes at different scales and two-way interactions between ecosystem components. We suggest that this is best achieved by coupling models, but there are very few existing cases where the coupling supports true two-way interaction. The advantages of coupling models are that the extent of discretization and representation can be targeted to the part of the food web being considered, making their development time- and cost-effective. Processes such as predation can be coupled to allow the propagation of forcing factors effects up and down the food web. However, there needs to be a stronger focus on enabling two-way interaction, carefully selecting the key functional groups and species, reconciling different time and space scales and the methods of converting between energy, nutrients and mass.

Conceptualizing Native Identity with a Multidimensional Model

ERIC Educational Resources Information Center

Gonzalez, John; Bennett, Russell

2011-01-01

This study reports on a Native Identity Scale (NIS) adapted from an African American identity scale (Sellers et al., 1997). American Indian (AIs) and First Nations Canadian participants (N = 199) completed the NIS at powwows in the Upper Midwest. The majority of respondents were Ojibwe, but other tribal groups were represented. A principal…

Least Squares Metric, Unidimensional Scaling of Multivariate Linear Models.

ERIC Educational Resources Information Center

Poole, Keith T.

1990-01-01

A general approach to least-squares unidimensional scaling is presented. Ordering information contained in the parameters is used to transform the standard squared error loss function into a discrete rather than continuous form. Monte Carlo tests with 38,094 ratings of 261 senators, and 1,258 representatives demonstrate the procedure's…

Multi-time scale analysis of the spatial representativeness of in situ soil moisture data within satellite footprints

USDA-ARS?s Scientific Manuscript database

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies ...

A Hydrologic Routing Model Based on Geomorphological Characteristics of the River Network

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Quintero, F.; Ghimire, G.; Rojas, M.

2017-12-01

The Iowa Flood Center (IFC) provides streamflow forecasts for about 2000 locations in Iowa using a real-time distributed hydrologic model, forced with radar and raingage rainfall information. The model structure is based on ordinary differential equations that represent the flow of water from the hillslopes to the channels of the river network. The formulation of the routing of water across the rivers constitutes a fundamental aspect of the model, because this component is mostly responsible for providing estimates of the time-to-peak and peak magnitude. The routing model structure of the system is based on the scaling properties of river velocity with the discharge and drainage area of the channel, which can be written in terms of a power-law function. This study examines how this scaling relation is connected to the Horton-Strahler order of the channel network. This evaluation represents a step forward towards formulating model structures that are based on characteristics that are invariant across spatial scales. We proposed a routing model for every different Horton orders of the network, by adjusting a power-law function to available observations of velocity and discharge provided by USGS. The models were implemented into the Hillslope-Link Model (HLM) of the IFC for offline evaluation. Model simulations were compared to discharge observations to assess their performance, and compared to simulations obtained with other hydrologic routing schemes, to determine if the new formulation improves performance of the model.

Finite Element Simulation of Three Full-Scale Crash Tests for Cessna 172 Aircraft

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Warren, Jerry E., Jr.

2017-01-01

The NASA Emergency Locator Transmitter Survivability and Reliability (ELT-SAR) project was initiated in 2013 to assess the crash performance standards for the next generation of emergency locator transmitter (ELT) systems. Three Cessna 172 aircraft were acquired to perform crash testing at NASA Langley Research Center's Landing and Impact Research Facility. Full-scale crash tests were conducted in the summer of 2015 and each test article was subjected to severe, but survivable, impact conditions including a flare-to-stall during emergency landing, and two controlled-flight-into-terrain scenarios. Full-scale finite element analyses were performed using a commercial explicit solver, ABAQUS. The first test simulated impacting a concrete surface represented analytically by a rigid plane. Tests 2 and 3 simulated impacting a dirt surface represented analytically by an Eulerian grid of brick elements using a Mohr-Coulomb material model. The objective of this paper is to summarize the test and analysis results for the three full-scale crash tests. Simulation models of the airframe which correlate well with the tests are needed for future studies of alternate ELT mounting configurations.

Accelerating advances in continental domain hydrologic modeling

USGS Publications Warehouse

Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.

2015-01-01

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Measurement properties of a novel survey to assess stages of organizational readiness for evidence-based interventions in community chronic disease prevention settings

PubMed Central

2012-01-01

Background There is a great deal of variation in the existing capacity of primary prevention programs and policies addressing chronic disease to deliver evidence-based interventions (EBIs). In order to develop and evaluate implementation strategies that are tailored to the appropriate level of capacity, there is a need for an easy-to-administer tool to stage organizational readiness for EBIs. Methods Based on theoretical frameworks, including Rogers’ Diffusion of Innovations, we developed a survey instrument to measure four domains representing stages of readiness for EBI: awareness, adoption, implementation, and maintenance. A separate scale representing organizational climate as a potential mediator of readiness for EBIs was also included in the survey. Twenty-three questions comprised the four domains, with four to nine items each, using a seven-point response scale. Representatives from obesity, asthma, diabetes, and tobacco prevention programs serving diverse populations in the United States were surveyed (N = 243); test-retest reliability was assessed with 92 respondents. Results Confirmatory factor analysis (CFA) was used to test and refine readiness scales. Test-retest reliability of the readiness scales, as measured by intraclass correlation, ranged from 0.47–0.71. CFA found good fit for the five-item adoption and implementation scales and resulted in revisions of the awareness and maintenance scales. The awareness scale was split into two two-item scales, representing community and agency awareness. The maintenance scale was split into five- and four-item scales, representing infrastructural maintenance and evaluation maintenance, respectively. Internal reliability of scales (Cronbach’s α) ranged from 0.66–0.78. The model for the final revised scales approached good fit, with most factor loadings >0.6 and all >0.4. Conclusions The lack of adequate measurement tools hinders progress in dissemination and implementation research. These preliminary results help fill this gap by describing the reliability and measurement properties of a theory-based tool; the short, user-friendly instrument may be useful to researchers and practitioners seeking to assess organizational readiness for EBIs across a variety of chronic disease prevention programs and settings. PMID:22800294

Measurement properties of a novel survey to assess stages of organizational readiness for evidence-based interventions in community chronic disease prevention settings.

PubMed

Stamatakis, Katherine A; McQueen, Amy; Filler, Carl; Boland, Elizabeth; Dreisinger, Mariah; Brownson, Ross C; Luke, Douglas A

2012-07-16

There is a great deal of variation in the existing capacity of primary prevention programs and policies addressing chronic disease to deliver evidence-based interventions (EBIs). In order to develop and evaluate implementation strategies that are tailored to the appropriate level of capacity, there is a need for an easy-to-administer tool to stage organizational readiness for EBIs. Based on theoretical frameworks, including Rogers' Diffusion of Innovations, we developed a survey instrument to measure four domains representing stages of readiness for EBI: awareness, adoption, implementation, and maintenance. A separate scale representing organizational climate as a potential mediator of readiness for EBIs was also included in the survey. Twenty-three questions comprised the four domains, with four to nine items each, using a seven-point response scale. Representatives from obesity, asthma, diabetes, and tobacco prevention programs serving diverse populations in the United States were surveyed (N=243); test-retest reliability was assessed with 92 respondents. Confirmatory factor analysis (CFA) was used to test and refine readiness scales. Test-retest reliability of the readiness scales, as measured by intraclass correlation, ranged from 0.47-0.71. CFA found good fit for the five-item adoption and implementation scales and resulted in revisions of the awareness and maintenance scales. The awareness scale was split into two two-item scales, representing community and agency awareness. The maintenance scale was split into five- and four-item scales, representing infrastructural maintenance and evaluation maintenance, respectively. Internal reliability of scales (Cronbach's α) ranged from 0.66-0.78. The model for the final revised scales approached good fit, with most factor loadings >0.6 and all >0.4. The lack of adequate measurement tools hinders progress in dissemination and implementation research. These preliminary results help fill this gap by describing the reliability and measurement properties of a theory-based tool; the short, user-friendly instrument may be useful to researchers and practitioners seeking to assess organizational readiness for EBIs across a variety of chronic disease prevention programs and settings.

Size-density scaling in protists and the links between consumer-resource interaction parameters.

PubMed

DeLong, John P; Vasseur, David A

2012-11-01

Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

Scaling Dissolved Nutrient Removal in River Networks: A Comparative Modeling Investigation

NASA Astrophysics Data System (ADS)

Ye, Sheng; Reisinger, Alexander J.; Tank, Jennifer L.; Baker, Michelle A.; Hall, Robert O.; Rosi, Emma J.; Sivapalan, Murugesu

2017-11-01

Along the river network, water, sediment, and nutrients are transported, cycled, and altered by coupled hydrological and biogeochemical processes. Our current understanding of the rates and processes controlling the cycling and removal of dissolved inorganic nutrients in river networks is limited due to a lack of empirical measurements in large, (nonwadeable), rivers. The goal of this paper was to develop a coupled hydrological and biogeochemical process model to simulate nutrient uptake at the network scale during summer base flow conditions. The model was parameterized with literature values from headwater streams, and empirical measurements made in 15 rivers with varying hydrological, biological, and topographic characteristics, to simulate nutrient uptake at the network scale. We applied the coupled model to 15 catchments describing patterns in uptake for three different solutes to determine the role of rivers in network-scale nutrient cycling. Model simulation results, constrained by empirical data, suggested that rivers contributed proportionally more to nutrient removal than headwater streams given the fraction of their length represented in a network. In addition, variability of nutrient removal patterns among catchments was varied among solutes, and as expected, was influenced by nutrient concentration and discharge. Net ammonium uptake was not significantly correlated with any environmental descriptor. In contrast, net daily nitrate removal was linked to suspended chlorophyll a (an indicator of primary producers) and land use characteristics. Finally, suspended sediment characteristics and agricultural land use were correlated with net daily removal of soluble reactive phosphorus, likely reflecting abiotic sorption dynamics. Rivers are understudied relative to streams, and our model suggests that rivers can contribute more to network-scale nutrient removal than would be expected based upon their representative fraction of network channel length.

Photogrammetric Measurements of CEV Airbag Landing Attenuation Systems

NASA Technical Reports Server (NTRS)

Barrows, Danny A.; Burner, Alpheus W.; Berry, Felecia C.; Dismond, Harriett R.; Cate, Kenneth H.

2008-01-01

High-speed photogrammetric measurements are being used to assess the impact dynamics of the Orion Crew Exploration Vehicle (CEV) for ground landing contingency upon return to earth. Test articles representative of the Orion capsule are dropped at the NASA Langley Landing and Impact Research (LandIR) Facility onto a sand/clay mixture representative of a dry lakebed from elevations as high as 62 feet (18.9 meters). Two different types of test articles have been evaluated: (1) half-scale metal shell models utilized to establish baseline impact dynamics and soil characterization, and (2) geometric full-scale drop models with shock-absorbing airbags which are being evaluated for their ability to cushion the impact of the Orion CEV with the earth s surface. This paper describes the application of the photogrammetric measurement technique and provides drop model trajectory and impact data that indicate the performance of the photogrammetric measurement system.

Multiscale predictions of aviation-attributable PM2.5 for US ...

EPA Pesticide Factsheets

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continental (spanning hundreds of kilometers) using the Community Multiscale Air Quality-Advanced Plume Treatment (CMAQ-APT) model. In our CMAQ-APT simulations, a plume scale treatment is applied to aircraft emissions from 99 major U.S. airports over the contiguous U.S. in January and July 2005. In addition to the plume scale treatment, we account for the formation of non-traditional secondary organic aerosols (NTSOA) from the oxidation of semivolatile and intermediate volatility organic compounds (S/IVOCs) emitted from aircraft, and utilize alternative emission estimates from the Aerosol Dynamics Simulation Code (ADSC). ADSC is a 1-D plume scale model that estimates engine specific PM and S/IVOC emissions at ambient conditions, accounting for relative humidity and temperature. We estimated monthly and contiguous U.S. average aviation-attributable PM2.5 to be 2.7 ng m−3 in January and 2.6 ng m−3 in July using CMAQ-APT with ADSC emissions. This represents an increase of 40% and 12% in January and July, respectively, over impacts using traditional modeling approaches (traditional emissions without APT). The maximum fine scale (subgrid scale) hourly impacts at a major airport were 133.6 μg m−

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Multi-Scale Modeling and the Eddy-Diffusivity/Mass-Flux (EDMF) Parameterization

NASA Astrophysics Data System (ADS)

Teixeira, J.

2015-12-01

Turbulence and convection play a fundamental role in many key weather and climate science topics. Unfortunately, current atmospheric models cannot explicitly resolve most turbulent and convective flow. Because of this fact, turbulence and convection in the atmosphere has to be parameterized - i.e. equations describing the dynamical evolution of the statistical properties of turbulence and convection motions have to be devised. Recently a variety of different models have been developed that attempt at simulating the atmosphere using variable resolution. A key problem however is that parameterizations are in general not explicitly aware of the resolution - the scale awareness problem. In this context, we will present and discuss a specific approach, the Eddy-Diffusivity/Mass-Flux (EDMF) parameterization, that not only is in itself a multi-scale parameterization but it is also particularly well suited to deal with the scale-awareness problems that plague current variable-resolution models. It does so by representing small-scale turbulence using a classic Eddy-Diffusivity (ED) method, and the larger-scale (boundary layer and tropospheric-scale) eddies as a variety of plumes using the Mass-Flux (MF) concept.

Development and Validation of the Body Size Scale for Assessing Body Weight Perception in African Populations

PubMed Central

Cohen, Emmanuel; Bernard, Jonathan Y.; Ponty, Amandine; Ndao, Amadou; Amougou, Norbert; Saïd-Mohamed, Rihlat; Pasquet, Patrick

2015-01-01

Background The social valorisation of overweight in African populations could promote high-risk eating behaviours and therefore become a risk factor of obesity. However, existing scales to assess body image are usually not accurate enough to allow comparative studies of body weight perception in different African populations. This study aimed to develop and validate the Body Size Scale (BSS) to estimate African body weight perception. Methods Anthropometric measures of 80 Cameroonians and 81 Senegalese were used to evaluate three criteria of adiposity: body mass index (BMI), overall percentage of fat, and endomorphy (fat component of the somatotype). To develop the BSS, the participants were photographed in full face and profile positions. Models were selected for their representativeness of the wide variability in adiposity with a progressive increase along the scale. Then, for the validation protocol, participants self-administered the BSS to assess self-perceived current body size (CBS), desired body size (DBS) and provide a “body self-satisfaction index.” This protocol included construct validity, test-retest reliability and convergent validity and was carried out with three independent samples of respectively 201, 103 and 1115 Cameroonians. Results The BSS comprises two sex-specific scales of photos of 9 models each, and ordered by increasing adiposity. Most participants were able to correctly order the BSS by increasing adiposity, using three different words to define body size. Test-retest reliability was consistent in estimating CBS, DBS and the “body self-satisfaction index.” The CBS was highly correlated to the objective BMI, and two different indexes assessed with the BSS were consistent with declarations obtained in interviews. Conclusion The BSS is the first scale with photos of real African models taken in both full face and profile and representing a wide and representative variability in adiposity. The validation protocol proved its reliability for estimating body weight perception in Africans. PMID:26536030

Recent advances towards a theory of catchment hydrologic transport: age-ranked storage and the Ω-functions

NASA Astrophysics Data System (ADS)

Harman, C. J.

2014-12-01

Models that faithfully represent spatially-integrated hydrologic transport through the critical zone at sub-watershed scales are essential building blocks for large-scale models of land use and climate controls on non-point source contaminant delivery. A particular challenge facing these models is the need to represent the delay between inputs of soluble contaminants (such as nitrate) at the field scale, and the solute load that appears in streams. Recent advances in the theory of time-variable transit time distributions (e.g. Botter et al., GRL 38(L11403), 2011) have provided a rigorous framework for representing conservative solute transport and its coupling to hydrologic variability and partitioning. Here I will present a reformulation of this framework that offers several distinct advantages over existing formulations: 1) the derivation of the governing conservation equation is simple and intuitive, 2) the closure relations are expressed in a convenient and physically meaningful way as probability distributions Ω(ST)Omega(S_T) over the storage ranked by age STS_T, and 3) changes in transport behavior determined by storage-dependent dilution and flow-path dynamics (as distinct from those due only to changes in the rates and partitioning of water flux) are completely encapsulated by these probability distributions. The framework has been implemented to model to the rich dataset of long-term stream and precipitation chloride from the Plynlimon watershed in Wales, UK. With suitable choices for the functional form of the closure relationships, only a small number of free parameters are required to reproduce the observed chloride dynamics as well as previous models with many more parameters, including reproducing the observed fractal 1/f filtering of the streamflow chloride variability. The modeled transport dynamics are sensitive to the input precipitation variability and water balance partitioning to evapotranspiration. Apparent storage-dependent age-sampling suggests that the model can account for shifts in flow pathways across high and low flows. This approach suggests a path forward for catchment-scale coupled flow and transport modeling.

Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data

USDA-ARS?s Scientific Manuscript database

The rapid evolution of high performance computing technology has allowed for the development of extremely detailed models of the urban and natural environment. Although models can now represent sub-meter-scale variability in environmental geometry, model users are often unable to specify the geometr...

Exploring the relevance of spatial scale to life cycle inventory results using environmentally-extended input-output models of the United States

EPA Science Inventory

The accuracy of direct and indirect resource use and emissions of products as quantified in life cycle models depends in part upon the geographical and technological representativeness of the production models. Production conditions vary not just between nations, but also within ...

Development of fine-resolution analyses and expanded large-scale forcing properties. Part II: Scale-awareness and application to single-column model experiments

DOE PAGES

Feng, Sha; Vogelmann, Andrew M.; Li, Zhijin; ...

2015-01-20

Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scalesmore » larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.« less

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine-scale processes. This assessment is also relevant for addressing the scale limitation of current RCMs or VRGCMs when next-generation model resolution increases to ~10km and beyond.

Multiscale Granger causality

NASA Astrophysics Data System (ADS)

Faes, Luca; Nollo, Giandomenico; Stramaglia, Sebastiano; Marinazzo, Daniele

2017-10-01

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer across multiple time scales. We show that the multiscale processing of a vector autoregressive (AR) process introduces a moving average (MA) component, and describe how to represent the resulting ARMA process using state space (SS) models and to combine the SS model parameters for computing exact GC values at arbitrarily large time scales. We exploit the theoretical formulation to identify peculiar features of multiscale GC in basic AR processes, and demonstrate with numerical simulations the much larger estimation accuracy of the SS approach compared to pure AR modeling of filtered and downsampled data. The improved computational reliability is exploited to disclose meaningful multiscale patterns of information transfer between global temperature and carbon dioxide concentration time series, both in paleoclimate and in recent years.

Hydrological and geomorphological controls of malaria transmission

NASA Astrophysics Data System (ADS)

Smith, M. W.; Macklin, M. G.; Thomas, C. J.

2013-01-01

Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.

Methane emissions from floodplains in the Amazon Basin: towards a process-based model for global applications

NASA Astrophysics Data System (ADS)

Ringeval, B.; Houweling, S.; van Bodegom, P. M.; Spahni, R.; van Beek, R.; Joos, F.; Röckmann, T.

2013-10-01

Tropical wetlands are estimated to represent about 50% of the natural wetland emissions and explain a large fraction of the observed CH4 variability on time scales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This study documents the first regional-scale, process-based model of CH4 emissions from tropical floodplains. The LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially-explicit hydrology model PCR-GLOBWB. We introduced new Plant Functional Types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote sensing datasets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX simulated CH4 flux densities are in reasonable agreement with observations at the field scale but with a~tendency to overestimate the flux observed at specific sites. In addition, the model did not reproduce between-site variations or between-year variations within a site. Unfortunately, site informations are too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr-1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin modulated emissions by about 20%. Correcting the LPX simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the seasonality in CH4 emissions. The Inter Annual Variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is account for, but still remains lower than in most of WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results stress the need for more research to constrain floodplain CH4 emissions and their temporal variability.

Fuzzy object modeling

NASA Astrophysics Data System (ADS)

Udupa, Jayaram K.; Odhner, Dewey; Falcao, Alexandre X.; Ciesielski, Krzysztof C.; Miranda, Paulo A. V.; Vaideeswaran, Pavithra; Mishra, Shipra; Grevera, George J.; Saboury, Babak; Torigian, Drew A.

2011-03-01

To make Quantitative Radiology (QR) a reality in routine clinical practice, computerized automatic anatomy recognition (AAR) becomes essential. As part of this larger goal, we present in this paper a novel fuzzy strategy for building bodywide group-wise anatomic models. They have the potential to handle uncertainties and variability in anatomy naturally and to be integrated with the fuzzy connectedness framework for image segmentation. Our approach is to build a family of models, called the Virtual Quantitative Human, representing normal adult subjects at a chosen resolution of the population variables (gender, age). Models are represented hierarchically, the descendents representing organs contained in parent organs. Based on an index of fuzziness of the models, 32 thorax data sets, and 10 organs defined in them, we found that the hierarchical approach to modeling can effectively handle the non-linear relationships in position, scale, and orientation that exist among organs in different patients.

Weighted Scaling in Non-growth Random Networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li

2012-09-01

We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in non-growth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its total number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scale-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

Multivariate Spatio-Temporal Clustering: A Framework for Integrating Disparate Data to Understand Network Representativeness and Scaling Up Sparse Ecosystem Measurements

NASA Astrophysics Data System (ADS)

Hoffman, F. M.; Kumar, J.; Maddalena, D. M.; Langford, Z.; Hargrove, W. W.

2014-12-01

Disparate in situ and remote sensing time series data are being collected to understand the structure and function of ecosystems and how they may be affected by climate change. However, resource and logistical constraints limit the frequency and extent of observations, particularly in the harsh environments of the arctic and the tropics, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent variability at desired scales. These regions host large areas of potentially vulnerable ecosystems that are poorly represented in Earth system models (ESMs), motivating two new field campaigns, called Next Generation Ecosystem Experiments (NGEE) for the Arctic and Tropics, funded by the U.S. Department of Energy. Multivariate Spatio-Temporal Clustering (MSTC) provides a quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks. We applied MSTC to down-scaled general circulation model results and data for the State of Alaska at a 4 km2 resolution to define maps of ecoregions for the present (2000-2009) and future (2090-2099), showing how combinations of 37 bioclimatic characteristics are distributed and how they may shift in the future. Optimal representative sampling locations were identified on present and future ecoregion maps, and representativeness maps for candidate sampling locations were produced. We also applied MSTC to remotely sensed LiDAR measurements and multi-spectral imagery from the WorldView-2 satellite at a resolution of about 5 m2 within the Barrow Environmental Observatory (BEO) in Alaska. At this resolution, polygonal ground features—such as centers, edges, rims, and troughs—can be distinguished. Using these remote sensing data, we up-scaled vegetation distribution data collected on these polygonal ground features to a large area of the BEO to provide distributions of plant functional types that can be used to parameterize ESMs. In addition, we applied MSTC to 4 km2 global bioclimate data to define global ecoregions and understand the representativeness of CTFS-ForestGEO, Fluxnet, and RAINFOR sampling networks. These maps identify tropical forests underrepresented in existing observations of individual and combined networks.

Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces

PubMed Central

Kim, Minsu; Or, Dani

2016-01-01

Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

NASA Astrophysics Data System (ADS)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE ‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE ‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal snowpack energetics over the distributions) was found to yield similar SCD and discharge results as simulations that resolved internal energy differences. Spatial/internal snowpack melt energy effects are more pronounced at times earlier in spring before the main period of snowmelt and SCD, as shown in previously published work. The paper discusses the importance of these findings as they apply to the warranted complexity of snowmelt process simulation in cold mountain environments, and shows how the end-of-winter SWE distribution represents an effective means of resolving snow cover heterogeneity at multiple scales for modelling, even in steep and complex terrain.

A case study of field-scale maize irrigation patterns in western Nebraska: implications for water managers and recommendations for hyper-resolution land surface modeling

NASA Astrophysics Data System (ADS)

Gibson, Justin; Franz, Trenton E.; Wang, Tiejun; Gates, John; Grassini, Patricio; Yang, Haishun; Eisenhauer, Dean

2017-02-01

In many agricultural regions, the human use of water for irrigation is often ignored or poorly represented in land surface models (LSMs) and operational forecasts. Because irrigation increases soil moisture, feedback on the surface energy balance, rainfall recycling, and atmospheric dynamics is not represented and may lead to reduced model skill. In this work, we describe four plausible and relatively simple irrigation routines that can be coupled to the next generation of hyper-resolution LSMs operating at scales of 1 km or less. The irrigation output from the four routines (crop model, precipitation delayed, evapotranspiration replacement, and vadose zone model) is compared against a historical field-scale irrigation database (2008-2014) from a 35 km2 study area under maize production and center pivot irrigation in western Nebraska (USA). We find that the most yield-conservative irrigation routine (crop model) produces seasonal totals of irrigation that compare well against the observed irrigation amounts across a range of wet and dry years but with a low bias of 80 mm yr-1. The most aggressive irrigation saving routine (vadose zone model) indicates a potential irrigation savings of 120 mm yr-1 and yield losses of less than 3 % against the crop model benchmark and historical averages. The results of the various irrigation routines and associated yield penalties will be valuable for future consideration by local water managers to be informed about the potential value of irrigation saving technologies and irrigation practices. Moreover, the routines offer the hyper-resolution LSM community a range of irrigation routines to better constrain irrigation decision-making at critical temporal (daily) and spatial scales (< 1 km).

A novel scale for measuring mixed states in bipolar disorder.

PubMed

Cavanagh, Jonathan; Schwannauer, Matthias; Power, Mick; Goodwin, Guy M

2009-01-01

Conventional descriptions of bipolar disorder tend to treat the mixed state as something of an afterthought. There is no scale that specifically measures the phenomena of the mixed state. This study aimed to test a novel scale for mixed state in a clinical and community population of bipolar patients. The scale included clinically relevant symptoms of both mania and depression in a bivariate scale. Recovered respondents were asked to recall their last manic episode. The scale allowed endorsement of one or more of the manic and depressive symptoms. Internal consistency analyses were carried out using Cronbach alpha. Factor analysis was carried out using a standard Principal Components Analysis followed by Varimax Rotation. A confirmatory factor analytic method was used to validate the scale structure in a representative clinical sample. The reliability analysis gave a Cronbach alpha value of 0.950, with a range of corrected-item-total-scale correlations from 0.546 (weight change) to 0.830 (mood). The factor analysis revealed a two-factor solution for the manic and depressed items which accounted for 61.2% of the variance in the data. Factor 1 represented physical activity, verbal activity, thought processes and mood. Factor 2 represented eating habits, weight change, passage of time and pain sensitivity. This novel scale appears to capture the key features of mixed states. The two-factor solution fits well with previous models of bipolar disorder and concurs with the view that mixed states may be more than the sum of their parts.

Category Rating Is Based on Prototypes and Not Instances: Evidence from Feedback-Dependent Context Effects

ERIC Educational Resources Information Center

Petrov, Alexander A.

2011-01-01

Context effects in category rating on a 7-point scale are shown to reverse direction depending on feedback. Context (skewed stimulus frequencies) was manipulated between and feedback within subjects in two experiments. The diverging predictions of prototype- and exemplar-based scaling theories were tested using two representative models: ANCHOR…

Water Awareness Scale for Pre-Service Science Teachers: Validity and Reliability Study

ERIC Educational Resources Information Center

Filik Iscen, Cansu

2015-01-01

The role of teachers in the formation of environmentally sensitive behaviors in students is quite high. Thus, the water awareness of teachers, who represent role models for students, is rather important. The main purpose of this study is to identify the reliability and validity study outcomes of the Water Awareness Scale, which was developed to…

Changes in photosynthesis and soil moisture drive the seasonal soil respiration-temperature hysteresis relationship

USDA-ARS?s Scientific Manuscript database

In nearly all large-scale models, CO2 efflux from soil (i.e., soil respiration) is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable at the local scale, and there is often a pronounced hysteresis in the soil resp...

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE PAGES

Baker, I. T.; Sellers, P. J.; Denning, A. S.; ...

2017-03-01

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, I. T.; Sellers, P. J.; Denning, A. S.

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

Applying Hillslope Hydrology to Bridge between Ecosystem and Grid-Scale Processes within an Earth System Model

NASA Astrophysics Data System (ADS)

Subin, Z. M.; Sulman, B. N.; Malyshev, S.; Shevliakova, E.

2013-12-01

Soil moisture is a crucial control on surface energy fluxes, vegetation properties, and soil carbon cycling. Its interactions with ecosystem processes are highly nonlinear across a large range, as both drought stress and anoxia can impede vegetation and microbial growth. Earth System Models (ESMs) generally only represent an average soil-moisture state in grid cells at scales of 50-200 km, and as a result are not able to adequately represent the effects of subgrid heterogeneity in soil moisture, especially in regions with large wetland areas. We addressed this deficiency by developing the first ESM-coupled subgrid hillslope-hydrological model, TiHy (Tiled-hillslope Hydrology), embedded within the Geophysical Fluid Dynamics Laboratory (GFDL) land model. In each grid cell, one or more representative hillslope geometries are discretized into land model tiles along an upland-to-lowland gradient. These geometries represent ~1 km hillslope-scale hydrological features and allow for flexible representation of hillslope profile and plan shapes, in addition to variation of subsurface properties among or within hillslopes. Each tile (which may represent ~100 m along the hillslope) has its own surface fluxes, vegetation state, and vertically-resolved state variables for soil physics and biogeochemistry. Resolution of water state in deep layers (~200 m) down to bedrock allows for physical integration of groundwater transport with unsaturated overlying dynamics. Multiple tiles can also co-exist at the same vertical position along the hillslope, allowing the simulation of ecosystem heterogeneity due to disturbance. The hydrological model is coupled to the vertically-resolved Carbon, Organisms, Respiration, and Protection in the Soil Environment (CORPSE) model, which captures non-linearity resulting from interactions between vertically-heterogeneous soil carbon and water profiles. We present comparisons of simulated water table depth to observations. We examine sensitivities to alternative parameterizations of hillslope geometry, macroporosity, and surface runoff / inundation, and to the choice of global topographic dataset and groundwater hydraulic conductivity distribution. Simulated groundwater dynamics among hillslopes tend to cluster into three regimes of wet and well-drained, wet but poorly-drained, and dry. In the base model configuration, near-surface gridcell-mean water tables exist in an excessively large area compared to observations, including large areas of the Eastern U.S. and Northern Europe. However, in better-drained areas, the decrease in water table depth along the hillslope gradient allows for realistic increases in ecosystem water availability and soil carbon downslope. The inclusion of subgrid hydrology can increase the equilibrium 0-2 m global soil carbon stock by a large factor, due to the nonlinear effect of anoxia. We conclude that this innovative modeling framework allows for the inclusion of hillslope-scale processes and the potential for wetland dynamics in an ESM without need for a high-resolution 3-dimensional groundwater model. Future work will include investigating the potential for future changes in land carbon fluxes caused by the effects of changing hydrological regime, particularly in peatland-rich areas poorly treated by current ESMs.

Predicting monthly precipitation along coastal Ecuador: ENSO and transfer function models

NASA Astrophysics Data System (ADS)

de Guenni, Lelys B.; García, Mariangel; Muñoz, Ángel G.; Santos, José L.; Cedeño, Alexandra; Perugachi, Carlos; Castillo, José

2017-08-01

It is well known that El Niño-Southern Oscillation (ENSO) modifies precipitation patterns in several parts of the world. One of the most impacted areas is the western coast of South America, where Ecuador is located. El Niño events that occurred in 1982-1983, 1987-1988, 1991-1992, and 1997-1998 produced important positive rainfall anomalies in the coastal zone of Ecuador, bringing considerable damage to livelihoods, agriculture, and infrastructure. Operational climate forecasts in the region provide only seasonal scale (e.g., 3-month averages) information, but during ENSO events it is key for decision-makers to use reliable sub-seasonal scale forecasts, which at the present time are still non-existent in most parts of the world. This study analyzes the potential predictability of coastal Ecuador rainfall at monthly scale. Instead of the discrete approach that considers training models using only particular seasons, continuous (i.e., all available months are used) transfer function models are built using standard ENSO indices to explore rainfall forecast skill along the Ecuadorian coast and Galápagos Islands. The modeling approach considers a large-scale contribution, represented by the role of a sea-surface temperature index, and a local-scale contribution represented here via the use of previous precipitation observed in the same station. The study found that the Niño3 index is the best ENSO predictor of monthly coastal rainfall, with a lagged response varying from 0 months (simultaneous) for Galápagos up to 3 months for the continental locations considered. Model validation indicates that the skill is similar to the one obtained using principal component regression models for the same kind of experiments. It is suggested that the proposed approach could provide skillful rainfall forecasts at monthly scale for up to a few months in advance.

Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset

NASA Astrophysics Data System (ADS)

Smith, A.; Neal, J. C.; Bates, P. D.; Quinn, N.; Wing, O.

2017-12-01

Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.

The Importance of Explicitly Representing Soil Carbon with Depth over the Permafrost Region in Earth System Models: Implications for Atmospheric Carbon Dynamics at Multiple Temporal Scales between 1960 and 2300.

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2014-12-01

We conducted an assessment of changes in permafrost area and carbon storage simulated by process-based models between 1960 and 2300. The models participating in this comparison were those that had joined the model integration team of the Vulnerability of Permafrost Carbon Research Coordination Network (see http://www.biology.ufl.edu/permafrostcarbon/). Each of the models in this comparison conducted simulations over the permafrost land region in the Northern Hemisphere driven by CCSM4-simulated climate for RCP 4.5 and 8.5 scenarios. Among the models, the area of permafrost (defined as the area for which active layer thickness was less than 3 m) ranged between 13.2 and 20.0 million km2. Between 1960 and 2300, models indicated the loss of permafrost area between 5.1 to 6.0 million km2 for RCP 4.5 and between 7.1 and 15.2 million km2 for RCP 8.5. Among the models, the density of soil carbon storage in 1960 ranged between 13 and 42 thousand g C m-2; models that explicitly represented carbon with depth had estimates greater than 27 thousand g C m-2. For the RCP 4.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 32 Pg C to gains of 58 Pg C, in which models that explicitly represent soil carbon with depth simulated losses or lower gains of soil carbon in comparison with those that did not. For the RCP 8.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 642 Pg C to gains of 66 Pg C, in which those models that represent soil carbon explicitly with depth all simulated losses, while those that do not all simulated gains. These results indicate that there are substantial differences in responses of carbon dynamics between model that do and do not explicitly represent soil carbon with depth in the permafrost region. We present analyses of the implications of the differences for atmospheric carbon dynamics at multiple temporal scales between 1960 and 2300.

Multiscale Cloud System Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell W.

2009-01-01

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

NASA Technical Reports Server (NTRS)

Kassemi, Mohammad; Kartuzova, Olga; Hylton, Sonya

2015-01-01

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

Using a Freshwater Lake Model Coupled with WRF for Dynamical Downscaling Applications

EPA Science Inventory

The ability to represent extremes in temperature and precipitation in regional climates (including those affected by inland lakes) has become an area of focus as regional climate models (RCMs) simulate smaller temporal and spatial scales. When using the Weather Research and Fore...

MULTIMEDIA INTEGRATED MODELING FOR ENVIRONMENTAL PROTECTION: INTRODUCTION TO A COLLABORATIVE FRAMEWORK

EPA Science Inventory

The EPA's Office of Research and Development is embarking on a long term project to develop a Multimedia Integrated Modeling System (MIMS). The system will have capabilities to represent the transport and fate of nutrients and chemical stressors over multiple scales. MIMS will ...

Achieving a Successful Scale-Down Model and Optimized Economics through Parvovirus Filter Validation using Purified TrueSpikeTM Viruses.

PubMed

De Vilmorin, Philippe; Slocum, Ashley; Jaber, Tareq; Schaefer, Oliver; Ruppach, Horst; Genest, Paul

2015-01-01

This article describes a four virus panel validation of EMD Millipore's (Bedford, MA) small virus-retentive filter, Viresolve® Pro, using TrueSpike(TM) viruses for a Biogen Idec process intermediate. The study was performed at Charles River Labs in King of Prussia, PA. Greater than 900 L/m(2) filter throughput was achieved with the approximately 8 g/L monoclonal antibody feed. No viruses were detected in any filtrate samples. All virus log reduction values were between ≥3.66 and ≥5.60. The use of TrueSpike(TM) at Charles River Labs allowed Biogen Idec to achieve a more representative scaled-down model and potentially reduce the cost of its virus filtration step and the overall cost of goods. The body of data presented here is an example of the benefits of following the guidance from the PDA Technical Report 47, The Preparation of Virus Spikes Used for Viral Clearance Studies. The safety of biopharmaceuticals is assured through the use of multiple steps in the purification process that are capable of virus clearance, including filtration with virus-retentive filters. The amount of virus present at the downstream stages in the process is expected to be and is typically low. The viral clearance capability of the filtration step is assessed in a validation study. The study utilizes a small version of the larger manufacturing size filter, and a large, known amount of virus is added to the feed prior to filtration. Viral assay before and after filtration allows the virus log reduction value to be quantified. The representativeness of the small-scale model is supported by comparing large-scale filter performance to small-scale filter performance. The large-scale and small-scale filtration runs are performed using the same operating conditions. If the filter performance at both scales is comparable, it supports the applicability of the virus log reduction value obtained with the small-scale filter to the large-scale manufacturing process. However, the virus preparation used to spike the feed material often contains impurities that contribute adversely to virus filter performance in the small-scale model. The added impurities from the virus spike, which are not present at manufacturing scale, compromise the scale-down model and put into question the direct applicability of the virus clearance results. Another consequence of decreased filter performance due to virus spike impurities is the unnecessary over-sizing of the manufacturing system to match the low filter capacity observed in the scale-down model. This article describes how improvements in mammalian virus spike purity ensure the validity of the log reduction value obtained with the scale-down model and support economically optimized filter usage. © PDA, Inc. 2015.

Using lumped modelling for providing simple metrics and associated uncertainties of catchment response to agricultural-derived nitrates pollutions

NASA Astrophysics Data System (ADS)

RUIZ, L.; Fovet, O.; Faucheux, M.; Molenat, J.; Sekhar, M.; Aquilina, L.; Gascuel-odoux, C.

2013-12-01

The development of simple and easily accessible metrics is required for characterizing and comparing catchment response to external forcings (climate or anthropogenic) and for managing water resources. The hydrological and geochemical signatures in the stream represent the integration of the various processes controlling this response. The complexity of these signatures over several time scales from sub-daily to several decades [Kirchner et al., 2001] makes their deconvolution very difficult. A large range of modeling approaches intent to represent this complexity by accounting for the spatial and/or temporal variability of the processes involved. However, simple metrics are not easily retrieved from these approaches, mostly because of over-parametrization issues. We hypothesize that to obtain relevant metrics, we need to use models that are able to simulate the observed variability of river signatures at different time scales, while being as parsimonious as possible. The lumped model ETNA (modified from[Ruiz et al., 2002]) is able to simulate adequately the seasonal and inter-annual patterns of stream NO3 concentration. Shallow groundwater is represented by two linear stores with double porosity and riparian processes are represented by a constant nitrogen removal function. Our objective was to identify simple metrics of catchment response by calibrating this lumped model on two paired agricultural catchments where both N inputs and outputs were monitored for a period of 20 years. These catchments, belonging to ORE AgrHys, although underlain by the same granitic bedrock are displaying contrasted chemical signatures. The model was able to simulate the two contrasted observed patterns in stream and groundwater, both on hydrology and chemistry, and at the seasonal and pluri-annual scales. It was also compatible with the expected trends of nitrate concentration since 1960. The output variables of the model were used to compute the nitrate residence time in both the catchments. We used the Global Likelihood Uncertainty Estimations (GLUE) approach [Beven and Binley, 1992] to assess the parameter uncertainties and the subsequent error in model outputs and residence times. Reasonably low parameter uncertainties were obtained by calibrating simultaneously the two paired catchments with two outlets time series of stream flow and nitrate concentrations. Finally, only one parameter controlled the contrast in nitrogen residence times between the catchments. Therefore, this approach provided a promising metric for classifying the variability of catchment response to agricultural nitrogen inputs. Beven, K., and A. Binley (1992), THE FUTURE OF DISTRIBUTED MODELS - MODEL CALIBRATION AND UNCERTAINTY PREDICTION, Hydrological Processes, 6(3), 279-298. Kirchner, J. W., X. Feng, and C. Neal (2001), Catchment-scale advection and dispersion as a mechanism for fractal scaling in stream tracer concentrations, Journal of Hydrology, 254(1-4), 82-101. Ruiz, L., S. Abiven, C. Martin, P. Durand, V. Beaujouan, and J. Molenat (2002), Effect on nitrate concentration in stream water of agricultural practices in small catchments in Brittany : II. Temporal variations and mixing processes, Hydrology and Earth System Sciences, 6(3), 507-513.

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

ERIC Educational Resources Information Center

Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.

2009-01-01

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

Measurement and modeling of unsaturated hydraulic conductivity: Chapter 21

USGS Publications Warehouse

Perkins, Kim S.; Elango, Lakshmanan

2011-01-01

This chapter will discuss, by way of examples, various techniques used to measure and model hydraulic conductivity as a function of water content, K(). The parameters that describe the K() curve obtained by different methods are used directly in Richards’ equation-based numerical models, which have some degree of sensitivity to those parameters. This chapter will explore the complications of using laboratory measured or estimated properties for field scale investigations to shed light on how adequately the processes are represented. Additionally, some more recent concepts for representing unsaturated-zone flow processes will be discussed.

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

Core analysis of heterogeneous rocks using experimental observations and digital whole core simulation

NASA Astrophysics Data System (ADS)

Jackson, S. J.; Krevor, S. C.; Agada, S.

2017-12-01

A number of studies have demonstrated the prevalent impact that small-scale rock heterogeneity can have on larger scale flow in multiphase flow systems including petroleum production and CO2sequestration. Larger scale modeling has shown that this has a significant impact on fluid flow and is possibly a significant source of inaccuracy in reservoir simulation. Yet no core analysis protocol has been developed that faithfully represents the impact of these heterogeneities on flow functions used in modeling. Relative permeability is derived from core floods performed at conditions with high flow potential in which the impact of capillary heterogeneity is voided. A more accurate representation would be obtained if measurements were made at flow conditions where the impact of capillary heterogeneity on flow is scaled to be representative of the reservoir system. This, however, is generally impractical due to laboratory constraints and the role of the orientation of the rock heterogeneity. We demonstrate a workflow of combined observations and simulations, in which the impact of capillary heterogeneity may be faithfully represented in the derivation of upscaled flow properties. Laboratory measurements that are a variation of conventional protocols are used for the parameterization of an accurate digital rock model for simulation. The relative permeability at the range of capillary numbers relevant to flow in the reservoir is derived primarily from numerical simulations of core floods that include capillary pressure heterogeneity. This allows flexibility in the orientation of the heterogeneity and in the range of flow rates considered. We demonstrate the approach in which digital rock models have been developed alongside core flood observations for three applications: (1) A Bentheimer sandstone with a simple axial heterogeneity to demonstrate the validity and limitations of the approach, (2) a set of reservoir rocks from the Captain sandstone in the UK North Sea targeted for CO2 storage, and for which the use of capillary pressure hysteresis is necessary, and (3) a secondary CO2-EOR production of residual oil from a Berea sandstone with layered heterogeneities. In all cases the incorporation of heterogeneity is shown to be key to the ultimate derivation of flow properties representative of the reservoir system.

Developing and exploring a theory for the lateral erosion of bedrock channels for use in landscape evolution models

NASA Astrophysics Data System (ADS)

Langston, Abigail L.; Tucker, Gregory E.

2018-01-01

Understanding how a bedrock river erodes its banks laterally is a frontier in geomorphology. Theories for the vertical incision of bedrock channels are widely implemented in the current generation of landscape evolution models. However, in general existing models do not seek to implement the lateral migration of bedrock channel walls. This is problematic, as modeling geomorphic processes such as terrace formation and hillslope-channel coupling depends on the accurate simulation of valley widening. We have developed and implemented a theory for the lateral migration of bedrock channel walls in a catchment-scale landscape evolution model. Two model formulations are presented, one representing the slow process of widening a bedrock canyon and the other representing undercutting, slumping, and rapid downstream sediment transport that occurs in softer bedrock. Model experiments were run with a range of values for bedrock erodibility and tendency towards transport- or detachment-limited behavior and varying magnitudes of sediment flux and water discharge in order to determine the role that each plays in the development of wide bedrock valleys. The results show that this simple, physics-based theory for the lateral erosion of bedrock channels produces bedrock valleys that are many times wider than the grid discretization scale. This theory for the lateral erosion of bedrock channel walls and the numerical implementation of the theory in a catchment-scale landscape evolution model is a significant first step towards understanding the factors that control the rates and spatial extent of wide bedrock valleys.

No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.

Evaluating CONUS-Scale Runoff Simulation across the National Water Model WRF-Hydro Implementation to Disentangle Regional Controls on Streamflow Generation and Model Error Contribution

NASA Astrophysics Data System (ADS)

Dugger, A. L.; Rafieeinasab, A.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L. R.; Pan, L.; Zhang, Y.; Sampson, K. M.; Cosgrove, B.

2016-12-01

Evaluation of physically-based hydrologic models applied across large regions can provide insight into dominant controls on runoff generation and how these controls vary based on climatic, biological, and geophysical setting. To make this leap, however, we need to combine knowledge of regional forcing skill, model parameter and physics assumptions, and hydrologic theory. If we can successfully do this, we also gain information on how well our current approximations of these dominant physical processes are represented in continental-scale models. In this study, we apply this diagnostic approach to a 5-year retrospective implementation of the WRF-Hydro community model configured for the U.S. National Weather Service's National Water Model (NWM). The NWM is a water prediction model in operations over the contiguous U.S. as of summer 2016, providing real-time estimates and forecasts out to 30 days of streamflow across 2.7 million stream reaches as well as distributed snowpack, soil moisture, and evapotranspiration at 1-km resolution. The WRF-Hydro system permits not only the standard simulation of vertical energy and water fluxes common in continental-scale models, but augments these processes with lateral redistribution of surface and subsurface water, simple groundwater dynamics, and channel routing. We evaluate 5 years of NLDAS-2 precipitation forcing and WRF-Hydro streamflow and evapotranspiration simulation across the contiguous U.S. at a range of spatial (gage, basin, ecoregion) and temporal (hourly, daily, monthly) scales and look for consistencies and inconsistencies in performance in terms of bias, timing, and extremes. Leveraging results from other CONUS-scale hydrologic evaluation studies, we translate our performance metrics into a matrix of likely dominant process controls and error sources (forcings, parameter estimates, and model physics). We test our hypotheses in a series of controlled model experiments on a subset of representative basins from distinct "problem" environments (Southeast U.S. Coastal Plain, Central and Coastal Texas, Northern Plains, and Arid Southwest). The results from these longer-term model diagnostics will inform future improvements in forcing bias correction, parameter calibration, and physics developments in the National Water Model.

Conceptual modelling of E. coli in urban stormwater drains, creeks and rivers

NASA Astrophysics Data System (ADS)

Jovanovic, Dusan; Hathaway, Jon; Coleman, Rhys; Deletic, Ana; McCarthy, David T.

2017-12-01

Accurate estimation of faecal microorganism levels in water systems, such as stormwater drains, creeks and rivers, is needed for appropriate assessment of impacts on receiving water bodies and the risks to human health. The underlying hypothesis for this work is that a single conceptual model (the MicroOrganism Prediction in Urban Stormwater model - i.e. MOPUS) can adequately simulate microbial dynamics over a variety of water systems and wide range of scales; something which has not been previously tested. Additionally, the application of radar precipitation data for improvement of the model performance at these scales via more accurate areal averaged rainfall intensities was tested. Six comprehensive Escherichia coli (E. coli) datasets collected from five catchments in south-eastern Australia and one catchment in Raleigh, USA, were used to calibrate the model. The MOPUS rainfall-runoff model performed well at all scales (Nash-Sutcliffe E for instantaneous flow rates between 0.70 and 0.93). Sensitivity analysis showed that wet weather urban stormwater flows can be modelled with only three of the five rainfall runoff model parameters: routing coefficient (K), effective imperviousness (IMP) and time of concentration (TOC). The model's performance for representing instantaneous E. coli fluctuations ranged from 0.17 to 0.45 in catchments drained via pipe or open creek, and was the highest for a large riverine catchment (0.64); performing similarly, if not better, than other microbial models in literature. The model could also capture the variability in event mean concentrations (E = 0.17-0.57) and event loads (E = 0.32-0.97) at all scales. Application of weather radar-derived rainfall inputs caused lower overall performance compared to using gauged rainfall inputs in representing both flow and E. coli levels in urban drain catchments, with the performance improving with increasing catchment size and being comparable to the models that use gauged rainfall inputs at the large riverine catchment. These results demonstrate the potential of the MOPUS model and its ability to be applied to a wide range of catchment scales, including large riverine systems.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Accuracy of methods for calculating volumetric wear from coordinate measuring machine data of retrieved metal-on-metal hip joint implants.

PubMed

Lu, Zhen; McKellop, Harry A

2014-03-01

This study compared the accuracy and sensitivity of several numerical methods employing spherical or plane triangles for calculating the volumetric wear of retrieved metal-on-metal hip joint implants from coordinate measuring machine measurements. Five methods, one using spherical triangles and four using plane triangles to represent the bearing and the best-fit surfaces, were assessed and compared on a perfect hemisphere model and a hemi-ellipsoid model (i.e. unworn models), computer-generated wear models and wear-tested femoral balls, with point spacings of 0.5, 1, 2 and 3 mm. The results showed that the algorithm (Method 1) employing spherical triangles to represent the bearing surface and to scale the mesh to the best-fit surfaces produced adequate accuracy for the wear volume with point spacings of 0.5, 1, 2 and 3 mm. The algorithms (Methods 2-4) using plane triangles to represent the bearing surface and to scale the mesh to the best-fit surface also produced accuracies that were comparable to that with spherical triangles. In contrast, if the bearing surface was represented with a mesh of plane triangles and the best-fit surface was taken as a smooth surface without discretization (Method 5), the algorithm produced much lower accuracy with a point spacing of 0.5 mm than Methods 1-4 with a point spacing of 3 mm.

Confirmatory factor analysis of the PTSD Checklist and the Clinician-Administered PTSD Scale in disaster workers exposed to the World Trade Center Ground Zero.

PubMed

Palmieri, Patrick A; Weathers, Frank W; Difede, JoAnn; King, Dainel W

2007-05-01

Although posttraumatic stress disorder (PTSD) factor analytic research has yielded little support for the DSM-IV 3-factor model of reexperiencing, avoidance, and hyperarousal symptoms, no clear consensus regarding alternative models has emerged. One possible explanation is differential instrumentation across studies. In the present study, the authors used confirmatory factor analysis to compare a self-report measure, the PTSD Checklist (PCL), and a structured clinical interview, the Clinician-Administered PTSD Scale (CAPS), in 2,960 utility workers exposed to the World Trade Center Ground Zero site. Although two 4-factor models fit adequately for each measure, the latent structure of the PCL was slightly better represented by correlated reexperiencing, avoidance, dysphoria, and hyperarousal factors, whereas that of the CAPS was slightly better represented by correlated reexperiencing, avoidance, emotional numbing, and hyperarousal factors. After accounting for method variance, the model specifying dysphoria as a distinct factor achieved slightly better fit. Patterns of correlations with external variables provided additional support for the dysphoria model. Implications regarding the underlying structure of PTSD are discussed.

Synchronicity in predictive modelling: a new view of data assimilation

NASA Astrophysics Data System (ADS)

Duane, G. S.; Tribbia, J. J.; Weiss, J. B.

2006-11-01

The problem of data assimilation can be viewed as one of synchronizing two dynamical systems, one representing "truth" and the other representing "model", with a unidirectional flow of information between the two. Synchronization of truth and model defines a general view of data assimilation, as machine perception, that is reminiscent of the Jung-Pauli notion of synchronicity between matter and mind. The dynamical systems paradigm of the synchronization of a pair of loosely coupled chaotic systems is expected to be useful because quasi-2D geophysical fluid models have been shown to synchronize when only medium-scale modes are coupled. The synchronization approach is equivalent to standard approaches based on least-squares optimization, including Kalman filtering, except in highly non-linear regions of state space where observational noise links regimes with qualitatively different dynamics. The synchronization approach is used to calculate covariance inflation factors from parameters describing the bimodality of a one-dimensional system. The factors agree in overall magnitude with those used in operational practice on an ad hoc basis. The calculation is robust against the introduction of stochastic model error arising from unresolved scales.

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; Wullschleger, Stan D.; Thornton, Peter E.; Riley, William J.; Song, Xia; Graham, David E.; Song, Changchun; Tian, Hanqin

2016-06-01

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

From actors to agents in socio-ecological systems models

PubMed Central

Rounsevell, M. D. A.; Robinson, D. T.; Murray-Rust, D.

2012-01-01

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept. PMID:22144388

From actors to agents in socio-ecological systems models.

PubMed

Rounsevell, M D A; Robinson, D T; Murray-Rust, D

2012-01-19

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.

Bayesian Estimation of Circumplex Models Subject to Prior Theory Constraints and Scale-Usage Bias

ERIC Educational Resources Information Center

Lenk, Peter; Wedel, Michel; Bockenholt, Ulf

2006-01-01

This paper presents a hierarchical Bayes circumplex model for ordinal ratings data. The circumplex model was proposed to represent the circular ordering of items in psychological testing by imposing inequalities on the correlations of the items. We provide a specification of the circumplex, propose identifying constraints and conjugate priors for…

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

Treesearch

D. Todd Jones-Farrand; Todd M. Fearer; Wayne E. Thogmartin; Frank R. Thompson; Mark D. Nelson; John M. Tirpak

2011-01-01

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and...

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

NASA Technical Reports Server (NTRS)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, David; Bellugi, Dino; McKean, Jim; Dietrich, William E.

2013-04-01

Current practice in regional-scale shallow landslide hazard assessment is to adopt a one-dimensional slope stability representation. Such a representation cannot produce discrete landslides and thus cannot make predictions on landslide size. Furthermore, one-dimensional approaches cannot include lateral effects, which are known to be important in defining instability. Here we derive an alternative model that accounts for lateral resistance by representing the forces acting on each margin of an unstable block of soil. We model boundary frictional resistances using 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure, using the log-spiral method, on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion declines exponentially with soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are relatively well constrained and find that our model predicts failure at the observed location and predicts that larger or smaller failures conformal to the observed shape are indeed more stable. We use a sensitivity analysis of the model to show that lateral reinforcement sets a minimum landslide size, and that the additional strength at the downslope boundary results in optimal shapes that are longer in the downslope direction. However, reinforcement effects alone cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of the spatial pattern of key parameters (e.g. pore water pressure and soil depth) at the watershed scale. The application of the model at this scale requires an efficient method to find unstable shapes among an exponential number of candidates. In this context, the model allows a more extensive examination of the controls on landslide size, shape and location.

The Thick Level-Set model for dynamic fragmentation

DOE PAGES

Stershic, Andrew J.; Dolbow, John E.; Moës, Nicolas

2017-01-04

The Thick Level-Set (TLS) model is implemented to simulate brittle media undergoing dynamic fragmentation. This non-local model is discretized by the finite element method with damage represented as a continuous field over the domain. A level-set function defines the extent and severity of damage, and a length scale is introduced to limit the damage gradient. Numerical studies in one dimension demonstrate that the proposed method reproduces the rate-dependent energy dissipation and fragment length observations from analytical, numerical, and experimental approaches. In conclusion, additional studies emphasize the importance of appropriate bulk constitutive models and sufficient spatial resolution of the length scale.

A multi-directional and multi-scale roughness filter to detect lineament segments on digital elevation models - analyzing spatial objects in R

NASA Astrophysics Data System (ADS)

Baumann, Sebastian; Robl, Jörg; Wendt, Lorenz; Willingshofer, Ernst; Hilberg, Sylke

2016-04-01

Automated lineament analysis on remotely sensed data requires two general process steps: The identification of neighboring pixels showing high contrast and the conversion of these domains into lines. The target output is the lineaments' position, extent and orientation. We developed a lineament extraction tool programmed in R using digital elevation models as input data to generate morphological lineaments defined as follows: A morphological lineament represents a zone of high relief roughness, whose length significantly exceeds the width. As relief roughness any deviation from a flat plane, defined by a roughness threshold, is considered. In our novel approach a multi-directional and multi-scale roughness filter uses moving windows of different neighborhood sizes to identify threshold limited rough domains on digital elevation models. Surface roughness is calculated as the vertical elevation difference between the center cell and the different orientated straight lines connecting two edge cells of a neighborhood, divided by the horizontal distance of the edge cells. Thus multiple roughness values depending on the neighborhood sizes and orientations of the edge connecting lines are generated for each cell and their maximum and minimum values are extracted. Thereby negative signs of the roughness parameter represent concave relief structures as valleys, positive signs convex relief structures as ridges. A threshold defines domains of high relief roughness. These domains are thinned to a representative point pattern by a 3x3 neighborhood filter, highlighting maximum and minimum roughness peaks, and representing the center points of lineament segments. The orientation and extent of the lineament segments are calculated within the roughness domains, generating a straight line segment in the direction of least roughness differences. We tested our algorithm on digital elevation models of multiple sources and scales and compared the results visually with shaded relief map of these digital elevation models. The lineament segments trace the relief structure to a great extent and the calculated roughness parameter represents the physical geometry of the digital elevation model. Modifying the threshold for the surface roughness value highlights different distinct relief structures. Also the neighborhood size at which lineament segments are detected correspond with the width of the surface structure and may be a useful additional parameter for further analysis. The discrimination of concave and convex relief structures perfectly matches with valleys and ridges of the surface.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

A new framework for modeling decentralized low impact developments using Soil and Water Assessment Tool

USDA-ARS?s Scientific Manuscript database

Assessing the performance of Low Impact Development (LID) practices at a catchment scale is important in managing urban watersheds. Few modeling tools exist that are capable of explicitly representing the hydrological mechanisms of LIDs while considering the diverse land uses of urban watersheds. ...

Evaluating the mitigation of greenhouse gas emissions and adaptation in dairy production.

USDA-ARS?s Scientific Manuscript database

Process-level modeling at the farm scale provides a tool for evaluating strategies for both mitigating greenhouse gas emissions and adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to predict performance...

Estimating effective soil properties of heterogeneous areas for modeling infiltration and redistribution

USDA-ARS?s Scientific Manuscript database

Field scale water infiltration and soil-water and solute transport models require spatially-averaged “effective” soil hydraulic parameters to represent the average flux and storage. The values of these effective parameters vary for different conditions, processes, and component soils in a field. For...

TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

EPA Science Inventory

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

Flip This Classroom: A Comparative Study

ERIC Educational Resources Information Center

Unruh, Tiffany; Peters, Michelle L.; Willis, Jana

2016-01-01

The purpose of this research was to compare the beliefs and attitudes of teachers using the flipped versus the traditional class model. Survey and interview data were collected from a matched sample of in-service teachers representing both models from a large suburban southeastern Texas school district. The Attitude Towards Technology Scale, the…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stershic, Andrew J.; Dolbow, John E.; Moës, Nicolas

The Thick Level-Set (TLS) model is implemented to simulate brittle media undergoing dynamic fragmentation. This non-local model is discretized by the finite element method with damage represented as a continuous field over the domain. A level-set function defines the extent and severity of damage, and a length scale is introduced to limit the damage gradient. Numerical studies in one dimension demonstrate that the proposed method reproduces the rate-dependent energy dissipation and fragment length observations from analytical, numerical, and experimental approaches. In conclusion, additional studies emphasize the importance of appropriate bulk constitutive models and sufficient spatial resolution of the length scale.

Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

To investigate scene segmentation in the visual system we present a model of two reciprocally connected visual areas using spiking neurons. Area P corresponds to the orientation-selective subsystem of the primary visual cortex, while the central visual area C is modeled as associative memory representing stimulus objects according to Hebbian learning. Without feedback from area C, a single stimulus results in relatively slow and irregular activity, synchronized only for neighboring patches (slow state), while in the complete model activity is faster with an enlarged synchronization range (fast state). When presenting a superposition of several stimulus objects, scene segmentation happens on a time scale of hundreds of milliseconds by alternating epochs of the slow and fast states, where neurons representing the same object are simultaneously in the fast state. Correlation analysis reveals synchronization on different time scales as found in experiments (designated as tower, castle, and hill peaks). On the fast time scale (tower peaks, gamma frequency range), recordings from two sites coding either different or the same object lead to correlograms that are either flat or exhibit oscillatory modulations with a central peak. This is in agreement with experimental findings, whereas standard phase-coding models would predict shifted peaks in the case of different objects.

The short-form version of the Depression Anxiety Stress Scales (DASS-21): construct validity and normative data in a large non-clinical sample.

PubMed

Henry, Julie D; Crawford, John R

2005-06-01

To test the construct validity of the short-form version of the Depression anxiety and stress scale (DASS-21), and in particular, to assess whether stress as indexed by this measure is synonymous with negative affectivity (NA) or whether it represents a related, but distinct, construct. To provide normative data for the general adult population. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS-21 was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,794). Competing models of the latent structure of the DASS-21 were evaluated using CFA. The model with optimal fit (RCFI = 0.94) had a quadripartite structure, and consisted of a general factor of psychological distress plus orthogonal specific factors of depression, anxiety, and stress. This model was a significantly better fit than a competing model that tested the possibility that the Stress scale simply measures NA. The DASS-21 subscales can validly be used to measure the dimensions of depression, anxiety, and stress. However, each of these subscales also taps a more general dimension of psychological distress or NA. The utility of the measure is enhanced by the provision of normative data based on a large sample.

Multi-scale hydrometeorological observation and modelling for flash flood understanding

NASA Astrophysics Data System (ADS)

Braud, I.; Ayral, P.-A.; Bouvier, C.; Branger, F.; Delrieu, G.; Le Coz, J.; Nord, G.; Vandervaere, J.-P.; Anquetin, S.; Adamovic, M.; Andrieu, J.; Batiot, C.; Boudevillain, B.; Brunet, P.; Carreau, J.; Confoland, A.; Didon-Lescot, J.-F.; Domergue, J.-M.; Douvinet, J.; Dramais, G.; Freydier, R.; Gérard, S.; Huza, J.; Leblois, E.; Le Bourgeois, O.; Le Boursicaud, R.; Marchand, P.; Martin, P.; Nottale, L.; Patris, N.; Renard, B.; Seidel, J.-L.; Taupin, J.-D.; Vannier, O.; Vincendon, B.; Wijbrans, A.

2014-09-01

This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km2. The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1-100 km2), where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100-1000 km2), where the river routing and flooding processes become important. These observations are part of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) enhanced observation period (EOP), which will last 4 years (2012-2015). In terms of hydrological modelling, the objective is to set up regional-scale models, while addressing small and generally ungauged catchments, which represent the scale of interest for flood risk assessment. Top-down and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set-up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes on various scales.

Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

PubMed Central

2017-01-01

Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria. PMID:28133437

Neural Schematics as a unified formal graphical representation of large-scale Neural Network Structures.

PubMed

Ehrlich, Matthias; Schüffny, René

2013-01-01

One of the major outcomes of neuroscientific research are models of Neural Network Structures (NNSs). Descriptions of these models usually consist of a non-standardized mixture of text, figures, and other means of visual information communication in print media. However, as neuroscience is an interdisciplinary domain by nature, a standardized way of consistently representing models of NNSs is required. While generic descriptions of such models in textual form have recently been developed, a formalized way of schematically expressing them does not exist to date. Hence, in this paper we present Neural Schematics as a concept inspired by similar approaches from other disciplines for a generic two dimensional representation of said structures. After introducing NNSs in general, a set of current visualizations of models of NNSs is reviewed and analyzed for what information they convey and how their elements are rendered. This analysis then allows for the definition of general items and symbols to consistently represent these models as Neural Schematics on a two dimensional plane. We will illustrate the possibilities an agreed upon standard can yield on sampled diagrams transformed into Neural Schematics and an example application for the design and modeling of large-scale NNSs.

A meta-analysis and statistical modelling of nitrates in groundwater at the African scale

NASA Astrophysics Data System (ADS)

Ouedraogo, Issoufou; Vanclooster, Marnik

2016-06-01

Contamination of groundwater with nitrate poses a major health risk to millions of people around Africa. Assessing the space-time distribution of this contamination, as well as understanding the factors that explain this contamination, is important for managing sustainable drinking water at the regional scale. This study aims to assess the variables that contribute to nitrate pollution in groundwater at the African scale by statistical modelling. We compiled a literature database of nitrate concentration in groundwater (around 250 studies) and combined it with digital maps of physical attributes such as soil, geology, climate, hydrogeology, and anthropogenic data for statistical model development. The maximum, medium, and minimum observed nitrate concentrations were analysed. In total, 13 explanatory variables were screened to explain observed nitrate pollution in groundwater. For the mean nitrate concentration, four variables are retained in the statistical explanatory model: (1) depth to groundwater (shallow groundwater, typically < 50 m); (2) recharge rate; (3) aquifer type; and (4) population density. The first three variables represent intrinsic vulnerability of groundwater systems to pollution, while the latter variable is a proxy for anthropogenic pollution pressure. The model explains 65 % of the variation of mean nitrate contamination in groundwater at the African scale. Using the same proxy information, we could develop a statistical model for the maximum nitrate concentrations that explains 42 % of the nitrate variation. For the maximum concentrations, other environmental attributes such as soil type, slope, rainfall, climate class, and region type improve the prediction of maximum nitrate concentrations at the African scale. As to minimal nitrate concentrations, in the absence of normal distribution assumptions of the data set, we do not develop a statistical model for these data. The data-based statistical model presented here represents an important step towards developing tools that will allow us to accurately predict nitrate distribution at the African scale and thus may support groundwater monitoring and water management that aims to protect groundwater systems. Yet they should be further refined and validated when more detailed and harmonized data become available and/or combined with more conceptual descriptions of the fate of nutrients in the hydrosystem.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species. PMID:28609466

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in effective conservation planning, and can be readily applied to other wildlife species.

Neural Network Modeling of UH-60A Pilot Vibration

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi

2003-01-01

Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

A Coupled Ocean General Circulation, Biogeochemical, and Radiative Model of the Global Oceans: Seasonal Distributions of Ocean Chlorophyll and Nutrients

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Busalacchi, Antonio (Technical Monitor)

2000-01-01

A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability. and the interactions among three functional phytoplankton groups (diatoms. chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (greater than 1000 km) model chlorophyll results are in overall agreement with CZCS pigments in many global regions. Seasonal variability observed in the CZCS is also represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are generally in conformance although occasional departures are apparent. Model nitrate distributions agree with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicates that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent many aspects of the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Ego-resiliency reloaded: a three-component model of general resiliency.

PubMed

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency.

Ego-Resiliency Reloaded: A Three-Component Model of General Resiliency

PubMed Central

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency. PMID:25815881

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Intermittency in small-scale turbulence: a velocity gradient approach

NASA Astrophysics Data System (ADS)

Meneveau, Charles; Johnson, Perry

2017-11-01

Intermittency of small-scale motions is an ubiquitous facet of turbulent flows, and predicting this phenomenon based on reduced models derived from first principles remains an important open problem. Here, a multiple-time scale stochastic model is introduced for the Lagrangian evolution of the full velocity gradient tensor in fluid turbulence at arbitrarily high Reynolds numbers. This low-dimensional model differs fundamentally from prior shell models and other empirically-motivated models of intermittency because the nonlinear gradient self-stretching and rotation A2 term vital to the energy cascade and intermittency development is represented exactly from the Navier-Stokes equations. With only one adjustable parameter needed to determine the model's effective Reynolds number, numerical solutions of the resulting set of stochastic differential equations show that the model predicts anomalous scaling for moments of the velocity gradient components and negative derivative skewness. It also predicts signature topological features of the velocity gradient tensor such as vorticity alignment trends with the eigen-directions of the strain-rate. This research was made possible by a graduate Fellowship from the National Science Foundation and by a Grant from The Gulf of Mexico Research Initiative.

Total Score Reliability in Large-Scale Writing Assessment.

ERIC Educational Resources Information Center

Bunch, Michael B.; Littlefair, Wendy

A total of 2,000 essays written by 1,000 students was submitted to generalizability analyses for domain-referenced tests. Each student had written one essay on each of two prompts representing two models of discourse. Each essay was read by six readers and judged on a scale of from 1 to 4. No reader read essays from both prompts. Reader agreement…

Geostatistics and the representative elementary volume of gamma ray tomography attenuation in rocks cores

USGS Publications Warehouse

Vogel, J.R.; Brown, G.O.

2003-01-01

Semivariograms of samples of Culebra Dolomite have been determined at two different resolutions for gamma ray computed tomography images. By fitting models to semivariograms, small-scale and large-scale correlation lengths are determined for four samples. Different semivariogram parameters were found for adjacent cores at both resolutions. Relative elementary volume (REV) concepts are related to the stationarity of the sample. A scale disparity factor is defined and is used to determine sample size required for ergodic stationarity with a specified correlation length. This allows for comparison of geostatistical measures and representative elementary volumes. The modifiable areal unit problem is also addressed and used to determine resolution effects on correlation lengths. By changing resolution, a range of correlation lengths can be determined for the same sample. Comparison of voxel volume to the best-fit model correlation length of a single sample at different resolutions reveals a linear scaling effect. Using this relationship, the range of the point value semivariogram is determined. This is the range approached as the voxel size goes to zero. Finally, these results are compared to the regularization theory of point variables for borehole cores and are found to be a better fit for predicting the volume-averaged range.

Numerical and Experimental Studies of Particle Settling in Real Fracture Geometries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Pratanu; Du Frane, Wyatt L.; Kanarska, Yuliya

In this study, proppant is a vital component of hydraulic stimulation operations, improving conductivity by maintaining fracture aperture. While correct placement is a necessary part of ensuring that proppant performs efficiently, the transport behavior of proppant in natural rock fractures is poorly understood. In particular, as companies pursue new propping strategies involving new types of proppant, more accurate models of proppant behavior are needed to help guide their deployment. A major difficulty with simulating reservoir-scale proppant behavior is that continuum models traditionally used to represent large-scale slurry behavior loose applicability in fracture geometries. Particle transport models are often based onmore » representative volumes that are at the same scale or larger than fractures found in hydraulic fracturing operations, making them inappropriate for modeling these types of flows. In the absence of a first-principles approach, empirical closure relations are needed. However, even such empirical closure relationships are difficult to derive without an accurate understanding of proppant behavior on the particle level. Thus, there is a need for experiments and simulations capable of probing phenomena at the sub-fracture scale. In this paper, we present results from experimental and numerical studies investigating proppant behavior at the sub-fracture level, in particular, the role of particle dispersion during proppant settling. In the experimental study, three-dimensional printing techniques are used to accurately reproduce the topology of a fractured Marcellus shale sample inside a particle-flow cell.« less

Numerical and Experimental Studies of Particle Settling in Real Fracture Geometries

DOE PAGES

Roy, Pratanu; Du Frane, Wyatt L.; Kanarska, Yuliya; ...

2016-09-30

In this study, proppant is a vital component of hydraulic stimulation operations, improving conductivity by maintaining fracture aperture. While correct placement is a necessary part of ensuring that proppant performs efficiently, the transport behavior of proppant in natural rock fractures is poorly understood. In particular, as companies pursue new propping strategies involving new types of proppant, more accurate models of proppant behavior are needed to help guide their deployment. A major difficulty with simulating reservoir-scale proppant behavior is that continuum models traditionally used to represent large-scale slurry behavior loose applicability in fracture geometries. Particle transport models are often based onmore » representative volumes that are at the same scale or larger than fractures found in hydraulic fracturing operations, making them inappropriate for modeling these types of flows. In the absence of a first-principles approach, empirical closure relations are needed. However, even such empirical closure relationships are difficult to derive without an accurate understanding of proppant behavior on the particle level. Thus, there is a need for experiments and simulations capable of probing phenomena at the sub-fracture scale. In this paper, we present results from experimental and numerical studies investigating proppant behavior at the sub-fracture level, in particular, the role of particle dispersion during proppant settling. In the experimental study, three-dimensional printing techniques are used to accurately reproduce the topology of a fractured Marcellus shale sample inside a particle-flow cell.« less

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size.

PubMed

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics.

A Life-Cycle Model of Human Social Groups Produces a U-Shaped Distribution in Group Size

PubMed Central

Salali, Gul Deniz; Whitehouse, Harvey; Hochberg, Michael E.

2015-01-01

One of the central puzzles in the study of sociocultural evolution is how and why transitions from small-scale human groups to large-scale, hierarchically more complex ones occurred. Here we develop a spatially explicit agent-based model as a first step towards understanding the ecological dynamics of small and large-scale human groups. By analogy with the interactions between single-celled and multicellular organisms, we build a theory of group lifecycles as an emergent property of single cell demographic and expansion behaviours. We find that once the transition from small-scale to large-scale groups occurs, a few large-scale groups continue expanding while small-scale groups gradually become scarcer, and large-scale groups become larger in size and fewer in number over time. Demographic and expansion behaviours of groups are largely influenced by the distribution and availability of resources. Our results conform to a pattern of human political change in which religions and nation states come to be represented by a few large units and many smaller ones. Future enhancements of the model should include decision-making rules and probabilities of fragmentation for large-scale societies. We suggest that the synthesis of population ecology and social evolution will generate increasingly plausible models of human group dynamics. PMID:26381745

Numerical and Experimental Studies of Particle Settling in Real Fracture Geometries

NASA Astrophysics Data System (ADS)

Roy, Pratanu; Du Frane, Wyatt L.; Kanarska, Yuliya; Walsh, Stuart D. C.

2016-11-01

Proppant is a vital component of hydraulic stimulation operations, improving conductivity by maintaining fracture aperture. While correct placement is a necessary part of ensuring that proppant performs efficiently, the transport behavior of proppant in natural rock fractures is poorly understood. In particular, as companies pursue new propping strategies involving new types of proppant, more accurate models of proppant behavior are needed to help guide their deployment. A major difficulty with simulating reservoir-scale proppant behavior is that continuum models traditionally used to represent large-scale slurry behavior loose applicability in fracture geometries. Particle transport models are often based on representative volumes that are at the same scale or larger than fractures found in hydraulic fracturing operations, making them inappropriate for modeling these types of flows. In the absence of a first-principles approach, empirical closure relations are needed. However, even such empirical closure relationships are difficult to derive without an accurate understanding of proppant behavior on the particle level. Thus, there is a need for experiments and simulations capable of probing phenomena at the sub-fracture scale. In this paper, we present results from experimental and numerical studies investigating proppant behavior at the sub-fracture level, in particular, the role of particle dispersion during proppant settling. In the experimental study, three-dimensional printing techniques are used to accurately reproduce the topology of a fractured Marcellus shale sample inside a particle-flow cell. By recreating the surface in clear plastic resin, proppant movement within the fracture can be tracked directly in real time without the need for X-ray imaging. Particle tracking is further enhanced through the use of mixtures of transparent and opaque proppant analogues. The accompanying numerical studies employ a high-fidelity three-dimensional particle-flow model, capable of explicitly representing the particles, the fracture surface and the interstitial fluid flow. Both studies reveal large-scale vortex motion during particle settling. For the most part, this behavior is independent of the fracture topology, instead driven by interactions between the sinking particles and the upwelling interstitial fluid. This motion results in large amounts of particle dispersion, significantly greater than might be expected from traditional slurry models. The competition between the particles and the fluid also results in a redistribution of particles toward the fracture walls, which has significant implications for the transport of proppant along the fracture.

The Influence of Multi-Scale Stratal Architecture on Multi-Phase Flow

NASA Astrophysics Data System (ADS)

Soltanian, M.; Gershenzon, N. I.; Ritzi, R. W.; Dominic, D.; Ramanathan, R.

2012-12-01

Geological heterogeneity affects flow and transport in porous media, including the migration and entrapment patterns of oil, and efforts for enhanced oil recovery. Such effects are only understood through their relation to a hierarchy of reservoir heterogeneities over a range of scales. Recent work on modern rivers and ancient sediments has led to a conceptual model of the hierarchy of fluvial forms within channel-belts of gravelly braided rivers, and a quantitative model for the corresponding scales of heterogeneity within the stratal architecture (e.g. [Lunt et al (2004) Sedimentology, 51 (3), 377]). In related work, a three-dimensional digital model was developed which represents these scales of fluvial architecture, the associated spatial distribution of permeability, and the connectivity of high-permeability pathways across the different scales of the stratal hierarchy [Ramanathan et al, (2010) Water Resour. Res., 46, W04515; Guin et al, (2010) Water Resour. Res., 46, W04516]. In the present work we numerically examine three-phase fluid flow (water-oil-gas) incorporating the multi-scale model for reservoir heterogeneity spanning the scales from 10^-1 to 10^3 meters. Comparison with results of flow in a reservoir with homogeneous permeability is made showing essentially different flow dynamics.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

Scaling between reanalyses and high-resolution land-surface modelling in mountainous areas - enabling better application and testing of reanalyses in heterogeneous environments

NASA Astrophysics Data System (ADS)

Gruber, S.; Fiddes, J.

2013-12-01

In mountainous topography, the difference in scale between atmospheric reanalyses (typically tens of kilometres) and relevant processes and phenomena near the Earth surface, such as permafrost or snow cover (meters to tens of meters) is most obvious. This contrast of scales is one of the major obstacles to using reanalysis data for the simulation of surface phenomena and to confronting reanalyses with independent observation. At the example of modelling permafrost in mountain areas (but simple to generalise to other phenomena and heterogeneous environments), we present and test methods against measurements for (A) scaling atmospheric data from the reanalysis to the ground level and (B) smart sampling of the heterogeneous landscape in order to set up a lumped model simulation that represents the high-resolution land surface. TopoSCALE (Part A, see http://dx.doi.org/10.5194/gmdd-6-3381-2013) is a scheme, which scales coarse-grid climate fields to fine-grid topography using pressure level data. In addition, it applies necessary topographic corrections e.g. those variables required for computation of radiation fields. This provides the necessary driving fields to the LSM. Tested against independent ground data, this scheme has been shown to improve the scaling and distribution of meteorological parameters in complex terrain, as compared to conventional methods, e.g. lapse rate based approaches. TopoSUB (Part B, see http://dx.doi.org/10.5194/gmd-5-1245-2012) is a surface pre-processor designed to sample a fine-grid domain (defined by a digital elevation model) along important topographical (or other) dimensions through a clustering scheme. This allows constructing a lumped model representing the main sources of fine-grid variability and applying a 1D LSM efficiently over large areas. Results can processed to derive (i) summary statistics at coarse-scale re-analysis grid resolution, (ii) high-resolution data fields spatialized to e.g., the fine-scale digital elevation model grid, or (iii) validation products for locations at which measurements exist, only. The ability of TopoSUB to approximate results simulated by a 2D distributed numerical LSM at a factor of ~10,000 less computations is demonstrated by comparison of 2D and lumped simulations. Successful application of the combined scheme in the European Alps is reported and based on its results, open issues for future research are outlined.

Simulations of Sea Level Rise Effects on Complex Coastal Systems

NASA Astrophysics Data System (ADS)

Niedoroda, A. W.; Ye, M.; Saha, B.; Donoghue, J. F.; Reed, C. W.

2009-12-01

It is now established that complex coastal systems with elements such as beaches, inlets, bays, and rivers adjust their morphologies according to time-varying balances in between the processes that control the exchange of sediment. Accelerated sea level rise introduces a major perturbation into the sediment-sharing systems. A modeling framework based on a new SL-PR model which is an advanced version of the aggregate-scale CST Model and the event-scale CMS-2D and CMS-Wave combination have been used to simulate the recent evolution of a portion of the Florida panhandle coast. This combination of models provides a method to evaluate coefficients in the aggregate-scale model that were previously treated as fitted parameters. That is, by carrying out simulations of a complex coastal system with runs of the event-scale model representing more than a year it is now possible to directly relate the coefficients in the large-scale SL-PR model to measureable physical parameters in the current and wave fields. This cross-scale modeling procedure has been used to simulate the shoreline evolution at the Santa Rosa Island, a long barrier which houses significant military infrastructure at the north Gulf Coast. The model has been used to simulate 137 years of measured shoreline change and to extend these to predictions of future rates of shoreline migration.

Five challenges for spatial epidemic models

PubMed Central

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-01-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. PMID:25843387

Representative Structural Element - A New Paradigm for Multi-Scale Structural Modeling

DTIC Science & Technology

2016-07-05

developed by NASA Glenn Research Center based on Aboudi’s micromechanics theories [5] that provides a wide range of capabilities for modeling ...to use appropriate models for related problems based on the capability of corresponding approaches. Moreover, the analyses will give a general...interface of heterogeneous materials but also help engineers to use appropriate models for related problems based on the capability of corresponding

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

“Modeling Trends in Air Pollutant Concentrations over the ...

EPA Pesticide Factsheets

Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the free-troposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for pr

Evaluation of Scaling Methods for Rotorcraft Icing

NASA Technical Reports Server (NTRS)

Tsao, Jen-Ching; Kreeger, Richard E.

2010-01-01

This paper reports result of an experimental study in the NASA Glenn Icing Research Tunnel (IRT) to evaluate how well the current recommended scaling methods developed for fixed-wing unprotected surface icing applications might apply to representative rotor blades at finite angle of attack. Unlike the fixed-wing case, there is no single scaling method that has been systematically developed and evaluated for rotorcraft icing applications. In the present study, scaling was based on the modified Ruff method with scale velocity determined by maintaining constant Weber number. Models were unswept NACA 0012 wing sections. The reference model had a chord of 91.4 cm and scale model had a chord of 35.6 cm. Reference tests were conducted with velocities of 76 and 100 kt (39 and 52 m/s), droplet MVDs of 150 and 195 fun, and with stagnation-point freezing fractions of 0.3 and 0.5 at angle of attack of 0deg and 5deg. It was shown that good ice shape scaling was achieved for NACA 0012 airfoils with angle of attack lip to 5deg.

Runoff production in a small agricultural catchment in Lao PDR : influence of slope, land-use and observation scale.

NASA Astrophysics Data System (ADS)

Patin, J.; Ribolzi, O.; Mugler, C.; Valentin, C.; Mouche, E.

2009-04-01

We study the surface and sub-surface hydrology of a small agricultural catchment (60ha) located in the Luang Prabang province of Lao PDR. This catchment is representative of the rural mountainous south east Asia. It exhibits steep slopes (up to 100% and more) under a monsoon climate. After years of traditional slash and burn cultures, it is now under high land pressures due to population resettling and environment preservation policies. This evolution leads to rapid land-use changes such as shifting cultivation reduction or growing of teak forest instead of classical crops. This catchment is a benchmark site of the Managing Soil Erosion Consortium since 1998. The international consortium aims to understand the effects of agricultural changes on the catchment hydrology and soil erosion in south east Asia. The Huay Pano catchment is subdivided into small sub-catchments that are gauged and monitored. Differ- ent agricultural practices where tested along the years. At a smaller scale, plot of 1m2 are instrumented to follow runoff and detachment of soil under natural rainfall along the monsoon season. Our modeling work aims to develop a distributed hydrological model integrating experimental data at the different scales. One of the objective is to understand the impact of land-use, soil properties (slope, crust, etc) and rainfall (dry and wet seasons) on surface and subsurface flows. We present here modeling results of the runoff plot experiments (1m2 scale) performed from 2002 to 2007. The plots distribution among the catchment and over the years gives a good representativity of the different runoff responses. The role of crust, slope and land-use on runoff is examined. Finally we discuss how this plot scale will be integrated in a sub-catchment model, with a particular attention on the observed paradox: how to explain that runoff coefficients at the catchment scale are much slower than at the plot scale ?

Modeling of turbulence and transition

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing

1992-01-01

The first objective is to evaluate current two-equation and second order closure turbulence models using available direct numerical simulations and experiments, and to identify the models which represent the state of the art in turbulence modeling. The second objective is to study the near-wall behavior of turbulence, and to develop reliable models for an engineering calculation of turbulence and transition. The third objective is to develop a two-scale model for compressible turbulence.

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

Cost decomposition of linear systems with application to model reduction

NASA Technical Reports Server (NTRS)

Skelton, R. E.

1980-01-01

A means is provided to assess the value or 'cst' of each component of a large scale system, when the total cost is a quadratic function. Such a 'cost decomposition' of the system has several important uses. When the components represent physical subsystems which can fail, the 'component cost' is useful in failure mode analysis. When the components represent mathematical equations which may be truncated, the 'component cost' becomes a criterion for model truncation. In this latter event component costs provide a mechanism by which the specific control objectives dictate which components should be retained in the model reduction process. This information can be valuable in model reduction and decentralized control problems.

Physical models of collective cell motility: from cell to tissue

NASA Astrophysics Data System (ADS)

Camley, B. A.; Rappel, W.-J.

2017-03-01

In this article, we review physics-based models of collective cell motility. We discuss a range of techniques at different scales, ranging from models that represent cells as simple self-propelled particles to phase field models that can represent a cell’s shape and dynamics in great detail. We also extensively review the ways in which cells within a tissue choose their direction, the statistics of cell motion, and some simple examples of how cell-cell signaling can interact with collective cell motility. This review also covers in more detail selected recent works on collective cell motion of small numbers of cells on micropatterns, in wound healing, and the chemotaxis of clusters of cells.

Development of a zoning-based environmental-ecological-coupled model for lakes to assess lake restoration effect

NASA Astrophysics Data System (ADS)

Xu, Mengjia; Zou, Changxin; Zhao, Yanwei

2017-04-01

Environmental/ecological models are widely used for lake management as they provide a means to understand physical, chemical and biological processes in highly complex ecosystems. Most research focused on the development of environmental (water quality) and ecological models, separately. Limited studies were developed to couple the two models, and in these limited coupled models, a lake was regarded as a whole for analysis (i.e., considering the lake to be one well-mixed box), which was appropriate for small-scale lakes and was not sufficient to capture spatial variations within middle-scale or large-scale lakes. This paper seeks to establish a zoning-based environmental-ecological-coupled model for a lake. The Baiyangdian Lake, the largest freshwater lake in Northern China, was adopted as the study case. The coupled lake models including a hydrodynamics and water quality model established by MIKE21 and a compartmental ecological model used STELLA software have been established for middle-sized Baiyangdian Lake to realize the simulation of spatial variations of ecological conditions. On the basis of the flow field distribution results generated by MIKE21 hydrodynamics model, four water area zones were used as an example for compartmental ecological model calibration and validation. The results revealed that the developed coupled lake models can reasonably reflected the changes of the key state variables although there remain some state variables that are not well represented by the model due to the low quality of field monitoring data. Monitoring sites in a compartment may not be representative of the water quality and ecological conditions in the entire compartment even though that is the intention of compartment-based model design. There was only one ecological observation from a single monitoring site for some periods. This single-measurement issue may cause large discrepancies particularly when sampled site is not representative of the whole compartment. The coupled models have been applied to simulate the spatial variation trends of ecological condition under ecological water supplement as an example to reflect the application effect in lake restoration and management. The simulation results indicate that the models can provide a useful tool for lake restoration and management. The simulated spatial variation trends can provide a foundation for establishing permissible ranges for a selected set of water quality indices for a series of management measures such as watershed pollution load control and ecological water transfer. Meanwhile, the coupled models can help us to understand processes taking place and the relations of interaction between components in the lake ecosystem and external conditions. Taken together, the proposed models we established show some promising applications as middle-scale or large-scale lake management tools for pollution load control and ecological water transfer. These tools quantify the implications of proposed future water management decisions.

The GFS Atmospheric Model description

Science.gov Websites

model has only one type of cloud cover represented by C. In the tropics the cloudiness is primarily due mainly through grid-scale condensation. The fractional cloud cover C is available at all model levels , 1996: Parameterizations for the absorption of solar radiation by water vapor and ozone. J. Atmos. Sci

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity N. C. Dickson, K. Gierens, H. L. Rogers, R. L. Jones

NASA Astrophysics Data System (ADS)

Dickson, N.

2009-12-01

The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal size of ISSR is 150 km (±250km) although 12-14% of ISS events occur on horizontal scales of less than 5km. The average vertical thickness of ISS layers is 600-800m (±575m) but layers ranging from 25m to 3000m have been observed, with up to one third of ISS layers thought to be less than 100m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50 and 100 hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50 and 100 hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Modeling of Atmospheric Turbulence as Disturbances for Control Design and Evaluation of High Speed Propulsion Systems

NASA Technical Reports Server (NTRS)

Kopasakis, George

2010-01-01

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying integrated couplings between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms. Then a generalized formulation is developed in frequency domain for these scale models that approximates the fractional order with the products of first order transfer functions. Given the parameters describing the conditions of atmospheric disturbances and utilizing the derived formulations, the objective is to directly compute the transfer functions that describe these disturbances for acoustic velocity, temperature, pressure and density. Utilizing these computed transfer functions and choosing the disturbance frequencies of interest, time domain simulations of these representative atmospheric turbulences can be developed. These disturbance representations are then used to first develop considerations for disturbance rejection specifications for the design of the propulsion control system, and then to evaluate the closed-loop performance.

Role of weakest links and system-size scaling in multiscale modeling of stochastic plasticity

NASA Astrophysics Data System (ADS)

Ispánovity, Péter Dusán; Tüzes, Dániel; Szabó, Péter; Zaiser, Michael; Groma, István

2017-02-01

Plastic deformation of crystalline and amorphous matter often involves intermittent local strain burst events. To understand the physical background of the phenomenon a minimal stochastic mesoscopic model was introduced, where details of the microstructure evolution are statistically represented in terms of a fluctuating local yield threshold. In the present paper we propose a method for determining the corresponding yield stress distribution for the case of crystal plasticity from lower scale discrete dislocation dynamics simulations which we combine with weakest link arguments. The success of scale linking is demonstrated by comparing stress-strain curves obtained from the resulting mesoscopic and the underlying discrete dislocation models in the microplastic regime. As shown by various scaling relations they are statistically equivalent and behave identically in the thermodynamic limit. The proposed technique is expected to be applicable to different microstructures and also to amorphous materials.

Vertical Descent and Landing Tests of a 0.13-Scale Model of the Convair XFY-1 Vertically Rising Airplane in Still Air, TED No. NACA DE 368

NASA Technical Reports Server (NTRS)

Smith, Charlee C., Jr.; Lovell, Powell M., Jr.

1954-01-01

An investigation is being conducted to determine the dynamic stability and control characteristics of a 0.13-scale flying model of Convair XFY-1 vertically rising airplane. This paper presents the results of flight and force tests to determine the stability and control characteristics of the model in vertical descent and landings in still air. The tests indicated that landings, including vertical descent from altitudes representing up to 400 feet for the full-scale airplane and at rates of descent up to 15 or 20 feet per second (full scale), can be performed satisfactorily. Sustained vertical descent in still air probably will be more difficult to perform because of large random trim changes that become greater as the descent velocity is increased. A slight steady head wind or cross wind might be sufficient to eliminate the random trim changes.

Scaling effects in the static and dynamic response of graphite-epoxy beam-columns. Ph.D. Thesis - Virginia Polytechnic Inst. and State Univ.

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

1990-01-01

Scale model technology represents one method of investigating the behavior of advanced, weight-efficient composite structures under a variety of loading conditions. It is necessary, however, to understand the limitations involved in testing scale model structures before the technique can be fully utilized. These limitations, or scaling effects, are characterized. in the large deflection response and failure of composite beams. Scale model beams were loaded with an eccentric axial compressive load designed to produce large bending deflections and global failure. A dimensional analysis was performed on the composite beam-column loading configuration to determine a model law governing the system response. An experimental program was developed to validate the model law under both static and dynamic loading conditions. Laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic were tested to examine a diversity of composite response and failure modes. The model beams were loaded under scaled test conditions until catastrophic failure. A large deflection beam solution was developed to compare with the static experimental results and to analyze beam failure. Also, the finite element code DYCAST (DYnamic Crash Analysis of STructure) was used to model both the static and impulsive beam response. Static test results indicate that the unidirectional and cross ply beam responses scale as predicted by the model law, even under severe deformations. In general, failure modes were consistent between scale models within a laminate family; however, a significant scale effect was observed in strength. The scale effect in strength which was evident in the static tests was also observed in the dynamic tests. Scaling of load and strain time histories between the scale model beams and the prototypes was excellent for the unidirectional beams, but inconsistent results were obtained for the angle ply, cross ply, and quasi-isotropic beams. Results show that valuable information can be obtained from testing on scale model composite structures, especially in the linear elastic response region. However, due to scaling effects in the strength behavior of composite laminates, caution must be used in extrapolating data taken from a scale model test when that test involves failure of the structure.

Emergence of scale-free close-knit friendship structure in online social networks.

PubMed

Cui, Ai-Xiang; Zhang, Zi-Ke; Tang, Ming; Hui, Pak Ming; Fu, Yan

2012-01-01

Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four real networks. This work helps understand the interplay between structures on different scales in online social networks.

Emergence of Scale-Free Close-Knit Friendship Structure in Online Social Networks

PubMed Central

Cui, Ai-Xiang; Zhang, Zi-Ke; Tang, Ming; Hui, Pak Ming; Fu, Yan

2012-01-01

Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four real networks. This work helps understand the interplay between structures on different scales in online social networks. PMID:23272067

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

USGS Publications Warehouse

Knightes, Christopher D.; Golden, Heather E.; Journey, Celeste A.; Davis, Gary M.; Conrads, Paul; Marvin-DiPasquale, Mark; Brigham, Mark E.; Bradley, Paul M.

2014-01-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km2) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km2 and 25 km2) and the encompassing watershed (79 km2). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport.

Chaotic and regular instantons in helical shell models of turbulence

NASA Astrophysics Data System (ADS)

De Pietro, Massimo; Mailybaev, Alexei A.; Biferale, Luca

2017-03-01

Shell models of turbulence have a finite-time blowup in the inviscid limit, i.e., the enstrophy diverges while the single-shell velocities stay finite. The signature of this blowup is represented by self-similar instantonic structures traveling coherently through the inertial range. These solutions might influence the energy transfer and the anomalous scaling properties empirically observed for the forced and viscous models. In this paper we present a study of the instantonic solutions for a set of four shell models of turbulence based on the exact decomposition of the Navier-Stokes equations in helical eigenstates. We find that depending on the helical structure of each model, instantons are chaotic or regular. Some instantonic solutions tend to recover mirror symmetry for scales small enough. Models that have anomalous scaling develop regular nonchaotic instantons. Conversely, models that have nonanomalous scaling in the stationary regime are those that have chaotic instantons. The direction of the energy carried by each single instanton tends to coincide with the direction of the energy cascade in the stationary regime. Finally, we find that whenever the small-scale stationary statistics is intermittent, the instanton is less steep than the dimensional Kolmogorov scaling, independently of whether or not it is chaotic. Our findings further support the idea that instantons might be crucial to describe some aspects of the multiscale anomalous statistics of shell models.

Assessing the ability of potential evapotranspiration models in capturing dynamics of evaporative demand across various biomes and climatic regimes with ChinaFLUX measurements

NASA Astrophysics Data System (ADS)

Zheng, Han; Yu, Guirui; Wang, Qiufeng; Zhu, Xianjin; Yan, Junhua; Wang, Huimin; Shi, Peili; Zhao, Fenghua; Li, Yingnian; Zhao, Liang; Zhang, Junhui; Wang, Yanfen

2017-08-01

Estimates of atmospheric evaporative demand have been widely required for a variety of hydrological analyses, with potential evapotranspiration (PET) being an important measure representing evaporative demand of actual vegetated surfaces under given metrological conditions. In this study, we assessed the ability of various PET models in capturing long-term (typically 2003-2011) dynamics of evaporative demand at eight ecosystems across various biomes and climatic regimes in China. Prior to assessing PET dynamics, we first examined the reasonability of fourteen PET models in representing the magnitudes of evaporative demand using eddy-covariance actual evapotranspiration (AET) as an indicator. Results showed that the robustness of the fourteen PET models differed somewhat across the sites, and only three PET models could produce reasonable magnitudes of evaporative demand (i.e., PET ≥ AET on average) for all eight sites, including the: (i) Penman; (ii) Priestly-Taylor and (iii) Linacre models. Then, we assessed the ability of these three PET models in capturing dynamics of evaporative demand by comparing the annual and seasonal trends in PET against the equivalent trends in AET and precipitation (P) for particular sites. Results indicated that nearly all the three PET models could faithfully reproduce the dynamics in evaporative demand for the energy-limited conditions at both annual and seasonal scales, while only the Penman and Linacre models could represent dynamics in evaporative demand for the water-limited conditions. However, the Linacre model was unable to reproduce the seasonal switches between water- and energy-limited states for some sites. Our findings demonstrated that the choice of PET models would be essential for the evaporative demand analyses and other related hydrological analyses at different temporal and spatial scales.

A fuzzy set preference model for market share analysis

NASA Technical Reports Server (NTRS)

Turksen, I. B.; Willson, Ian A.

1992-01-01

Consumer preference models are widely used in new product design, marketing management, pricing, and market segmentation. The success of new products depends on accurate market share prediction and design decisions based on consumer preferences. The vague linguistic nature of consumer preferences and product attributes, combined with the substantial differences between individuals, creates a formidable challenge to marketing models. The most widely used methodology is conjoint analysis. Conjoint models, as currently implemented, represent linguistic preferences as ratio or interval-scaled numbers, use only numeric product attributes, and require aggregation of individuals for estimation purposes. It is not surprising that these models are costly to implement, are inflexible, and have a predictive validity that is not substantially better than chance. This affects the accuracy of market share estimates. A fuzzy set preference model can easily represent linguistic variables either in consumer preferences or product attributes with minimal measurement requirements (ordinal scales), while still estimating overall preferences suitable for market share prediction. This approach results in flexible individual-level conjoint models which can provide more accurate market share estimates from a smaller number of more meaningful consumer ratings. Fuzzy sets can be incorporated within existing preference model structures, such as a linear combination, using the techniques developed for conjoint analysis and market share estimation. The purpose of this article is to develop and fully test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation), and how much to make (market share prediction).

Modeling and visualizing borehole information on virtual globes using KML

NASA Astrophysics Data System (ADS)

Zhu, Liang-feng; Wang, Xi-feng; Zhang, Bing

2014-01-01

Advances in virtual globes and Keyhole Markup Language (KML) are providing the Earth scientists with the universal platforms to manage, visualize, integrate and disseminate geospatial information. In order to use KML to represent and disseminate subsurface geological information on virtual globes, we present an automatic method for modeling and visualizing a large volume of borehole information. Based on a standard form of borehole database, the method first creates a variety of borehole models with different levels of detail (LODs), including point placemarks representing drilling locations, scatter dots representing contacts and tube models representing strata. Subsequently, the level-of-detail based (LOD-based) multi-scale representation is constructed to enhance the efficiency of visualizing large numbers of boreholes. Finally, the modeling result can be loaded into a virtual globe application for 3D visualization. An implementation program, termed Borehole2KML, is developed to automatically convert borehole data into KML documents. A case study of using Borehole2KML to create borehole models in Shanghai shows that the modeling method is applicable to visualize, integrate and disseminate borehole information on the Internet. The method we have developed has potential use in societal service of geological information.

Model calibration and issues related to validation, sensitivity analysis, post-audit, uncertainty evaluation and assessment of prediction data needs

USGS Publications Warehouse

Tiedeman, Claire; Hill, Mary C.

2007-01-01

When simulating natural and engineered groundwater flow and transport systems, one objective is to produce a model that accurately represents important aspects of the true system. However, using direct measurements of system characteristics, such as hydraulic conductivity, to construct a model often produces simulated values that poorly match observations of the system state, such as hydraulic heads, flows and concentrations (for example, Barth et al., 2001). This occurs because of inaccuracies in the direct measurements and because the measurements commonly characterize system properties at different scales from that of the model aspect to which they are applied. In these circumstances, the conservation of mass equations represented by flow and transport models can be used to test the applicability of the direct measurements, such as by comparing model simulated values to the system state observations. This comparison leads to calibrating the model, by adjusting the model construction and the system properties as represented by model parameter values, so that the model produces simulated values that reasonably match the observations.

Modelling Thin Film Microbending: A Comparative Study of Three Different Approaches

NASA Astrophysics Data System (ADS)

Aifantis, Katerina E.; Nikitas, Nikos; Zaiser, Michael

2011-09-01

Constitutive models which describe crystal microplasticity in a continuum framework can be envisaged as average representations of the dynamics of dislocation systems. Thus, their performance needs to be assessed not only by their ability to correctly represent stress-strain characteristics on the specimen scale but also by their ability to correctly represent the evolution of internal stress and strain patterns. In the present comparative study we consider the bending of a free-standing thin film. We compare the results of 3D DDD simulations with those obtained from a simple 1D gradient plasticity model and a more complex dislocation-based continuum model. Both models correctly reproduce the nontrivial strain patterns predicted by DDD for the microbending problem.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

A Cellular Automata Model for the Study of Landslides

NASA Astrophysics Data System (ADS)

Liucci, Luisa; Suteanu, Cristian; Melelli, Laura

2016-04-01

Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model parameters, and its temporal behavior. Results show that the model reproduces the scaling behavior of real landslide areas; while the value of the scaling exponent is stable over time, it linearly decreases with increasing rate of weakening. This suggests that it is the intensity of the triggering mechanism rather than its duration that affects the probability of landslide magnitudes. A quantitative relationship between the scaling exponent of the area frequency distribution of the generated landslides, on one hand, and the changes regarding the topographic surface affected by landslides, on the other hand, is established. The fact that a similar behavior could be observed in real systems may have useful implications in the context of landslide hazard assessment. These results support the hypotheses that landslides are driven by SOC dynamics, and that topography plays a key role in the scaling properties of their size distribution.

Uncertainty Quantification in High Throughput Screening: Applications to Models of Endocrine Disruption, Cytotoxicity, and Zebrafish Development (GRC Drug Safety)

EPA Science Inventory

Using uncertainty quantification, we aim to improve the quality of modeling data from high throughput screening assays for use in risk assessment. ToxCast is a large-scale screening program that analyzes thousands of chemicals using over 800 assays representing hundreds of bioche...

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models

NASA Astrophysics Data System (ADS)

Schneider, Adam; Flanner, Mark; Perket, Justin

2018-02-01

Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Mesh refinement in a two-dimensional large eddy simulation of a forced shear layer

NASA Technical Reports Server (NTRS)

Claus, R. W.; Huang, P. G.; Macinnes, J. M.

1989-01-01

A series of large eddy simulations are made of a forced shear layer and compared with experimental data. Several mesh densities were examined to separate the effect of numerical inaccuracy from modeling deficiencies. The turbulence model that was used to represent small scale, 3-D motions correctly predicted some gross features of the flow field, but appears to be structurally incorrect. The main effect of mesh refinement was to act as a filter on the scale of vortices that developed from the inflow boundary conditions.

Towards mechanism-based simulation of impact damage using exascale computing

NASA Astrophysics Data System (ADS)

Shterenlikht, Anton; Margetts, Lee; McDonald, Samuel; Bourne, Neil K.

2017-01-01

Over the past 60 years, the finite element method has been very successful in modelling deformation in engineering structures. However the method requires the definition of constitutive models that represent the response of the material to applied loads. There are two issues. Firstly, the models are often difficult to define. Secondly, there is often no physical connection between the models and the mechanisms that accommodate deformation. In this paper, we present a potentially disruptive two-level strategy which couples the finite element method at the macroscale with cellular automata at the mesoscale. The cellular automata are used to simulate mechanisms, such as crack propagation. The stress-strain relationship emerges as a continuum mechanics scale interpretation of changes at the micro- and meso-scales. Iterative two-way updating between the cellular automata and finite elements drives the simulation forward as the material undergoes progressive damage at high strain rates. The strategy is particularly attractive on large-scale computing platforms as both methods scale well on tens of thousands of CPUs.

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Towards Cloud-Resolving European-Scale Climate Simulations using a fully GPU-enabled Prototype of the COSMO Regional Model

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Cumming, Benjamin; Lapillonne, Xavier; Gysi, Tobias; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph

2014-05-01

The representation of moist convection is a major shortcoming of current global and regional climate models. State-of-the-art global models usually operate at grid spacings of 10-300 km, and therefore cannot fully resolve the relevant upscale and downscale energy cascades. Therefore parametrization of the relevant sub-grid scale processes is required. Several studies have shown that this approach entails major uncertainties for precipitation processes, which raises concerns about the model's ability to represent precipitation statistics and associated feedback processes, as well as their sensitivities to large-scale conditions. Further refining the model resolution to the kilometer scale allows representing these processes much closer to first principles and thus should yield an improved representation of the water cycle including the drivers of extreme events. Although cloud-resolving simulations are very useful tools for climate simulations and numerical weather prediction, their high horizontal resolution and consequently the small time steps needed, challenge current supercomputers to model large domains and long time scales. The recent innovations in the domain of hybrid supercomputers have led to mixed node designs with a conventional CPU and an accelerator such as a graphics processing unit (GPU). GPUs relax the necessity for cache coherency and complex memory hierarchies, but have a larger system memory-bandwidth. This is highly beneficial for low compute intensity codes such as atmospheric stencil-based models. However, to efficiently exploit these hybrid architectures, climate models need to be ported and/or redesigned. Within the framework of the Swiss High Performance High Productivity Computing initiative (HP2C) a project to port the COSMO model to hybrid architectures has recently come to and end. The product of these efforts is a version of COSMO with an improved performance on traditional x86-based clusters as well as hybrid architectures with GPUs. We present our redesign and porting approach as well as our experience and lessons learned. Furthermore, we discuss relevant performance benchmarks obtained on the new hybrid Cray XC30 system "Piz Daint" installed at the Swiss National Supercomputing Centre (CSCS), both in terms of time-to-solution as well as energy consumption. We will demonstrate a first set of short cloud-resolving climate simulations at the European-scale using the GPU-enabled COSMO prototype and elaborate our future plans on how to exploit this new model capability.

Reversible Parallel Discrete-Event Execution of Large-scale Epidemic Outbreak Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

The spatial scale, runtime speed and behavioral detail of epidemic outbreak simulations together require the use of large-scale parallel processing. In this paper, an optimistic parallel discrete event execution of a reaction-diffusion simulation model of epidemic outbreaks is presented, with an implementation over themore » $$\\mu$$sik simulator. Rollback support is achieved with the development of a novel reversible model that combines reverse computation with a small amount of incremental state saving. Parallel speedup and other runtime performance metrics of the simulation are tested on a small (8,192-core) Blue Gene / P system, while scalability is demonstrated on 65,536 cores of a large Cray XT5 system. Scenarios representing large population sizes (up to several hundred million individuals in the largest case) are exercised.« less

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

NASA Astrophysics Data System (ADS)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.

Advanced core-analyses for subsurface characterization

NASA Astrophysics Data System (ADS)

Pini, R.

2017-12-01

The heterogeneity of geological formations varies over a wide range of length scales and represents a major challenge for predicting the movement of fluids in the subsurface. Although they are inherently limited in the accessible length-scale, laboratory measurements on reservoir core samples still represent the only way to make direct observations on key transport properties. Yet, properties derived on these samples are of limited use and should be regarded as sample-specific (or `pseudos'), if the presence of sub-core scale heterogeneities is not accounted for in data processing and interpretation. The advent of imaging technology has significantly reshaped the landscape of so-called Special Core Analysis (SCAL) by providing unprecedented insight on rock structure and processes down to the scale of a single pore throat (i.e. the scale at which all reservoir processes operate). Accordingly, improved laboratory workflows are needed that make use of such wealth of information by e.g., referring to the internal structure of the sample and in-situ observations, to obtain accurate parameterisation of both rock- and flow-properties that can be used to populate numerical models. We report here on the development of such workflow for the study of solute mixing and dispersion during single- and multi-phase flows in heterogeneous porous systems through a unique combination of two complementary imaging techniques, namely X-ray Computed Tomography (CT) and Positron Emission Tomography (PET). The experimental protocol is applied to both synthetic and natural porous media, and it integrates (i) macroscopic observations (tracer effluent curves), (ii) sub-core scale parameterisation of rock heterogeneities (e.g., porosity, permeability and capillary pressure), and direct 3D observation of (iii) fluid saturation distribution and (iv) the dynamic spreading of the solute plumes. Suitable mathematical models are applied to reproduce experimental observations, including both 1D and 3D numerical schemes populated with the parameterisation above. While it validates the core-flooding experiments themselves, the calibrated mathematical model represents a key element for extending them to conditions prevalent in the subsurface, which would be otherwise not attainable in the laboratory.

How model and input uncertainty impact maize yield simulations in West Africa

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

2015-02-01

Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

Strut and wall interference on jet-induced ground effects of a STOVL aircraft in hover

NASA Technical Reports Server (NTRS)

Kristy, Michael H.

1995-01-01

A small scale ground effect test rig was used to study the ground plane flow field generated by a STOVL aircraft in hover. The objective of the research was to support NASA-Ames Research Center planning for the Large Scale Powered Model (LSPM) test for the ARPA-sponsored ASTOVL program. Specifically, small scale oil flow visualization studies were conducted to make a relative assessment of the aerodynamic interference of a proposed strut configuration and a wall configuration on the ground plane stagnation line. A simplified flat plate model representative of a generic jet-powered STOVL aircraft was used to simulate the LSPM. Cold air jets were used to simulate both the lift fan and the twin rear engines. Nozzle Pressure Ratios were used that closely represented those used on the LSPM tests. The flow visualization data clearly identified a shift in the stagnation line location for both the strut and the wall configuration. Considering the experimental uncertainty, it was concluded that either the strut configuration o r the wall configuration caused only a minor aerodynamic interference.

Toward irrigation retrieval by combining multi-sensor remote sensing data into a land surface model over a semi-arid region

NASA Astrophysics Data System (ADS)

Malbéteau, Y.; Lopez, O.; Houborg, R.; McCabe, M.

2017-12-01

Agriculture places considerable pressure on water resources, with the relationship between water availability and food production being critical for sustaining population growth. Monitoring water resources is particularly important in arid and semi-arid regions, where irrigation can represent up to 80% of the consumptive uses of water. In this context, it is necessary to optimize on-farm irrigation management by adjusting irrigation to crop water requirements throughout the growing season. However, in situ point measurements are not routinely available over extended areas and may not be representative at the field scale. Remote sensing approaches present as a cost-effective technique for mapping and monitoring broad areas. By taking advantage of multi-sensor remote sensing methodologies, such as those provided by MODIS, Landsat, Sentinel and Cubesats, we propose a new method to estimate irrigation input at pivot-scale. Here we explore the development of crop-water use estimates via these remote sensing data and integrate them into a land surface modeling framework, using a farm in Saudi Arabia as a demonstration of what can be achieved at larger scales.

Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Hicke, Jeffrey A.; Vargas, Rodrigo; Zhao, Shuqing; Chen, Jing; Edburg, Steven L.; Hu, Yueming; Liu, Jinxun; McGuire, A. David; Xiao, Jingfeng; Keane, Robert; Yuan, Wenping; Tang, Jianwu; Luo, Yiqi; Potter, Christopher; Oeding, Jennifer

2011-01-01

Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty

A framework for modeling and optimizing dynamic systems under uncertainty

DOE PAGES

Nicholson, Bethany; Siirola, John

2017-11-11

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

A framework for modeling and optimizing dynamic systems under uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicholson, Bethany; Siirola, John

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

Acoustic Treatment Design Scaling Methods. Volume 1; Overview, Results, and Recommendations

NASA Technical Reports Server (NTRS)

Kraft, R. E.; Yu, J.

1999-01-01

Scale model fan rigs that simulate new generation ultra-high-bypass engines at about 1/5-scale are achieving increased importance as development vehicles for the design of low-noise aircraft engines. Testing at small scale allows the tests to be performed in existing anechoic wind tunnels, which provides an accurate simulation of the important effects of aircraft forward motion on the noise generation. The ability to design, build, and test miniaturized acoustic treatment panels on scale model fan rigs representative of the fullscale engine provides not only a cost-savings, but an opportunity to optimize the treatment by allowing tests of different designs. The primary objective of this study was to develop methods that will allow scale model fan rigs to be successfully used as acoustic treatment design tools. The study focuses on finding methods to extend the upper limit of the frequency range of impedance prediction models and acoustic impedance measurement methods for subscale treatment liner designs, and confirm the predictions by correlation with measured data. This phase of the program had as a goal doubling the upper limit of impedance measurement from 6 kHz to 12 kHz. The program utilizes combined analytical and experimental methods to achieve the objectives.

Using a Large Scale Computational Model to Study the Effect of Longitudinal and Radial Electrical Coupling in the Cochlea

NASA Astrophysics Data System (ADS)

Mistrík, Pavel; Ashmore, Jonathan

2009-02-01

We describe a large scale computational model of electrical current flow in the cochlea which is constructed by a flexible Modified Nodal Analysis algorithm to incorporate electrical components representing hair cells and the intercellular radial and longitudinal current flow. The model is used as a laboratory to study the effects of changing longitudinal gap junctional coupling, and shows the way in which cochlear microphonic spreads and tuning is affected. The process for incorporating mechanical longitudinal coupling and feedback is described. We find a difference in tuning and attenuation depending on whether longitudinal or radial couplings are altered.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

Multiscale pore structure and constitutive models of fine-grained rocks

NASA Astrophysics Data System (ADS)

Heath, J. E.; Dewers, T. A.; Shields, E. A.; Yoon, H.; Milliken, K. L.

2017-12-01

A foundational concept of continuum poromechanics is the representative elementary volume or REV: an amount of material large enough that pore- or grain-scale fluctuations in relevant properties are dissipated to a definable mean, but smaller than length scales of heterogeneity. We determine 2D-equivalent representative elementary areas (REAs) of pore areal fraction of three major types of mudrocks by applying multi-beam scanning electron microscopy (mSEM) to obtain terapixel image mosaics. Image analysis obtains pore areal fraction and pore size and shape as a function of progressively larger measurement areas. Using backscattering imaging and mSEM data, pores are identified by the components within which they occur, such as in organics or the clastic matrix. We correlate pore areal fraction with nano-indentation, micropillar compression, and axysimmetic testing at multiple length scales on a terrigenous-argillaceous mudrock sample. The combined data set is used to: investigate representative elementary volumes (and areas for the 2D images); determine if scale separation occurs; and determine if transport and mechanical properties at a given length scale can be statistically defined. Clear scale separation occurs between REAs and observable heterogeneity in two of the samples. A highly-laminated sample exhibits fine-scale heterogeneity and an overlapping in scales, in which case typical continuum assumptions on statistical variability may break down. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Leaf hydraulics II: vascularized tissues.

PubMed

Rockwell, Fulton E; Holbrook, N Michele; Stroock, Abraham D

2014-01-07

Current models of leaf hydration employ an Ohm's law analogy of the leaf as an ideal capacitor, neglecting the resistance to flow between cells, or treat the leaf as a plane sheet with a source of water at fixed potential filling the mid-plane, neglecting the discrete placement of veins as well as their resistance. We develop a model of leaf hydration that considers the average conductance of the vascular network to a representative areole (region bounded by the vascular network), and represent the volume of tissue within the areole as a poroelastic composite of cells and air spaces. Solutions to the 3D flow problem are found by numerical simulation, and these results are then compared to 1D models with exact solutions for a range of leaf geometries, based on a survey of temperate woody plants. We then show that the hydration times given by these solutions are well approximated by a sum of the ideal capacitor and plane sheet times, representing the time for transport through the vasculature and tissue respectively. We then develop scaling factors relating this approximate solution to the 3D model, and examine the dependence of these scaling factors on leaf geometry. Finally, we apply a similar strategy to reduce the dimensions of the steady state problem, in the context of peristomatal transpiration, and consider the relation of transpirational gradients to equilibrium leaf water potential measurements. © 2013 Published by Elsevier Ltd. All rights reserved.

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

Multi-scale Modeling of Arctic Clouds

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

NASA Astrophysics Data System (ADS)

Dickson, N. C.; Gierens, K. M.; Rogers, H. L.; Jones, R. L.

2010-02-01

The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal path length through ISSR as observed by MOZAIC aircraft is 150 km (±250 km). The average vertical thickness of ISS layers is 600-800 m (±575 m) but layers ranging from 25 m to 3000 m have been observed, with up to one third of ISS layers thought to be less than 100 m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Methods for Scaling Icing Test Conditions

NASA Technical Reports Server (NTRS)

Anderson, David N.

1995-01-01

This report presents the results of tests at NASA Lewis to evaluate several methods to establish suitable alternative test conditions when the test facility limits the model size or operating conditions. The first method was proposed by Olsen. It can be applied when full-size models are tested and all the desired test conditions except liquid-water content can be obtained in the facility. The other two methods discussed are: a modification of the French scaling law and the AEDC scaling method. Icing tests were made with cylinders at both reference and scaled conditions representing mixed and glaze ice in the NASA Lewis Icing Research Tunnel. Reference and scale ice shapes were compared to evaluate each method. The Olsen method was tested with liquid-water content varying from 1.3 to .8 g/m(exp3). Over this range, ice shapes produced using the Olsen method were unchanged. The modified French and AEDC methods produced scaled ice shapes which approximated the reference shapes when model size was reduced to half the reference size for the glaze-ice cases tested.

Seasonal Distributions of Global Ocean Chlorophyll and Nutrients: Analysis with a Coupled Ocean General Circulation Biogeochemical, and Radiative Model

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

1999-01-01

A coupled general ocean circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. The model is driven by climatological meteorological conditions, cloud cover, and sea surface temperature. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chorophytes, and picoplankton) and three nutrient groups (nitrate, ammonium, and silicate). Phytoplankton groups are initialized as homogeneous fields horizontally and vertically, and allowed to distribute themselves according to the prevailing conditions. Basin-scale model chlorophyll results are in very good agreement with CZCS pigments in virtually every global region. Seasonal variability observed in the CZCS is also well represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are also in good conformance, although occasional departures are apparent. Agreement of nitrate distributions with in situ data is even better, including seasonal dynamics, except for the equatorial Atlantic. The good agreement of the model with satellite and in situ data sources indicates that the model dynamics realistically simulate phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization, and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Assessing the utility of FIB-SEM images for shale digital rock physics

NASA Astrophysics Data System (ADS)

Kelly, Shaina; El-Sobky, Hesham; Torres-Verdín, Carlos; Balhoff, Matthew T.

2016-09-01

Shales and other unconventional or low permeability (tight) reservoirs house vast quantities of hydrocarbons, often demonstrate considerable water uptake, and are potential repositories for fluid sequestration. The pore-scale topology and fluid transport mechanisms within these nanoporous sedimentary rocks remain to be fully understood. Image-informed pore-scale models are useful tools for studying porous media: a debated question in shale pore-scale petrophysics is whether there is a representative elementary volume (REV) for shale models? Furthermore, if an REV exists, how does it differ among petrophysical properties? We obtain three dimensional (3D) models of the topology of microscale shale volumes from image analysis of focused ion beam-scanning electron microscope (FIB-SEM) image stacks and investigate the utility of these models as a potential REV for shale. The scope of data used in this work includes multiple local groups of neighboring FIB-SEM images of different microscale sizes, corresponding core-scale (milli- and centimeters) laboratory data, and, for comparison, series of two-dimensional (2D) cross sections from broad ion beam SEM images (BIB-SEM), which capture a larger microscale field of view than the FIB-SEM images; this array of data is larger than the majority of investigations with FIB-SEM-derived microscale models of shale. Properties such as porosity, organic matter content, and pore connectivity are extracted from each model. Assessments of permeability with single phase, pressure-driven flow simulations are performed in the connected pore space of the models using the lattice-Boltzmann method. Calculated petrophysical properties are compared to those of neighboring FIB-SEM images and to core-scale measurements of the sample associated with the FIB-SEM sites. Results indicate that FIB-SEM images below ∼5000 μm3 volume (the largest volume analyzed) are not a suitable REV for shale permeability and pore-scale networks; i.e. field of view is compromised at the expense of detailed, but often unconnected, nanopore morphology. Further, we find that it is necessary to acquire several local FIB-SEM or BIB-SEM images and correlate their extracted geometric properties to improve the likelihood of achieving representative values of porosity and organic matter volume. Our work indicates that FIB-SEM images of microscale volumes of shale are a qualitative tool for petrophysical and transport analysis. Finally, we offer alternatives for quantitative pore-scale assessments of shale.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

2017-04-01

The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.

Analog Microcontroller Model for an Energy Harvesting Round Counter

DTIC Science & Technology

2012-07-01

densities representing the duration of ≥ for all scaled piezo ................................7 1 INTRODUCTION An accurate count...limited surface area available for mounting piezos on the gun system. Figure 1. Equivalent circuit model for a piezoelectric transducer...circuit model for the linear I-V relationships is parallel combination of six stages, each of which is comprised of a series combination of a resistor , DC

Assessment Engineering Task Model Maps, Task Models and Templates as a New Way to Develop and Implement Test Specifications

ERIC Educational Resources Information Center

Luecht, Richard M.

2013-01-01

Assessment engineering is a new way to design and implement scalable, sustainable and ideally lower-cost solutions to the complexities of designing and developing tests. It represents a merger of sorts between cognitive task modeling and engineering design principles--a merger that requires some new thinking about the nature of score scales, item…

Measuring potential predictors of burnout and engagement among young veterinary professionals; construction of a customised questionnaire (the Vet-DRQ).

PubMed

Mastenbroek, N J J M; Demerouti, E; van Beukelen, P; Muijtjens, A M M; Scherpbier, A J J A; Jaarsma, A D C

2014-02-15

The Job Demands-Resources model (JD-R model) was used as the theoretical basis of a tailormade questionnaire to measure the psychosocial work environment and personal resources of recently graduated veterinary professionals. According to the JD-R model, two broad categories of work characteristics that determine employee wellbeing can be distinguished: job demands and job resources. Recently, the JD-R model has been expanded by integrating personal resource measures into the model. Three semistructured group interviews with veterinarians active in different work domains were conducted to identify relevant job demands, job resources and personal resources. These demands and resources were organised in themes (constructs). For measurement purposes, a set of questions ('a priori scale') was selected from the literature for each theme. The full set of a priori scales was included in a questionnaire that was administered to 1760 veterinary professionals. Exploratory factor analysis and reliability analysis were conducted to arrive at the final set of validated scales (final scales). 860 veterinarians (73 per cent females) participated. The final set of scales consisted of seven job demands scales (32 items), nine job resources scales (41 items), and six personal resources scales (26 items) which were considered to represent the most relevant potential predictors of work-related wellbeing in this occupational group. The procedure resulted in a tailormade questionnaire: the Veterinary Job Demands and Resources Questionnaire (Vet-DRQ). The use of valid theory and validated scales enhances opportunities for comparative national and international research.

Object-based class modelling for multi-scale riparian forest habitat mapping

NASA Astrophysics Data System (ADS)

Strasser, Thomas; Lang, Stefan

2015-05-01

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

A study of gradient strengthening based on a finite-deformation gradient crystal-plasticity model

NASA Astrophysics Data System (ADS)

Pouriayevali, Habib; Xu, Bai-Xiang

2017-11-01

A comprehensive study on a finite-deformation gradient crystal-plasticity model which has been derived based on Gurtin's framework (Int J Plast 24:702-725, 2008) is carried out here. This systematic investigation on the different roles of governing components of the model represents the strength of this framework in the prediction of a wide range of hardening behaviors as well as rate-dependent and scale-variation responses in a single crystal. The model is represented in the reference configuration for the purpose of numerical implementation and then implemented in the FEM software ABAQUS via a user-defined subroutine (UEL). Furthermore, a function of accumulation rates of dislocations is employed and viewed as a measure of formation of short-range interactions. Our simulation results reveal that the dissipative gradient strengthening can be identified as a source of isotropic-hardening behavior, which may represent the effect of irrecoverable work introduced by Gurtin and Ohno (J Mech Phys Solids 59:320-343, 2011). Here, the variation of size dependency at different magnitude of a rate-sensitivity parameter is also discussed. Moreover, an observation of effect of a distinctive feature in the model which explains the effect of distortion of crystal lattice in the reference configuration is reported in this study for the first time. In addition, plastic flows in predefined slip systems and expansion of accumulation of GNDs are distinctly observed in varying scales and under different loading conditions.

An Objective Evaluation of Mass Scaling Techniques Utilizing Computational Human Body Finite Element Models.

PubMed

Davis, Matthew L; Scott Gayzik, F

2016-10-01

Biofidelity response corridors developed from post-mortem human subjects are commonly used in the design and validation of anthropomorphic test devices and computational human body models (HBMs). Typically, corridors are derived from a diverse pool of biomechanical data and later normalized to a target body habitus. The objective of this study was to use morphed computational HBMs to compare the ability of various scaling techniques to scale response data from a reference to a target anthropometry. HBMs are ideally suited for this type of study since they uphold the assumptions of equal density and modulus that are implicit in scaling method development. In total, six scaling procedures were evaluated, four from the literature (equal-stress equal-velocity, ESEV, and three variations of impulse momentum) and two which are introduced in the paper (ESEV using a ratio of effective masses, ESEV-EffMass, and a kinetic energy approach). In total, 24 simulations were performed, representing both pendulum and full body impacts for three representative HBMs. These simulations were quantitatively compared using the International Organization for Standardization (ISO) ISO-TS18571 standard. Based on these results, ESEV-EffMass achieved the highest overall similarity score (indicating that it is most proficient at scaling a reference response to a target). Additionally, ESEV was found to perform poorly for two degree-of-freedom (DOF) systems. However, the results also indicated that no single technique was clearly the most appropriate for all scenarios.

Local-Scale Simulations of Nucleate Boiling on Micrometer Featured Surfaces: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-08-03

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Local-Scale Simulations of Nucleate Boiling on Micrometer-Featured Surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-07-12

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

Modeling fast and slow earthquakes at various scales

PubMed Central

IDE, Satoshi

2014-01-01

Earthquake sources represent dynamic rupture within rocky materials at depth and often can be modeled as propagating shear slip controlled by friction laws. These laws provide boundary conditions on fault planes embedded in elastic media. Recent developments in observation networks, laboratory experiments, and methods of data analysis have expanded our knowledge of the physics of earthquakes. Newly discovered slow earthquakes are qualitatively different phenomena from ordinary fast earthquakes and provide independent information on slow deformation at depth. Many numerical simulations have been carried out to model both fast and slow earthquakes, but problems remain, especially with scaling laws. Some mechanisms are required to explain the power-law nature of earthquake rupture and the lack of characteristic length. Conceptual models that include a hierarchical structure over a wide range of scales would be helpful for characterizing diverse behavior in different seismic regions and for improving probabilistic forecasts of earthquakes. PMID:25311138

Modeling fast and slow earthquakes at various scales.

PubMed

Ide, Satoshi

2014-01-01

Earthquake sources represent dynamic rupture within rocky materials at depth and often can be modeled as propagating shear slip controlled by friction laws. These laws provide boundary conditions on fault planes embedded in elastic media. Recent developments in observation networks, laboratory experiments, and methods of data analysis have expanded our knowledge of the physics of earthquakes. Newly discovered slow earthquakes are qualitatively different phenomena from ordinary fast earthquakes and provide independent information on slow deformation at depth. Many numerical simulations have been carried out to model both fast and slow earthquakes, but problems remain, especially with scaling laws. Some mechanisms are required to explain the power-law nature of earthquake rupture and the lack of characteristic length. Conceptual models that include a hierarchical structure over a wide range of scales would be helpful for characterizing diverse behavior in different seismic regions and for improving probabilistic forecasts of earthquakes.

Quantitative framework for preferential flow initiation and partitioning

USGS Publications Warehouse

Nimmo, John R.

2016-01-01

A model for preferential flow in macropores is based on the short-range spatial distribution of soil matrix infiltrability. It uses elementary areas at two different scales. One is the traditional representative elementary area (REA), which includes a sufficient heterogeneity to typify larger areas, as for measuring field-scale infiltrability. The other, called an elementary matrix area (EMA), is smaller, but large enough to represent the local infiltrability of soil matrix material, between macropores. When water is applied to the land surface, each EMA absorbs water up to the rate of its matrix infiltrability. Excess water flows into a macropore, becoming preferential flow. The land surface then can be represented by a mesoscale (EMA-scale) distribution of matrix infiltrabilities. Total preferential flow at a given depth is the sum of contributions from all EMAs. Applying the model, one case study with multi-year field measurements of both preferential and diffuse fluxes at a specific depth was used to obtain parameter values by inverse calculation. The results quantify the preferential–diffuse partition of flow from individual storms that differed in rainfall amount, intensity, antecedent soil water, and other factors. Another case study provided measured values of matrix infiltrability to estimate parameter values for comparison and illustrative predictions. These examples give a self-consistent picture from the combination of parameter values, directions of sensitivities, and magnitudes of differences caused by different variables. One major practical use of this model is to calculate the dependence of preferential flow on climate-related factors, such as varying soil wetness and rainfall intensity.

Open and scalable analytics of large Earth observation datasets: From scenes to multidimensional arrays using SciDB and GDAL

NASA Astrophysics Data System (ADS)

Appel, Marius; Lahn, Florian; Buytaert, Wouter; Pebesma, Edzer

2018-04-01

Earth observation (EO) datasets are commonly provided as collection of scenes, where individual scenes represent a temporal snapshot and cover a particular region on the Earth's surface. Using these data in complex spatiotemporal modeling becomes difficult as soon as data volumes exceed a certain capacity or analyses include many scenes, which may spatially overlap and may have been recorded at different dates. In order to facilitate analytics on large EO datasets, we combine and extend the geospatial data abstraction library (GDAL) and the array-based data management and analytics system SciDB. We present an approach to automatically convert collections of scenes to multidimensional arrays and use SciDB to scale computationally intensive analytics. We evaluate the approach in three study cases on national scale land use change monitoring with Landsat imagery, global empirical orthogonal function analysis of daily precipitation, and combining historical climate model projections with satellite-based observations. Results indicate that the approach can be used to represent various EO datasets and that analyses in SciDB scale well with available computational resources. To simplify analyses of higher-dimensional datasets as from climate model output, however, a generalization of the GDAL data model might be needed. All parts of this work have been implemented as open-source software and we discuss how this may facilitate open and reproducible EO analyses.

Improving Representation of Convective Transport for Scale-Aware Parameterization, Part II: Analysis of Cloud-Resolving Model Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.

2015-04-27

Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the mid-latitude continental and the tropical regions are conducted and evaluated, we examine the scale-dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraftmore » eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of 38 mid-latitude continental convection. We show that the single updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as 3 updrafts can account for the internal variability of updrafts well. Based on evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Conformal standard model, leptogenesis, and dark matter

NASA Astrophysics Data System (ADS)

Lewandowski, Adrian; Meissner, Krzysztof A.; Nicolai, Hermann

2018-02-01

The conformal standard model is a minimal extension of the Standard Model (SM) of particle physics based on the assumed absence of large intermediate scales between the TeV scale and the Planck scale, which incorporates only right-chiral neutrinos and a new complex scalar in addition to the usual SM degrees of freedom, but no other features such as supersymmetric partners. In this paper, we present a comprehensive quantitative analysis of this model, and show that all outstanding issues of particle physics proper can in principle be solved "in one go" within this framework. This includes in particular the stabilization of the electroweak scale, "minimal" leptogenesis and the explanation of dark matter, with a small mass and very weakly interacting Majoron as the dark matter candidate (for which we propose to use the name "minoron"). The main testable prediction of the model is a new and almost sterile scalar boson that would manifest itself as a narrow resonance in the TeV region. We give a representative range of parameter values consistent with our assumptions and with observation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Na; Zhang, Peng; Kang, Wei

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less

CONSISTENT SCALING LAWS IN ANELASTIC SPHERICAL SHELL DYNAMOS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yadav, Rakesh K.; Gastine, Thomas; Christensen, Ulrich R.

2013-09-01

Numerical dynamo models always employ parameter values that differ by orders of magnitude from the values expected in natural objects. However, such models have been successful in qualitatively reproducing properties of planetary and stellar dynamos. This qualitative agreement fuels the idea that both numerical models and astrophysical objects may operate in the same asymptotic regime of dynamics. This can be tested by exploring the scaling behavior of the models. For convection-driven incompressible spherical shell dynamos with constant material properties, scaling laws had been established previously that relate flow velocity and magnetic field strength to the available power. Here we analyzemore » 273 direct numerical simulations using the anelastic approximation, involving also cases with radius-dependent magnetic, thermal, and viscous diffusivities. These better represent conditions in gas giant planets and low-mass stars compared to Boussinesq models. Our study provides strong support for the hypothesis that both mean velocity and mean magnetic field strength scale as a function of the power generated by buoyancy forces in the same way for a wide range of conditions.« less

Forecast model for great earthquakes at the Nankai Trough subduction zone

USGS Publications Warehouse

Stuart, W.D.

1988-01-01

An earthquake instability model is formulated for recurring great earthquakes at the Nankai Trough subduction zone in southwest Japan. The model is quasistatic, two-dimensional, and has a displacement and velocity dependent constitutive law applied at the fault plane. A constant rate of fault slip at depth represents forcing due to relative motion of the Philippine Sea and Eurasian plates. The model simulates fault slip and stress for all parts of repeated earthquake cycles, including post-, inter-, pre- and coseismic stages. Calculated ground uplift is in agreement with most of the main features of elevation changes observed before and after the M=8.1 1946 Nankaido earthquake. In model simulations, accelerating fault slip has two time-scales. The first time-scale is several years long and is interpreted as an intermediate-term precursor. The second time-scale is a few days long and is interpreted as a short-term precursor. Accelerating fault slip on both time-scales causes anomalous elevation changes of the ground surface over the fault plane of 100 mm or less within 50 km of the fault trace. ?? 1988 Birkha??user Verlag.

Hybrid reduced order modeling for assembly calculations

DOE PAGES

Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; ...

2015-08-14

While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the usemore » of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.« less

Dynamics of coupled human-landscape systems

NASA Astrophysics Data System (ADS)

Werner, B. T.; McNamara, D. E.

2007-11-01

A preliminary dynamical analysis of landscapes and humans as hierarchical complex systems suggests that strong coupling between the two that spreads to become regionally or globally pervasive should be focused at multi-year to decadal time scales. At these scales, landscape dynamics is dominated by water, sediment and biological routing mediated by fluvial, oceanic, atmospheric processes and human dynamics is dominated by simplifying, profit-maximizing market forces and political action based on projection of economic effect. Also at these scales, landscapes impact humans through patterns of natural disasters and trends such as sea level rise; humans impact landscapes by the effect of economic activity and changes meant to mitigate natural disasters and longer term trends. Based on this analysis, human-landscape coupled systems can be modeled using heterogeneous agents employing prediction models to determine actions to represent the nonlinear behavior of economic and political systems and rule-based routing algorithms to represent landscape processes. A cellular model for the development of New Orleans illustrates this approach, with routing algorithms for river and hurricane-storm surge determining flood extent, five markets (home, labor, hotel, tourism and port services) connecting seven types of economic agents (home buyers/laborers, home developers, hotel owners/ employers, hotel developers, tourists, port services developer and port services owners/employers), building of levees or a river spillway by political agents and damage to homes, hotels or port services within cells determined by the passage or depth of flood waters. The model reproduces historical aspects of New Orleans economic development and levee construction and the filtering of frequent small-scale floods at the expense of large disasters.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses.

PubMed

Imam, Saheed; Schäuble, Sascha; Valenzuela, Jacob; López García de Lomana, Adrián; Carter, Warren; Price, Nathan D; Baliga, Nitin S

2015-12-01

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

AgMIP 1.5°C Assessment: Mitigation and Adaptation at Coordinated Global and Regional Scales

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2016-12-01

The AgMIP 1.5°C Coordinated Global and Regional Integrated Assessments of Climate Change and Food Security (AgMIP 1.5 CGRA) is linking site-based crop and livestock models with similar models run on global grids, and then links these biophysical components with economics models and nutrition metrics at regional and global scales. The AgMIP 1.5 CGRA assessment brings together experts in climate, crop, livestock, economics, nutrition, and food security to define the 1.5°C Protocols and guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including socioeconomic development (Shared Socioeconomic Pathways), greenhouse gas concentrations (Representative Concentration Pathways), and specific pathways of agricultural sector development (Representative Agricultural Pathways). Shared Climate Policy Assumptions will be extended to provide additional agricultural detail on mitigation and adaptation strategies. The multi-model, multi-disciplinary, multi-scale integrated assessment framework is using scenarios of economic development, adaptation, mitigation, food policy, and food security. These coordinated assessments are grounded in the expertise of AgMIP partners around the world, leading to more consistent results and messages for stakeholders, policymakers, and the scientific community. The early inclusion of nutrition and food security experts has helped to ensure that assessment outputs include important metrics upon which investment and policy decisions may be based. The CGRA builds upon existing AgMIP research groups (e.g., the AgMIP Wheat Team and the AgMIP Global Gridded Crop Modeling Initiative; GGCMI) and regional programs (e.g., AgMIP Regional Teams in Sub-Saharan Africa and South Asia), with new protocols for cross-scale and cross-disciplinary linkages to ensure the propagation of expert judgment and consistent assumptions.

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

DOE PAGES

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; ...

2015-06-19

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functionsmore » for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.« less

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses

DOE PAGES

Imam, Saheed; Schäuble, Sascha; Valenzuela, Jacob; ...

2015-10-20

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting formore » 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.« less

A Fundamental Test for Galaxy Formation Models: Matching the Lyman-α Absorption Profiles of Galactic Halos Over Three Decades in Distance

NASA Astrophysics Data System (ADS)

Sorini, Daniele; Oñorbe, José; Hennawi, Joseph F.; Lukić, Zarija

2018-06-01

Galaxy formation depends critically on the physical state of gas in the circumgalactic medium (CGM) and its interface with the intergalactic medium (IGM), determined by the complex interplay between inflow from the IGM and outflows from supernovae and/or AGN feedback. The average Lyα absorption profile around galactic halos represents a powerful tool to probe their gaseous environments. We compare predictions from Illustris and Nyx hydrodynamical simulations with the observed absorption around foreground quasars, damped Lyα systems, and Lyman-break galaxies. We show how large-scale BOSS and small-scale quasar pair measurements can be combined to precisely constrain the absorption profile over three decades in transverse distance 20 {kpc}≲ b≲ 20 {Mpc}. Far from galaxies, ≳ 2 {Mpc}, the simulations converge to the same profile and provide a reasonable match to the observations. This asymptotic agreement arises because the ΛCDM model successfully describes the ambient IGM and represents a critical advantage of studying the mean absorption profile. However, significant differences between the simulations, and between simulations and observations, are present on scales 20 {kpc}≲ b≲ 2 {Mpc}, illustrating the challenges of accurately modeling and resolving galaxy formation physics. It is noteworthy that these differences are observed as far out as ∼ 2 {Mpc}, indicating that the “sphere of influence” of galaxies could extend to approximately ∼7 times the halo virial radius. Current observations are very precise on these scales and can thus strongly discriminate between different galaxy formation models. We demonstrate that the Lyα absorption profile is primarily sensitive to the underlying temperature–density relationship of diffuse gas around galaxies, and argue that it thus provides a fundamental test of galaxy formation models.

Equation-free multiscale computation: algorithms and applications.

PubMed

Kevrekidis, Ioannis G; Samaey, Giovanni

2009-01-01

In traditional physicochemical modeling, one derives evolution equations at the (macroscopic, coarse) scale of interest; these are used to perform a variety of tasks (simulation, bifurcation analysis, optimization) using an arsenal of analytical and numerical techniques. For many complex systems, however, although one observes evolution at a macroscopic scale of interest, accurate models are only given at a more detailed (fine-scale, microscopic) level of description (e.g., lattice Boltzmann, kinetic Monte Carlo, molecular dynamics). Here, we review a framework for computer-aided multiscale analysis, which enables macroscopic computational tasks (over extended spatiotemporal scales) using only appropriately initialized microscopic simulation on short time and length scales. The methodology bypasses the derivation of macroscopic evolution equations when these equations conceptually exist but are not available in closed form-hence the term equation-free. We selectively discuss basic algorithms and underlying principles and illustrate the approach through representative applications. We also discuss potential difficulties and outline areas for future research.

Modes and emergent time scales of embayed beach dynamics

NASA Astrophysics Data System (ADS)

Ratliff, Katherine M.; Murray, A. Brad

2014-10-01

In this study, we use a simple numerical model (the Coastline Evolution Model) to explore alongshore transport-driven shoreline dynamics within generalized embayed beaches (neglecting cross-shore effects). Using principal component analysis (PCA), we identify two primary orthogonal modes of shoreline behavior that describe shoreline variation about its unchanging mean position: the rotation mode, which has been previously identified and describes changes in the mean shoreline orientation, and a newly identified breathing mode, which represents changes in shoreline curvature. Wavelet analysis of the PCA mode time series reveals characteristic time scales of these modes (typically years to decades) that emerge within even a statistically constant white-noise wave climate (without changes in external forcing), suggesting that these time scales can arise from internal system dynamics. The time scales of both modes increase linearly with shoreface depth, suggesting that the embayed beach sediment transport dynamics exhibit a diffusive scaling.

On representation of temporal variability in electricity capacity planning models

DOE PAGES

Merrick, James H.

2016-08-23

This study systematically investigates how to represent intra-annual temporal variability in models of optimum electricity capacity investment. Inappropriate aggregation of temporal resolution can introduce substantial error into model outputs and associated economic insight. The mechanisms underlying the introduction of this error are shown. How many representative periods are needed to fully capture the variability is then investigated. For a sample dataset, a scenario-robust aggregation of hourly (8760) resolution is possible in the order of 10 representative hours when electricity demand is the only source of variability. The inclusion of wind and solar supply variability increases the resolution of the robustmore » aggregation to the order of 1000. A similar scale of expansion is shown for representative days and weeks. These concepts can be applied to any such temporal dataset, providing, at the least, a benchmark that any other aggregation method can aim to emulate. Finally, how prior information about peak pricing hours can potentially reduce resolution further is also discussed.« less

On representation of temporal variability in electricity capacity planning models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merrick, James H.

This study systematically investigates how to represent intra-annual temporal variability in models of optimum electricity capacity investment. Inappropriate aggregation of temporal resolution can introduce substantial error into model outputs and associated economic insight. The mechanisms underlying the introduction of this error are shown. How many representative periods are needed to fully capture the variability is then investigated. For a sample dataset, a scenario-robust aggregation of hourly (8760) resolution is possible in the order of 10 representative hours when electricity demand is the only source of variability. The inclusion of wind and solar supply variability increases the resolution of the robustmore » aggregation to the order of 1000. A similar scale of expansion is shown for representative days and weeks. These concepts can be applied to any such temporal dataset, providing, at the least, a benchmark that any other aggregation method can aim to emulate. Finally, how prior information about peak pricing hours can potentially reduce resolution further is also discussed.« less

High Resolution Modelling of the Congo River's Multi-Threaded Main Stem Hydraulics

NASA Astrophysics Data System (ADS)

Carr, A. B.; Trigg, M.; Tshimanga, R.; Neal, J. C.; Borman, D.; Smith, M. W.; Bola, G.; Kabuya, P.; Mushie, C. A.; Tschumbu, C. L.

2017-12-01

We present the results of a summer 2017 field campaign by members of the Congo River users Hydraulics and Morphology (CRuHM) project, and a subsequent reach-scale hydraulic modelling study on the Congo's main stem. Sonar bathymetry, ADCP transects, and water surface elevation data have been collected along the Congo's heavily multi-threaded middle reach, which exhibits complex in-channel hydraulic processes that are not well understood. To model the entire basin's hydrodynamics, these in-channel hydraulic processes must be parameterised since it is not computationally feasible to represent them explicitly. Furthermore, recent research suggests that relative to other large global rivers, in-channel flows on the Congo represent a relatively large proportion of total flow through the river-floodplain system. We therefore regard sufficient representation of in-channel hydraulic processes as a Congo River hydrodynamic research priority. To enable explicit representation of in-channel hydraulics, we develop a reach-scale (70 km), high resolution hydraulic model. Simulation of flow through individual channel threads provides new information on flow depths and velocities, and will be used to inform the parameterisation of a broader basin-scale hydrodynamic model. The basin-scale model will ultimately be used to investigate floodplain fluxes, flood wave attenuation, and the impact of future hydrological change scenarios on basin hydrodynamics. This presentation will focus on the methodology we use to develop a reach-scale bathymetric DEM. The bathymetry of only a small proportion of channel threads can realistically be captured, necessitating some estimation of the bathymetry of channels not surveyed. We explore different approaches to this bathymetry estimation, and the extent to which it influences hydraulic model predictions. The CRuHM project is a consortium comprising the Universities of Kinshasa, Rhodes, Dar es Salaam, Bristol, and Leeds, and is funded by Royal Society-DFID Africa Capacity Building Initiative. The project aims to strengthen institutional research capacity and advance our understanding of the hydrology, hydrodynamics and sediment dynamics of the world's second largest river system through fieldwork and development of numerical models.

Regional Climate Change across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

NASA Astrophysics Data System (ADS)

Otte, T. L.; Nolte, C. G.; Otte, M. J.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2011-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. Preliminary results from downscaling NASA/GISS ModelE simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model will be used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0.

A study of two subgrid-scale models and their effects on wake breakdown behind a wind turbine in uniform inflow

NASA Astrophysics Data System (ADS)

Martinez, Luis; Meneveau, Charles

2014-11-01

Large Eddy Simulations (LES) of the flow past a single wind turbine with uniform inflow have been performed. A goal of the simulations is to compare two turbulence subgrid-scale models and their effects in predicting the initial breakdown, transition and evolution of the wake behind the turbine. Prior works have often observed negligible sensitivities to subgrid-scale models. The flow is modeled using an in-house LES with pseudo-spectral discretization in horizontal planes and centered finite differencing in the vertical direction. Turbines are represented using the actuator line model. We compare the standard constant-coefficient Smagorinsky subgrid-scale model with the Lagrangian Scale Dependent Dynamic model (LSDM). The LSDM model predicts faster transition to turbulence in the wake, whereas the standard Smagorinsky model predicts significantly delayed transition. The specified Smagorinsky coefficient is larger than the dynamic one on average, increasing diffusion thus delaying transition. A second goal is to compare the resulting near-blade properties such as local aerodynamic forces from the LES with Blade Element Momentum Theory. Results will also be compared with those of the SOWFA package, the wind energy CFD framework from NREL. This work is supported by NSF (IGERT and IIA-1243482) and computations use XSEDE resources, and has benefitted from interactions with Dr. M. Churchfield of NREL.

Spatial structures of stream and hillslope drainage networks following gully erosion after wildfire

USGS Publications Warehouse

Moody, J.A.; Kinner, D.A.

2006-01-01

The drainage networks of catchment areas burned by wildfire were analysed at several scales. The smallest scale (1-1000 m2) representative of hillslopes, and the small scale (1000 m2 to 1 km2), representative of small catchments, were characterized by the analysis of field measurements. The large scale (1-1000 km2), representative of perennial stream networks, was derived from a 30-m digital elevation model and analysed by computer analysis. Scaling laws used to describe large-scale drainage networks could be extrapolated to the small scale but could not describe the smallest scale of drainage structures observed in the hillslope region. The hillslope drainage network appears to have a second-order effect that reduces the number of order 1 and order 2 streams predicted by the large-scale channel structure. This network comprises two spatial patterns of rills with width-to-depth ratios typically less than 10. One pattern is parallel rills draining nearly planar hillslope surfaces, and the other pattern is three to six converging rills draining the critical source area uphill from an order 1 channel head. The magnitude of this critical area depends on infiltration, hillslope roughness and critical shear stress for erosion of sediment, all of which can be substantially altered by wildfire. Order 1 and 2 streams were found to constitute the interface region, which is altered by a disturbance, like wildfire, from subtle unchannelized drainages in unburned catchments to incised drainages. These drainages are characterized by gullies also with width-to-depth ratios typically less than 10 in burned catchments. The regions (hillslope, interface and chanel) had different drainage network structures to collect and transfer water and sediment. Copyright ?? 2005 John Wiley & Sons, Ltd.

An individual-based model of rabbit viral haemorrhagic disease on European wild rabbits (Oryctolagus cuniculus)

USGS Publications Warehouse

Fa, John E.; Sharples, Colin M.; Bell, Diana J.; DeAngelis, Donald L.

2001-01-01

We developed an individual-based model of Rabbit Viral Hemorrhagic Disease (RVHD) for European wild rabbits (Oryctolagus cuniculus L.), representing up to 1000 rabbits in four hectares. Model output for productivity and recruitment matched published values. The disease was density-dependent and virulence affected outcome. Strains that caused death after several days produced greater overall mortality than strains in which rabbits either died or recovered very quickly. Disease effect also depended on time of year. We also elaborated a larger scale model representing 25 km2 and 100,000+ rabbits, split into a number of grid-squares. This was a more traditional model that did not represent individual rabbits, but employed a system of dynamic equations for each grid-square. Disease spread depended on probability of transmission between neighboring grid-squares. Potential recovery from a major population crash caused by the disease relied on disease virulence and frequency of recurrence. The model's dependence on probability of disease transmission between grid-squares suggests the way that the model represents the spatial distribution of the population affects simulation. Although data on RVHD in Europe are lacking, our models provide a basis for describing the disease in realistic detail and for assessing influence of various social and spatial factors on spread.

A hybrid approach to simulation of electron transfer in complex molecular systems

PubMed Central

Kubař, Tomáš; Elstner, Marcus

2013-01-01

Electron transfer (ET) reactions in biomolecular systems represent an important class of processes at the interface of physics, chemistry and biology. The theoretical description of these reactions constitutes a huge challenge because extensive systems require a quantum-mechanical treatment and a broad range of time scales are involved. Thus, only small model systems may be investigated with the modern density functional theory techniques combined with non-adiabatic dynamics algorithms. On the other hand, model calculations based on Marcus's seminal theory describe the ET involving several assumptions that may not always be met. We review a multi-scale method that combines a non-adiabatic propagation scheme and a linear scaling quantum-chemical method with a molecular mechanics force field in such a way that an unbiased description of the dynamics of excess electron is achieved and the number of degrees of freedom is reduced effectively at the same time. ET reactions taking nanoseconds in systems with hundreds of quantum atoms can be simulated, bridging the gap between non-adiabatic ab initio simulations and model approaches such as the Marcus theory. A major recent application is hole transfer in DNA, which represents an archetypal ET reaction in a polarizable medium. Ongoing work focuses on hole transfer in proteins, peptides and organic semi-conductors. PMID:23883952

Low-dimensional representations of exact coherent states of the Navier-Stokes equations from the resolvent model of wall turbulence.

PubMed

Sharma, Ati S; Moarref, Rashad; McKeon, Beverley J; Park, Jae Sung; Graham, Michael D; Willis, Ashley P

2016-02-01

We report that many exact invariant solutions of the Navier-Stokes equations for both pipe and channel flows are well represented by just a few modes of the model of McKeon and Sharma [J. Fluid Mech. 658, 336 (2010)]. This model provides modes that act as a basis to decompose the velocity field, ordered by their amplitude of response to forcing arising from the interaction between scales. The model was originally derived from the Navier-Stokes equations to represent turbulent flows and has been used to explain coherent structure and to predict turbulent statistics. This establishes a surprising new link between the two distinct approaches to understanding turbulence.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR-Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land-surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5-deg initial / boundary condition data. LIS will provide much higher-resolution land-surface data at a scale more representative to regional WRF configuration. Future implementation of real-time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.

Low-dimensional representations of exact coherent states of the Navier-Stokes equations from the resolvent model of wall turbulence

NASA Astrophysics Data System (ADS)

Sharma, Ati S.; Moarref, Rashad; McKeon, Beverley J.; Park, Jae Sung; Graham, Michael D.; Willis, Ashley P.

2016-02-01

We report that many exact invariant solutions of the Navier-Stokes equations for both pipe and channel flows are well represented by just a few modes of the model of McKeon and Sharma [J. Fluid Mech. 658, 336 (2010), 10.1017/S002211201000176X]. This model provides modes that act as a basis to decompose the velocity field, ordered by their amplitude of response to forcing arising from the interaction between scales. The model was originally derived from the Navier-Stokes equations to represent turbulent flows and has been used to explain coherent structure and to predict turbulent statistics. This establishes a surprising new link between the two distinct approaches to understanding turbulence.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

PubMed

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

Farm simulation: a tool for evaluating the mitigation of greenhouse gas emissions and the adaptation of dairy production to climate change

USDA-ARS?s Scientific Manuscript database

Process-level modeling at the farm scale provides a tool for evaluating both strategies for mitigating greenhouse gas emissions and strategies for adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to pred...

Toward a Tripartite Model of Research Motivation: Development and Initial Validation of the Research Motivation Scale

ERIC Educational Resources Information Center

Deemer, Eric D.; Martens, Matthew P.; Buboltz, Walter C.

2010-01-01

An instrument designed to measure a 3-factor model of research motivation was developed and psychometrically examined in the present research. Participants were 437 graduate students in biology, chemistry/biochemistry, physics/astronomy, and psychology. A principal components analysis supported the retention of 20 items representing the 3-factor…

Plant systems biology: network matters.

PubMed

Lucas, Mikaël; Laplaze, Laurent; Bennett, Malcolm J

2011-04-01

Systems biology is all about networks. A recent trend has been to associate systems biology exclusively with the study of gene regulatory or protein-interaction networks. However, systems biology approaches can be applied at many other scales, from the subatomic to the ecosystem scales. In this review, we describe studies at the sub-cellular, tissue, whole plant and crop scales and highlight how these studies can be related to systems biology. We discuss the properties of system approaches at each scale as well as their current limits, and pinpoint in each case advances unique to the considered scale but representing potential for the other scales. We conclude by examining plant models bridging different scales and considering the future prospects of plant systems biology. © 2011 Blackwell Publishing Ltd.

Experiences from the testing of a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Experience gained in testing a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift, and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Three-dimensional multi-scale model of deformable platelets adhesion to vessel wall in blood flow

PubMed Central

Wu, Ziheng; Xu, Zhiliang; Kim, Oleg; Alber, Mark

2014-01-01

When a blood vessel ruptures or gets inflamed, the human body responds by rapidly forming a clot to restrict the loss of blood. Platelets aggregation at the injury site of the blood vessel occurring via platelet–platelet adhesion, tethering and rolling on the injured endothelium is a critical initial step in blood clot formation. A novel three-dimensional multi-scale model is introduced and used in this paper to simulate receptor-mediated adhesion of deformable platelets at the site of vascular injury under different shear rates of blood flow. The novelty of the model is based on a new approach of coupling submodels at three biological scales crucial for the early clot formation: novel hybrid cell membrane submodel to represent physiological elastic properties of a platelet, stochastic receptor–ligand binding submodel to describe cell adhesion kinetics and lattice Boltzmann submodel for simulating blood flow. The model implementation on the GPU cluster significantly improved simulation performance. Predictive model simulations revealed that platelet deformation, interactions between platelets in the vicinity of the vessel wall as well as the number of functional GPIbα platelet receptors played significant roles in platelet adhesion to the injury site. Variation of the number of functional GPIbα platelet receptors as well as changes of platelet stiffness can represent effects of specific drugs reducing or enhancing platelet activity. Therefore, predictive simulations can improve the search for new drug targets and help to make treatment of thrombosis patient-specific. PMID:24982253

Integrating neuroinformatics tools in TheVirtualBrain.

PubMed

Woodman, M Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Integrating neuroinformatics tools in TheVirtualBrain

PubMed Central

Woodman, M. Marmaduke; Pezard, Laurent; Domide, Lia; Knock, Stuart A.; Sanz-Leon, Paula; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2014-01-01

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting. PMID:24795617

A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale

Treesearch

Takahiro Sayama; Jeffrey J. McDonnell

2009-01-01

Hydrograph source components and stream water residence time are fundamental behavioral descriptors of watersheds but, as yet, are poorly represented in most rainfall-runoff models. We present a new time-space accounting scheme (T-SAS) to simulate the pre-event and event water fractions, mean residence time, and spatial source of streamflow at the watershed scale. We...

SCALE TSUNAMI Analysis of Critical Experiments for Validation of 233U Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Don; Rearden, Bradley T

2009-01-01

Oak Ridge National Laboratory (ORNL) staff used the SCALE TSUNAMI tools to provide a demonstration evaluation of critical experiments considered for use in validation of current and anticipated operations involving {sup 233}U at the Radiochemical Development Facility (RDF). This work was reported in ORNL/TM-2008/196 issued in January 2009. This paper presents the analysis of two representative safety analysis models provided by RDF staff.

Five challenges for spatial epidemic models.

PubMed

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-03-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Middle atmosphere project. A semi-spectral numerical model for the large-scale stratospheric circulation

NASA Technical Reports Server (NTRS)

Holton, J. R.; Wehrbein, W.

1979-01-01

The complete model is a semispectral model in which the longitudinal dependence is represented by expansion in zonal harmonics while the latitude and height dependencies are represented by a finite difference grid. The model is based on the primitive equations in the log pressure coordinate system. The lower boundary of the model domain is set at the 100 mb level (i.e., near the tropopause) and the effects of tropospheric forcing are included in the lower boundary condition. The upper boundary is at approximately 96 km, and the latitudinal extent is either global or hemispheric. The basic differential equations and boundary conditions are outlined. The finite difference equations are described. The initial conditions are discussed and a sample calculation is presented. The FORTRAN code is given in the appendix.

Spatial and Temporal Scales of Surface Water-Groundwater Interactions

NASA Astrophysics Data System (ADS)

Boano, F.

2016-12-01

The interfaces between surface water and groundwater (i.e., river and lake sediments) represent hotspots for nutrient transformation in watersheds. This intense biochemical activity stems from the peculiar physicochemical properties of these interface areas. Here, the exchange of water and nutrients between surface and subsurface environments creates an ecotone region that can support the presence of different microbial species responsible for nutrient transformation. Previous studies have elucidated that water exchange between rivers and aquifers is organized in a complex system of nested flow cells. Each cell entails a range of residence timescales spanning multiple order of magnitudes, providing opportunities for different biochemical reactions to occur. Physically-bases models represent useful tools to deal with the wide range of spatial and temporal scales that characterize surface-subsurface water exchange. This contribution will present insights about how hydrodynamic processes control scale organization for surface water - groundwater interactions. The specific focus will be the influence of exchange processes on microbial activity and nutrient transformation, discussing how groundwater flow at watershed scale controls flow conditions and hence constrain microbial reactions at much smaller scales.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Wind Tunnel Investigation of Ground Wind Loads for Ares Launch Vehicle

NASA Technical Reports Server (NTRS)

Keller, Donald F.; Ivanco, Thomas G.

2010-01-01

A three year program was conducted at the NASA Langley Research Center (LaRC) Aeroelasticity Branch (AB) and Transonic Dynamics Tunnel (TDT) with the primary objective to acquire scaled steady and dynamic ground-wind loads (GWL) wind-tunnel data for rollout, on-pad stay, and on-pad launch configurations for the Ares I-X Flight Test Vehicle (FTV). The experimental effort was conducted to obtain an understanding of the coupling of aerodynamic and structural characteristics that can result in large sustained wind-induced oscillations (WIO) on such a tall and slender launch vehicle and to generate a unique database for development and evaluation of analytical methods for predicting steady and dynamic GWL, especially those caused by vortex shedding, and resulting in significant WIO. This paper summarizes the wind-tunnel test program that employed two dynamically-aeroelastically scaled GWL models based on the Ares I-X Flight Test Vehicle. The first model tested, the GWL Checkout Model (CM), was a relatively simple model with a secondary objective of restoration and development of processes and methods for design, fabrication, testing, and data analysis of a representative ground wind loads model. In addition, parametric variations in surface roughness, Reynolds number, and protuberances (on/off) were investigated to determine effects on GWL characteristics. The second windtunnel model, the Ares I-X GWL Model, was significantly more complex and representative of the Ares I-X FTV and included the addition of simplified rigid geometrically-scaled models of the Kennedy Space Center (KSC) Mobile Launch Platform (MLP) and Launch Complex 39B primary structures. Steady and dynamic base bending moment as well as model response and steady and unsteady pressure data was acquired during the testing of both models. During wind-tunnel testing of each model, flow conditions (speed and azimuth) where significant WIO occurred, were identified and thoroughly investigated. Scaled data from the Ares I-X GWL model test was used in the determination of worst-case loads for the analysis of Ares I-X FTV design wind conditions. Finally, this paper includes a brief discussion of the limited full-scale GWL data acquired during the rollout and on-pad stay of the Ares I-X FTV that was launched from KSC on October 28, 2009.

High-resolution RCMs as pioneers for future GCMs

NASA Astrophysics Data System (ADS)

Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H.

2017-12-01

Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies.

Ecosystem oceanography for global change in fisheries.

PubMed

Cury, Philippe Maurice; Shin, Yunne-Jai; Planque, Benjamin; Durant, Joël Marcel; Fromentin, Jean-Marc; Kramer-Schadt, Stephanie; Stenseth, Nils Christian; Travers, Morgane; Grimm, Volker

2008-06-01

Overexploitation and climate change are increasingly causing unanticipated changes in marine ecosystems, such as higher variability in fish recruitment and shifts in species dominance. An ecosystem-based approach to fisheries attempts to address these effects by integrating populations, food webs and fish habitats at different scales. Ecosystem models represent indispensable tools to achieve this objective. However, a balanced research strategy is needed to avoid overly complex models. Ecosystem oceanography represents such a balanced strategy that relates ecosystem components and their interactions to climate change and exploitation. It aims at developing realistic and robust models at different levels of organisation and addressing specific questions in a global change context while systematically exploring the ever-increasing amount of biological and environmental data.

A normal stress subgrid-scale eddy viscosity model in large eddy simulation

NASA Technical Reports Server (NTRS)

Horiuti, K.; Mansour, N. N.; Kim, John J.

1993-01-01

The Smagorinsky subgrid-scale eddy viscosity model (SGS-EVM) is commonly used in large eddy simulations (LES) to represent the effects of the unresolved scales on the resolved scales. This model is known to be limited because its constant must be optimized in different flows, and it must be modified with a damping function to account for near-wall effects. The recent dynamic model is designed to overcome these limitations but is compositionally intensive as compared to the traditional SGS-EVM. In a recent study using direct numerical simulation data, Horiuti has shown that these drawbacks are due mainly to the use of an improper velocity scale in the SGS-EVM. He also proposed the use of the subgrid-scale normal stress as a new velocity scale that was inspired by a high-order anisotropic representation model. The testing of Horiuti, however, was conducted using DNS data from a low Reynolds number channel flow simulation. It was felt that further testing at higher Reynolds numbers and also using different flows (other than wall-bounded shear flows) were necessary steps needed to establish the validity of the new model. This is the primary motivation of the present study. The objective is to test the new model using DNS databases of high Reynolds number channel and fully developed turbulent mixing layer flows. The use of both channel (wall-bounded) and mixing layer flows is important for the development of accurate LES models because these two flows encompass many characteristic features of complex turbulent flows.

Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

NASA Astrophysics Data System (ADS)

Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

2017-12-01

Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

Looking for a relevant potential evapotranspiration model at the watershed scale

NASA Astrophysics Data System (ADS)

Oudin, L.; Hervieu, F.; Michel, C.; Perrin, C.; Anctil, F.; Andréassian, V.

2003-04-01

In this paper, we try to identify the most relevant approach to calculate Potential Evapotranspiration (PET) for use in a daily watershed model, to try to bring an answer to the following question: "how can we use commonly available atmospheric parameters to represent the evaporative demand at the catchment scale?". Hydrologists generally see the Penman model as the ideal model regarding to its good adequacy with lysimeter measurements and its physically-based formulation. However, in real-world engineering situations, where meteorological stations are scarce, hydrologists are often constrained to use other PET formulae with less data requirements or/and long-term average of PET values (the rationale being that PET is an inherently conservative variable). We chose to test 28 commonly used PET models coupled with 4 different daily watershed models. For each test, we compare both PET input options: actual data and long-term average data. The comparison is made in terms of streamflow simulation efficiency, over a large sample of 308 watersheds. The watersheds are located in France, Australia and the United States of America and represent varied climates. Strikingly, we find no systematic improvements of the watershed model efficiencies when using actual PET series instead of long-term averages. This suggests either that watershed models may not conveniently use the climatic information contained in PET values or that formulae are only awkward indicators of the real PET which watershed models need.

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

Accelerated Characterization of Full-Scale Reinforced Flexible Pavement Models Using Vibroseis

DOT National Transportation Integrated Search

2010-03-01

Geosynthetic basal reinforcement has been used in flexible pavements and unbound roads to limit the occurrence of rutting, fatigue, and environmental-related cracking, and to permit reduction in base course thickness. However, the lack of a represent...

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

DOE PAGES

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; ...

2016-01-28

A number of numerical models have been developed to quantify the magnitude, over the past 4 decades, such that we have investigated the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH 4) fluxes within terrestrial ecosystems. These CH 4 models are also used for integrating multi-scale CH 4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH 4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvementmore » and application. Our key findings are that (1) the focus of CH 4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH 4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Furthermore three areas for future improvements and applications of terrestrial CH 4 models are that (1) CH 4 models should more explicitly represent the mechanisms underlying land–atmosphere CH 4 exchange, with an emphasis on improving and validating individual CH 4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH 4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. Finally, these improvements in CH 4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.« less

Evaluation of a micro-scale wind model's performance over realistic building clusters using wind tunnel experiments

NASA Astrophysics Data System (ADS)

Zhang, Ning; Du, Yunsong; Miao, Shiguang; Fang, Xiaoyi

2016-08-01

The simulation performance over complex building clusters of a wind simulation model (Wind Information Field Fast Analysis model, WIFFA) in a micro-scale air pollutant dispersion model system (Urban Microscale Air Pollution dispersion Simulation model, UMAPS) is evaluated using various wind tunnel experimental data including the CEDVAL (Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models) wind tunnel experiment data and the NJU-FZ experiment data (Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data). The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier-Stokes equations, and can produce very high-resolution (1-5 m) wind fields of a complex neighborhood scale urban building canopy (~ 1 km ×1 km) in less than 3 min when run on a personal computer.

Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer

DOE PAGES

Nuijens, Louise; Medeiros, Brian; Sandu, Irina; ...

2015-11-06

We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less

Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nuijens, Louise; Medeiros, Brian; Sandu, Irina

We present patterns of covariability between low-level cloudiness and the trade-wind boundary layer structure using long-term measurements at a site representative of dynamical regimes with moderate subsidence or weak ascent. We compare these with ECMWF’s Integrated Forecast System and 10 CMIP5 models. By using single-time step output at a single location, we find that models can produce a fairly realistic trade-wind layer structure in long-term means, but with unrealistic variability at shorter-time scales. The unrealistic variability in modeled cloudiness near the lifting condensation level (LCL) is due to stronger than observed relationships with mixed-layer relative humidity (RH) and temperature stratificationmore » at the mixed-layer top. Those relationships are weak in observations, or even of opposite sign, which can be explained by a negative feedback of convection on cloudiness. Cloudiness near cumulus tops at the tradewind inversion instead varies more pronouncedly in observations on monthly time scales, whereby larger cloudiness relates to larger surface winds and stronger trade-wind inversions. However, these parameters appear to be a prerequisite, rather than strong controlling factors on cloudiness, because they do not explain submonthly variations in cloudiness. Models underestimate the strength of these relationships and diverge in particular in their responses to large-scale vertical motion. No model stands out by reproducing the observed behavior in all respects. As a result, these findings suggest that climate models do not realistically represent the physical processes that underlie the coupling between trade-wind clouds and their environments in present-day climate, which is relevant for how we interpret modeled cloud feedbacks.« less

Towards large scale modelling of wetland water dynamics in northern basins.

NASA Astrophysics Data System (ADS)

Pedinotti, V.; Sapriza, G.; Stone, L.; Davison, B.; Pietroniro, A.; Quinton, W. L.; Spence, C.; Wheater, H. S.

2015-12-01

Understanding the hydrological behaviour of low topography, wetland-dominated sub-arctic areas is one major issue needed for the improvement of large scale hydrological models. These wet organic soils cover a large extent of Northern America and have a considerable impact on the rainfall-runoff response of a catchment. Moreover their strong interactions with the lower atmosphere and the carbon cycle make of these areas a noteworthy component of the regional climate system. In the framework of the Changing Cold Regions Network (CCRN), this study aims at providing a model for wetland water dynamics that can be used for large scale applications in cold regions. The modelling system has two main components : a) the simulation of surface runoff using the Modélisation Environmentale Communautaire - Surface and Hydrology (MESH) land surface model driven with several gridded atmospheric datasets and b) the routing of surface runoff using the WATROUTE channel scheme. As a preliminary study, we focus on two small representative study basins in Northern Canada : Scotty Creek in the lower Liard River valley of the Northwest Territories and Baker Creek, located a few kilometers north of Yellowknife. Both areas present characteristic landscapes dominated by a series of peat plateaus, channel fens, small lakes and bogs. Moreover, they constitute important fieldwork sites with detailed data to support our modelling study. The challenge of our new wetland model is to represent the hydrological functioning of the various landscape units encountered in those watersheds and their interactions using simple numerical formulations that can be later extended to larger basins such as the Mackenzie river basin. Using observed datasets, the performance of the model to simulate the temporal evolution of hydrological variables such as the water table depth, frost table depth and discharge is assessed.

A Testbed for Model Development

NASA Astrophysics Data System (ADS)

Berry, J. A.; Van der Tol, C.; Kornfeld, A.

2014-12-01

Carbon cycle and land-surface models used in global simulations need to be computationally efficient and have a high standard of software engineering. These models also make a number of scaling assumptions to simplify the representation of complex biochemical and structural properties of ecosystems. This makes it difficult to use these models to test new ideas for parameterizations or to evaluate scaling assumptions. The stripped down nature of these models also makes it difficult to "connect" with current disciplinary research which tends to be focused on much more nuanced topics than can be included in the models. In our opinion/experience this indicates the need for another type of model that can more faithfully represent the complexity ecosystems and which has the flexibility to change or interchange parameterizations and to run optimization codes for calibration. We have used the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model in this way to develop, calibrate, and test parameterizations for solar induced chlorophyll fluorescence, OCS exchange and stomatal parameterizations at the canopy scale. Examples of the data sets and procedures used to develop and test new parameterizations are presented.

Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

PubMed

Liu, Qin; Ulloa, Antonio; Horwitz, Barry

2017-11-01

Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

Simulating hydrologic and hydraulic processes throughout the Amazon River Basin

USGS Publications Warehouse

Beighley, R.E.; Eggert, K.G.; Dunne, T.; He, Y.; Gummadi, V.; Verdin, K.L.

2009-01-01

Presented here is a model framework based on a land surface topography that can be represented with various degrees of resolution and capable of providing representative channel/floodplain hydraulic characteristics on a daily to hourly scale. The framework integrates two models: (1) a water balance model (WBM) for the vertical fluxes and stores of water in and through the canopy and soil layers based on the conservation of mass and energy, and (2) a routing model for the horizontal routing of surface and subsurface runoff and channel and floodplain waters based on kinematic and diffusion wave methodologies. The WBM is driven by satellite-derived precipitation (TRMM_3B42) and air temperature (MOD08_M3). The model's use of an irregular computational grid is intended to facilitate parallel processing for applications to continental and global scales. Results are presented for the Amazon Basin over the period Jan 2001 through Dec 2005. The model is shown to capture annual runoff totals, annual peaks, seasonal patterns, and daily fluctuations over a range of spatial scales (>1, 000 to < 4·7M km2). For the period of study, results suggest basin-wide total water storage changes in the Amazon vary by approximately + /− 5 to 10 cm, and the fractional components accounting for these changes are: root zone soil moisture (20%), subsurface water being routed laterally to channels (40%) and channel/floodplain discharge (40%). Annual variability in monthly water storage changes by + /− 2·5 cm is likely due to 0·5 to 1 month variability in the arrival of significant rainfall periods throughout the basin.

Flooding Fragility Experiments and Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis L.; Tahhan, Antonio; Muchmore, Cody

2016-09-01

This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

A control theoretical approach to crowd management. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Borzí, Alfio; Caponigro, Marco

2016-09-01

The formulation of mathematical models for crowd dynamics is one current challenge in many fields of applied sciences. It involves the modelization of the complex behavior of a large number of individuals. In particular, the difficulty lays in describing emerging collective behaviors by means of a relatively small number of local interaction rules between individuals in a crowd. Clearly, the individual's free will involved in decision making processes and in the management of the social interactions cannot be described by a finite number of deterministic rules. On the other hand, in large crowds, this individual indeterminacy can be considered as a local fluctuation averaged to zero by the size of the crowd. While at the microscopic scale, using a system of coupled ODEs, the free will should be included in the mathematical description (e.g. with a stochastic term), the mesoscopic and macroscopic scales, modeled by PDEs, represent a powerful modelling tool that allows to neglect this feature and provide a reliable description. In this sense, the work by Bellomo, Clarke, Gibelli, Townsend, and Vreugdenhil [2] represents a mathematical-epistemological contribution towards the design of a reliable model of human behavior.

Modelling Precipitation and Temperature Extremes: The Importance of Horizontal Resolution

NASA Astrophysics Data System (ADS)

Shields, C. A.; Kiehl, J. T.; Meehl, G. A.

2013-12-01

Understanding Earth's water cycle on a warming planet is of critical importance in society's ability to adapt to climate change. Extreme weather events, such as floods, heat waves, and drought will likely change with the water cycle as greenhouse gases continue to rise. Location, duration, and intensity of extreme events can be studied using complex earth system models. Here, we employ the fully coupled Community Earth System Model (CESM1.0) to evaluate extreme event impacts for different possible future forcing scenarios. Simulations applying the Representative Concentration Pathway (RCP) scenarios 2.6 and 8.5 were chosen to bracket the range of model responses. Because extreme weather events happen on a regional scale, there is a tendency to favor using higher resolution models, i.e. models that can represent regional features with greater accuracy. Within the CESM1.0 framework, we evaluate both the standard 1 degree resolution (1 degree atmosphere/land coupled to 1 degree ocean/sea ice), and the higher 0.5 degree resolution version (0.5 degree atmosphere/land coupled to 1 degree ocean/sea ice), focusing on extreme precipitation events, heat waves, and droughts. We analyze a variety of geographical regions, but generally find that benefits from increased horizontal resolution are most significant on the regional scale.

"The Effect of Alternative Representations of Lake ...

EPA Pesticide Factsheets

Lakes can play a significant role in regional climate, modulating inland extremes in temperature and enhancing precipitation. Representing these effects becomes more important as regional climate modeling (RCM) efforts focus on simulating smaller scales. When using the Weather Research and Forecasting (WRF) model to downscale future global climate model (GCM) projections into RCM simulations, model users typically must rely on the GCM to represent temperatures at all water points. However, GCMs have insufficient resolution to adequately represent even large inland lakes, such as the Great Lakes. Some interpolation methods, such as setting lake surface temperatures (LSTs) equal to the nearest water point, can result in inland lake temperatures being set from sea surface temperatures (SSTs) that are hundreds of km away. In other cases, a single point is tasked with representing multiple large, heterogeneous lakes. Similar consequences can result from interpolating ice from GCMs to inland lake points, resulting in lakes as large as Lake Superior freezing completely in the space of a single timestep. The use of a computationally-efficient inland lake model can improve RCM simulations where the input data is too coarse to adequately represent inland lake temperatures and ice (Gula and Peltier 2012). This study examines three scenarios under which ice and LSTs can be set within the WRF model when applied as an RCM to produce 2-year simulations at 12 km gri

Progressive transmission of road network

NASA Astrophysics Data System (ADS)

Ai, Bo; Ai, Tinghua; Tang, Xinming; Li, Zhen

2009-10-01

The progressive transmission of vector map data requires efficient multi-scale data model to process the data into hierarchical structure. This paper presents such a data structure of road network without redundancy of geometry for progressive transmission. For a given scale, the road network display has to settle two questions. One is which road objects to be represented and the other is what geometric details to be visualized for the selected roads. This paper combines the Töpfer law and the BLG-tree structure into a multi-scale representation matrix to answer simultaneously the above two questions. In the matrix, rows from top to bottom represent the roads in the sequence of descending classification of traffic and length, which can support the Töpfer law to retrieve the more important roads. In a row, columns record one road by a linear BLG-tree to provide good line graphics.

Cross-domain transfer of quantitative discriminations: is it all a matter of proportion?

PubMed

Balci, Fuat; Gallistel, Charles R

2006-08-01

Meck and Church (1983) estimated a 5:1 scale factor relating the mental magnitudes representing number to the mental magnitudes representing duration. We repeated their experiment with human subjects. We obtained transfer regardless of the objective scaling between the ranges; a 5:1 scaling for number versus duration (measured in seconds) was not necessary. We obtained transfer even when the proportions between the endpoints of the number range were different. We conclude that, at least in human subjects, transfer from a discrimination based on continuous quantity (duration) to a discrimination based on discrete quantity (number) is mediated by the cross-domain comparability of within-domain proportions. The results of our second and third experiments also suggest that the subjects compare a probe with a criterion determined by the range of stimuli tested rather than by trial-specific referents, in accordance with the pseudologistic model of Killeen, Fetterman, and Bizo (1997).

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

PubMed Central

Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan

2014-01-01

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470

Geological modeling of submeter scale heterogeneity and its influence on tracer transport in a fluvial aquifer

NASA Astrophysics Data System (ADS)

Ronayne, Michael J.; Gorelick, Steven M.; Zheng, Chunmiao

2010-10-01

We developed a new model of aquifer heterogeneity to analyze data from a single-well injection-withdrawal tracer test conducted at the Macrodispersion Experiment (MADE) site on the Columbus Air Force Base in Mississippi (USA). The physical heterogeneity model is a hybrid that combines 3-D lithofacies to represent submeter scale, highly connected channels within a background matrix based on a correlated multivariate Gaussian hydraulic conductivity field. The modeled aquifer architecture is informed by a variety of field data, including geologic core sampling. Geostatistical properties of this hybrid heterogeneity model are consistent with the statistics of the hydraulic conductivity data set based on extensive borehole flowmeter testing at the MADE site. The representation of detailed, small-scale geologic heterogeneity allows for explicit simulation of local preferential flow and slow advection, processes that explain the complex tracer response from the injection-withdrawal test. Based on the new heterogeneity model, advective-dispersive transport reproduces key characteristics of the observed tracer recovery curve, including a delayed concentration peak and a low-concentration tail. Importantly, our results suggest that intrafacies heterogeneity is responsible for local-scale mass transfer.

On inclusion of water resource management in Earth system models - Part 1: Problem definition and representation of water demand

NASA Astrophysics Data System (ADS)

Nazemi, A.; Wheater, H. S.

2015-01-01

Human activities have caused various changes to the Earth system, and hence the interconnections between human activities and the Earth system should be recognized and reflected in models that simulate Earth system processes. One key anthropogenic activity is water resource management, which determines the dynamics of human-water interactions in time and space and controls human livelihoods and economy, including energy and food production. There are immediate needs to include water resource management in Earth system models. First, the extent of human water requirements is increasing rapidly at the global scale and it is crucial to analyze the possible imbalance between water demands and supply under various scenarios of climate change and across various temporal and spatial scales. Second, recent observations show that human-water interactions, manifested through water resource management, can substantially alter the terrestrial water cycle, affect land-atmospheric feedbacks and may further interact with climate and contribute to sea-level change. Due to the importance of water resource management in determining the future of the global water and climate cycles, the World Climate Research Program's Global Energy and Water Exchanges project (WRCP-GEWEX) has recently identified gaps in describing human-water interactions as one of the grand challenges in Earth system modeling (GEWEX, 2012). Here, we divide water resource management into two interdependent elements, related firstly to water demand and secondly to water supply and allocation. In this paper, we survey the current literature on how various components of water demand have been included in large-scale models, in particular land surface and global hydrological models. Issues of water supply and allocation are addressed in a companion paper. The available algorithms to represent the dominant demands are classified based on the demand type, mode of simulation and underlying modeling assumptions. We discuss the pros and cons of available algorithms, address various sources of uncertainty and highlight limitations in current applications. We conclude that current capability of large-scale models to represent human water demands is rather limited, particularly with respect to future projections and coupled land-atmospheric simulations. To fill these gaps, the available models, algorithms and data for representing various water demands should be systematically tested, intercompared and improved. In particular, human water demands should be considered in conjunction with water supply and allocation, particularly in the face of water scarcity and unknown future climate.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: a multi-scale simulation analysis.

PubMed

Knightes, C D; Golden, H E; Journey, C A; Davis, G M; Conrads, P A; Marvin-DiPasquale, M; Brigham, M E; Bradley, P M

2014-04-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km(2)) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km(2) and 25 km(2)) and the encompassing watershed (79 km(2)). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport. Published by Elsevier Ltd.

Overview of the Meso-NH model version 5.4 and its applications

NASA Astrophysics Data System (ADS)

Lac, Christine; Chaboureau, Jean-Pierre; Masson, Valéry; Pinty, Jean-Pierre; Tulet, Pierre; Escobar, Juan; Leriche, Maud; Barthe, Christelle; Aouizerats, Benjamin; Augros, Clotilde; Aumond, Pierre; Auguste, Franck; Bechtold, Peter; Berthet, Sarah; Bielli, Soline; Bosseur, Frédéric; Caumont, Olivier; Cohard, Jean-Martial; Colin, Jeanne; Couvreux, Fleur; Cuxart, Joan; Delautier, Gaëlle; Dauhut, Thibaut; Ducrocq, Véronique; Filippi, Jean-Baptiste; Gazen, Didier; Geoffroy, Olivier; Gheusi, François; Honnert, Rachel; Lafore, Jean-Philippe; Lebeaupin Brossier, Cindy; Libois, Quentin; Lunet, Thibaut; Mari, Céline; Maric, Tomislav; Mascart, Patrick; Mogé, Maxime; Molinié, Gilles; Nuissier, Olivier; Pantillon, Florian; Peyrillé, Philippe; Pergaud, Julien; Perraud, Emilie; Pianezze, Joris; Redelsperger, Jean-Luc; Ricard, Didier; Richard, Evelyne; Riette, Sébastien; Rodier, Quentin; Schoetter, Robert; Seyfried, Léo; Stein, Joël; Suhre, Karsten; Taufour, Marie; Thouron, Odile; Turner, Sandra; Verrelle, Antoine; Vié, Benoît; Visentin, Florian; Vionnet, Vincent; Wautelet, Philippe

2018-05-01

This paper presents the Meso-NH model version 5.4. Meso-NH is an atmospheric non hydrostatic research model that is applied to a broad range of resolutions, from synoptic to turbulent scales, and is designed for studies of physics and chemistry. It is a limited-area model employing advanced numerical techniques, including monotonic advection schemes for scalar transport and fourth-order centered or odd-order WENO advection schemes for momentum. The model includes state-of-the-art physics parameterization schemes that are important to represent convective-scale phenomena and turbulent eddies, as well as flows at larger scales. In addition, Meso-NH has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling. Here, we present the main innovations to the dynamics and physics of the code since the pioneer paper of Lafore et al. (1998) and provide an overview of recent applications and couplings.

Basin-scale hydrogeologic modeling

NASA Astrophysics Data System (ADS)

Person, Mark; Raffensperger, Jeff P.; Ge, Shemin; Garven, Grant

1996-02-01

Mathematical modeling of coupled groundwater flow, heat transfer, and chemical mass transport at the sedimentary basin scale has been increasingly used by Earth scientists studying a wide range of geologic processes including the formation of excess pore pressures, infiltration-driven metamorphism, heat flow anomalies, nuclear waste isolation, hydrothermal ore genesis, sediment diagenesis, basin tectonics, and petroleum generation and migration. These models have provided important insights into the rates and pathways of groundwater migration through basins, the relative importance of different driving mechanisms for fluid flow, and the nature of coupling between the hydraulic, thermal, chemical, and stress regimes. The mathematical descriptions of basin transport processes, the analytical and numerical solution methods employed, and the application of modeling to sedimentary basins around the world are the subject of this review paper. The special considerations made to represent coupled transport processes at the basin scale are emphasized. Future modeling efforts will probably utilize three-dimensional descriptions of transport processes, incorporate greater information regarding natural geological heterogeneity, further explore coupled processes, and involve greater field applications.

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

PubMed

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.

Peridynamic Multiscale Finite Element Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Timothy; Bond, Stephen D.; Littlewood, David John

The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less

A Bayesian method for assessing multiscalespecies-habitat relationships

USGS Publications Warehouse

Stuber, Erica F.; Gruber, Lutz F.; Fontaine, Joseph J.

2017-01-01

ContextScientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.ObjectivesOur objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.MethodsWe introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.ResultsOur method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.ConclusionsGiven the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

DOE PAGES

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.; ...

2018-04-17

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

NASA Astrophysics Data System (ADS)

Feyen, Luc; Caers, Jef

2006-06-01

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.

R-HyMOD: an R-package for the hydrological model HyMOD

NASA Astrophysics Data System (ADS)

Baratti, Emanuele; Montanari, Alberto

2015-04-01

A software code for the implementation of the HyMOD hydrological model [1] is presented. HyMOD is a conceptual lumped rainfall-runoff model that is based on the probability-distributed soil storage capacity principle introduced by R. J. Moore 1985 [2]. The general idea behind this model is to describe the spatial variability of some process parameters as, for instance, the soil structure or the water storage capacities, through probability distribution functions. In HyMOD, the rainfall-runoff process is represented through a nonlinear tank connected with three identical linear tanks in parallel representing the surface flow and a slow-flow tank representing groundwater flow. The model requires the optimization of five parameters: Cmax (the maximum storage capacity within the watershed), β (the degree of spatial variability of the soil moisture capacity within the watershed), α (a factor for partitioning the flow between two series of tanks) and the two residence time parameters of quick-flow and slow-flow tanks, kquick and kslow respectively. Given its relatively simplicity but robustness, the model is widely used in the literature. The input data consist of precipitation and potential evapotranspiration at the given time scale. The R-HyMOD package is composed by a 'canonical' R-function of HyMOD and a fast FORTRAN implementation. The first one can be easily modified and can be used, for instance, for educational purposes; the second part combines the R user friendly interface with a fast processing unit. [1] Boyle D.P. (2000), Multicriteria calibration of hydrological models, Ph.D. dissertation, Dep. of Hydrol. and Water Resour., Univ of Arizona, Tucson. [2] Moore, R.J., (1985), The probability-distributed principle and runoff production at point and basin scale, Hydrol. Sci. J., 30(2), 273-297.

Shear-induced rigidity in athermal materials

NASA Astrophysics Data System (ADS)

Chakraborty, Bulbul; Sarkar, Sumantra

2014-03-01

In this talk, we present a minimal model of rigidity and plastic failure in solids whose rigidity emerges directly as a result of applied stresses. Examples include shear-jamming (SJ) in dry grains and discontinuous shear thickening (DST) of dense non-Brownian suspensions. Both SJ and DST states are examples of non-equilibrium, self-assembled structures that have evolved to support the load that created them. These are strongly-interacting systems where the interactions arise primarily from the strict constraints of force and torque balance at the local and global scales. Our model is based on a reciprocal-space picture that strictly enforces the local and global constraints, and is, therefore, best suited to capturing the strong correlations in these non-equilibrium systems. The reciprocal space is a tiling whose edges represent contact forces, and whose faces represent grains. A separation of scale between force fluctuations and displacements of grains is used to represent the positional disorder as quenched randomness on variables in the reciprocal space. Comparing theoretical results to experiments, we will argue that the packing fraction controls the strength of the quenched disorder. Sumantra Sarkar et al, Phys. Rev. Lett. 111, 068301 (2013)

Wave propagation in equivalent continuums representing truss lattice materials

DOE PAGES

Messner, Mark C.; Barham, Matthew I.; Kumar, Mukul; ...

2015-07-29

Stiffness scales linearly with density in stretch-dominated lattice meta-materials offering the possibility of very light yet very stiff structures. Current additive manufacturing techniques can assemble structures from lattice materials, but the design of such structures will require accurate, efficient simulation methods. Equivalent continuum models have several advantages over discrete truss models of stretch dominated lattices, including computational efficiency and ease of model construction. However, the development an equivalent model suitable for representing the dynamic response of a periodic truss in the small deformation regime is complicated by microinertial effects. This study derives a dynamic equivalent continuum model for periodic trussmore » structures suitable for representing long-wavelength wave propagation and verifies it against the full Bloch wave theory and detailed finite element simulations. The model must incorporate microinertial effects to accurately reproduce long wavelength characteristics of the response such as anisotropic elastic soundspeeds. Finally, the formulation presented here also improves upon previous work by preserving equilibrium at truss joints for simple lattices and by improving numerical stability by eliminating vertices in the effective yield surface.« less

Modelling of Sub-daily Hydrological Processes Using Daily Time-Step Models: A Distribution Function Approach to Temporal Scaling

NASA Astrophysics Data System (ADS)

Kandel, D. D.; Western, A. W.; Grayson, R. B.

2004-12-01

Mismatches in scale between the fundamental processes, the model and supporting data are a major limitation in hydrologic modelling. Surface runoff generation via infiltration excess and the process of soil erosion are fundamentally short time-scale phenomena and their average behaviour is mostly determined by the short time-scale peak intensities of rainfall. Ideally, these processes should be simulated using time-steps of the order of minutes to appropriately resolve the effect of rainfall intensity variations. However, sub-daily data support is often inadequate and the processes are usually simulated by calibrating daily (or even coarser) time-step models. Generally process descriptions are not modified but rather effective parameter values are used to account for the effect of temporal lumping, assuming that the effect of the scale mismatch can be counterbalanced by tuning the parameter values at the model time-step of interest. Often this results in parameter values that are difficult to interpret physically. A similar approach is often taken spatially. This is problematic as these processes generally operate or interact non-linearly. This indicates a need for better techniques to simulate sub-daily processes using daily time-step models while still using widely available daily information. A new method applicable to many rainfall-runoff-erosion models is presented. The method is based on temporal scaling using statistical distributions of rainfall intensity to represent sub-daily intensity variations in a daily time-step model. This allows the effect of short time-scale nonlinear processes to be captured while modelling at a daily time-step, which is often attractive due to the wide availability of daily forcing data. The approach relies on characterising the rainfall intensity variation within a day using a cumulative distribution function (cdf). This cdf is then modified by various linear and nonlinear processes typically represented in hydrological and erosion models. The statistical description of sub-daily variability is thus propagated through the model, allowing the effects of variability to be captured in the simulations. This results in cdfs of various fluxes, the integration of which over a day gives respective daily totals. Using 42-plot-years of surface runoff and soil erosion data from field studies in different environments from Australia and Nepal, simulation results from this cdf approach are compared with the sub-hourly (2-minute for Nepal and 6-minute for Australia) and daily models having similar process descriptions. Significant improvements in the simulation of surface runoff and erosion are achieved, compared with a daily model that uses average daily rainfall intensities. The cdf model compares well with a sub-hourly time-step model. This suggests that the approach captures the important effects of sub-daily variability while utilizing commonly available daily information. It is also found that the model parameters are more robustly defined using the cdf approach compared with the effective values obtained at the daily scale. This suggests that the cdf approach may offer improved model transferability spatially (to other areas) and temporally (to other periods).

Statistical self-similarity of width function maxima with implications to floods

USGS Publications Warehouse

Veitzer, S.A.; Gupta, V.K.

2001-01-01

Recently a new theory of random self-similar river networks, called the RSN model, was introduced to explain empirical observations regarding the scaling properties of distributions of various topologic and geometric variables in natural basins. The RSN model predicts that such variables exhibit statistical simple scaling, when indexed by Horton-Strahler order. The average side tributary structure of RSN networks also exhibits Tokunaga-type self-similarity which is widely observed in nature. We examine the scaling structure of distributions of the maximum of the width function for RSNs for nested, complete Strahler basins by performing ensemble simulations. The maximum of the width function exhibits distributional simple scaling, when indexed by Horton-Strahler order, for both RSNs and natural river networks extracted from digital elevation models (DEMs). We also test a powerlaw relationship between Horton ratios for the maximum of the width function and drainage areas. These results represent first steps in formulating a comprehensive physical statistical theory of floods at multiple space-time scales for RSNs as discrete hierarchical branching structures. ?? 2001 Published by Elsevier Science Ltd.

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Methodology for calculating shear stress in a meandering channel

Treesearch

Kyung-Seop Sin

2010-01-01

Shear stress in meandering channels is the key parameter to predict bank erosion and bend migration. A representative study reach of the Rio Grande River in central New Mexico has been modeled in the Hydraulics Laboratory at CSU. To determine the shear stress distribution in a meandering channel, the large scale (1:12) physical modeling study was conducted in the...

The Circumplex Model of the Questionnaire on Teacher Interaction among Hong Kong Students: A Multidimensional Scaling Solution

ERIC Educational Resources Information Center

Sivan, Atara; Cohen, Arie; Chan, Dennis W.; Kwan, Yee Wan

2017-01-01

The Questionnaire on Teacher Interaction (QTI) is a teacher--student relationship measure whose underlying two-dimensional structure is represented in a circumplex model with eight sectors. Using Smallest Space Analysis (SSA), this study examined the circumplex structure of the Chinese version of the QTI among a convenience sample of 731…

Development and Validation of Big Four Personality Scales for the Schedule for Nonadaptive and Adaptive Personality-Second Edition (SNAP-2)

ERIC Educational Resources Information Center

Calabrese, William R.; Rudick, Monica M.; Simms, Leonard J.; Clark, Lee Anna

2012-01-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality…

Solid object visualization of 3D ultrasound data

NASA Astrophysics Data System (ADS)

Nelson, Thomas R.; Bailey, Michael J.

2000-04-01

Visualization of volumetric medical data is challenging. Rapid-prototyping (RP) equipment producing solid object prototype models of computer generated structures is directly applicable to visualization of medical anatomic data. The purpose of this study was to develop methods for transferring 3D Ultrasound (3DUS) data to RP equipment for visualization of patient anatomy. 3DUS data were acquired using research and clinical scanning systems. Scaling information was preserved and the data were segmented using threshold and local operators to extract features of interest, converted from voxel raster coordinate format to a set of polygons representing an iso-surface and transferred to the RP machine to create a solid 3D object. Fabrication required 30 to 60 minutes depending on object size and complexity. After creation the model could be touched and viewed. A '3D visualization hardcopy device' has advantages for conveying spatial relations compared to visualization using computer display systems. The hardcopy model may be used for teaching or therapy planning. Objects may be produced at the exact dimension of the original object or scaled up (or down) to facilitate matching the viewers reference frame more optimally. RP models represent a useful means of communicating important information in a tangible fashion to patients and physicians.

Influences of Regional Climate Change on Air Quality Across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations. Chapter 2

NASA Technical Reports Server (NTRS)

Nolte, Christopher; Otte, Tanya; Pinder, Robert; Bowden, J.; Herwehe, J.; Faluvegi, Gregory; Shindell, Drew

2013-01-01

Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture regional-scale changes in temperatures and precipitation. We use a regional climate model (RCM) to dynamically downscale the GCM's large-scale signal to investigate the changes in regional and local extremes of temperature and precipitation that may result from a changing climate. In this paper, we show preliminary results from downscaling the NASA/GISS ModelE IPCC AR5 Representative Concentration Pathway (RCP) 6.0 scenario. We use the Weather Research and Forecasting (WRF) model as the RCM to downscale decadal time slices (1995-2005 and 2025-2035) and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0. The regional climate change scenario is further processed using the Community Multiscale Air Quality modeling system to explore influences of regional climate change on air quality.

Tidal dissipation in a viscoelastic planet

NASA Technical Reports Server (NTRS)

Ross, M.; Schubert, G.

1986-01-01

Tidal dissipation is examined using Maxwell standard liner solid (SLS), and Kelvin-Voigt models, and viscosity parameters are derived from the models that yield the amount of dissipation previously calculated for a moon model with QW = 100 in a hypothetical orbit closer to the earth. The relevance of these models is then assessed for simulating planetary tidal responses. Viscosities of 10 exp 14 and 10 ex 18 Pa s for the Kelvin-Voigt and Maxwell rheologies, respectively, are needed to match the dissipation rate calculated using the Q approach with a quality factor = 100. The SLS model requires a short time viscosity of 3 x 10 exp 17 Pa s to match the Q = 100 dissipation rate independent of the model's relaxation strength. Since Q = 100 is considered a representative value for the interiors of terrestrial planets, it is proposed that derived viscosities should characterize planetary materials. However, it is shown that neither the Kelvin-Voigt nor the SLS models simulate the behavior of real planetary materials on long time scales. The Maxwell model, by contrast, behaves realistically on both long and short time scales. The inferred Maxwell viscosity, corresponding to the time scale of days, is several times smaller than the longer time scale (greater than or equal to 10 exp 14 years) viscosity of the earth's mantle.

Physical understanding of complex multiscale biochemical models via algorithmic simplification: Glycolysis in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Kourdis, Panayotis D.; Steuer, Ralf; Goussis, Dimitris A.

2010-09-01

Large-scale models of cellular reaction networks are usually highly complex and characterized by a wide spectrum of time scales, making a direct interpretation and understanding of the relevant mechanisms almost impossible. We address this issue by demonstrating the benefits provided by model reduction techniques. We employ the Computational Singular Perturbation (CSP) algorithm to analyze the glycolytic pathway of intact yeast cells in the oscillatory regime. As a primary object of research for many decades, glycolytic oscillations represent a paradigmatic candidate for studying biochemical function and mechanisms. Using a previously published full-scale model of glycolysis, we show that, due to fast dissipative time scales, the solution is asymptotically attracted on a low dimensional manifold. Without any further input from the investigator, CSP clarifies several long-standing questions in the analysis of glycolytic oscillations, such as the origin of the oscillations in the upper part of glycolysis, the importance of energy and redox status, as well as the fact that neither the oscillations nor cell-cell synchronization can be understood in terms of glycolysis as a simple linear chain of sequentially coupled reactions.

RADSOURCE. Volume 1, Part 1, A scaling factor prediction computer program technical manual and code validation: Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vance, J.N.; Holderness, J.H.; James, D.W.

1992-12-01

Waste stream scaling factors based on sampling programs are vulnerable to one or more of the following factors: sample representativeness, analytic accuracy, and measurement sensitivity. As an alternative to sample analyses or as a verification of the sampling results, this project proposes the use of the RADSOURCE code, which accounts for the release of fuel-source radionuclides. Once the release rates of these nuclides from fuel are known, the code develops scaling factors for waste streams based on easily measured Cobalt-60 (Co-60) and Cesium-137 (Cs-137). The project team developed mathematical models to account for the appearance rate of 10CFR61 radionuclides inmore » reactor coolant. They based these models on the chemistry and nuclear physics of the radionuclides involved. Next, they incorporated the models into a computer code that calculates plant waste stream scaling factors based on reactor coolant gamma- isotopic data. Finally, the team performed special sampling at 17 reactors to validate the models in the RADSOURCE code.« less

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Why do we have such difficulty assessing aerosol impacts in Southeast Asia? Examining the representativeness of regional in situ, remote sensing, and modeling data using examples from a recent field trial

NASA Astrophysics Data System (ADS)

Reid, J.; Hyer, E. J.; Lagrosas, N.; Salinas Cortijo, S. V.; Campbell, J. R.; Chew, B.; Cook, J.; Di Girolamo, L.; Kuciauskas, A. P.; Johnson, R. S.; Jonsson, H.; Lynch, P.; Sessions, W.; Simpas, J. B.; Turk, F. J.; Wang, J.

2012-12-01

Southeast Asia faces numerous climate change issues, and the interaction between aerosol particles, clouds, and precipitation is thought to impact the environment in this region at both weather and climate scales. Aerosol particles have direct radiative effects, indirect effects through interaction with clouds and precipitation, and also act as a tracer for other processes affecting the carbon cycle or atmospheric chemistry. Southeast Asia also hosts some of the most complex meteorological phenomenon of the world, challenging in situ, remote sensing and modeling systems. Indeed, there is more diversity in satellite based aerosol, fire, cloud, and precipitation products in Southeast Asia than perhaps anywhere else in the world outside of the poles. In addition to serious direct challenges to aerosol observability in Southeast Asia, such as persistent ubiquitous cloud cover, there are also contextual biases (such as for aerosol retrievals the classic clear sky bias). Contextual bias affects the representativeness of nearly all aerosol assessments in Southeast Asia. As part of the 7 Southeast Asian Studies (7SEAS) program, a small intensive study was conducted in Singapore and the Palawan Archipelago in September 2011 to study the flow of biomass burning smoke through the South China/East Sea and into the summertime monsoonal trough. Analysis of field data coupled with multiple satellite and model products allowed us to investigate questions on the representativeness of data and to what extent they capture the 'true' state of the meteorological and aerosol environment. Four specific representativeness issues are presented based on IOP examples: 1) Individual biases in retrievals or model simulations; 2) Sampling biases at short time scales based on product coverage; 3) Temporal and spatial scale biases inherent in large and point based measurements; 4) Contextual biases that develop from the aggregation of data products. Considering all four of these issues we conclude with a discussion of strategies for hypothesis testing and the development of regional state vectors with realistic uncertainties.

Development and application of a reactive plume-in-grid model: evaluation over Greater Paris

NASA Astrophysics Data System (ADS)

Korsakissok, I.; Mallet, V.

2010-02-01

Emissions from major point sources are badly represented by classical Eulerian models. An overestimation of the horizontal plume dilution, a bad representation of the vertical diffusion as well as an incorrect estimate of the chemical reaction rates are the main limitations of such models in the vicinity of major point sources. The plume-in-grid method is a multiscale modeling technique that couples a local-scale Gaussian puff model with an Eulerian model in order to better represent these emissions. We present the plume-in-grid model developed in the air quality modeling system Polyphemus, with full gaseous chemistry. The model is evaluated on the metropolitan Île-de-France region, during six months (summer 2001). The subgrid-scale treatment is used for 89 major point sources, a selection based on the emission rates of NOx and SO2. Results with and without the subgrid treatment of point emissions are compared, and their performance by comparison to the observations at measurement stations is assessed. A sensitivity study is also carried out, on several local-scale parameters as well as on the vertical diffusion within the urban area. Primary pollutants are shown to be the most impacted by the plume-in-grid treatment, with a decrease in RMSE by up to about -17% for SO2 and -7% for NO at measurement stations. SO2 is the most impacted pollutant, since the point sources account for an important part of the total SO2 emissions, whereas NOx emissions are mostly due to traffic. The spatial impact of the subgrid treatment is localized in the vicinity of the sources, especially for reactive species (NOx and O3). Reactive species are mostly sensitive to the local-scale parameters, such as the time step between two puff emissions which influences the in-plume chemical reactions, whereas the almost-passive species SO2 is more sensitive to the injection time, which determines the duration of the subgrid-scale treatment. Future developments include an extension to handle aerosol chemistry, and an application to the modeling of line sources in order to use the subgrid treatment with road emissions. The latter is expected to lead to more striking results, due to the importance of traffic emissions for the pollutants of interest.

Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity

NASA Astrophysics Data System (ADS)

Chaney, N.; Newman, A. J.

2017-12-01

By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.

A coupled synoptic-hydrological model for climate change impact assessment

NASA Astrophysics Data System (ADS)

Wilby, Robert; Greenfield, Brian; Glenny, Cathy

1994-01-01

A coupled atmospheric-hydrological model is presented. Sequences of daily rainfall occurrence for the 20 year period 1971-1990 at sites in the British Isles are related to the Lamb's Weather Types (LWT) by using conditional probabilities. Time series of circulation patterns and hence rainfall were then generated using a Markov representation of matrices of transition probabilities between weather types. The resultant precipitation data were used as input to a semidistributed catchment model to simulate daily flows. The combined model successfully reproduced aspects of the daily weather, precipitation and flow regimes. A range of synoptic scenarios were further investigated with particular reference to low flows in the River Coln, UK. The modelling approach represents a means of translating general circulation model (GCM) climate change predictions at the macro-scale into hydrological concerns at the catchment scale.

Aero-acoustic tests of duct-burning turbofan exhaust nozzles

NASA Technical Reports Server (NTRS)

Kozlowski, H.; Packman, A. B.

1976-01-01

The acoustic and aerodynamic characteristics of several exhaust systems suitable for duct burning turbofan engines are evaluated. Scale models representing unsuppressed coannular exhaust systems are examined statically under varying exhaust conditions. Ejectors with both hardwall and acoustically treated inserts are investigated.

Hierarchical algorithms for modeling the ocean on hierarchical architectures

NASA Astrophysics Data System (ADS)

Hill, C. N.

2012-12-01

This presentation will describe an approach to using accelerator/co-processor technology that maps hierarchical, multi-scale modeling techniques to an underlying hierarchical hardware architecture. The focus of this work is on making effective use of both CPU and accelerator/co-processor parts of a system, for large scale ocean modeling. In the work, a lower resolution basin scale ocean model is locally coupled to multiple, "embedded", limited area higher resolution sub-models. The higher resolution models execute on co-processor/accelerator hardware and do not interact directly with other sub-models. The lower resolution basin scale model executes on the system CPU(s). The result is a multi-scale algorithm that aligns with hardware designs in the co-processor/accelerator space. We demonstrate this approach being used to substitute explicit process models for standard parameterizations. Code for our sub-models is implemented through a generic abstraction layer, so that we can target multiple accelerator architectures with different programming environments. We will present two application and implementation examples. One uses the CUDA programming environment and targets GPU hardware. This example employs a simple non-hydrostatic two dimensional sub-model to represent vertical motion more accurately. The second example uses a highly threaded three-dimensional model at high resolution. This targets a MIC/Xeon Phi like environment and uses sub-models as a way to explicitly compute sub-mesoscale terms. In both cases the accelerator/co-processor capability provides extra compute cycles that allow improved model fidelity for little or no extra wall-clock time cost.

Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system

NASA Astrophysics Data System (ADS)

Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Ochoa-Rodriguez, Susana; Willems, Patrick; Ichiba, Abdellah; Wang, Lipen; Pina, Rui; Van Assel, Johan; Bruni, Guendalina; Murla Tuyls, Damian; ten Veldhuis, Marie-Claire

2017-04-01

Land use distribution and sewer system geometry exhibit complex scale dependent patterns in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. Such features are well grasped with fractal tools, which are based scale invariance and intrinsically designed to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper, they are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries in the framework of the NWE Interreg RainGain project (www.raingain.eu). The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m x 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. It appears that both sewer density and imperviousness exhibit scale invariant features that can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area, consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enables to quantify how well spatial structures of imperviousness are represented in the urban hydrological models.

Characterization of double continuum formulations of transport through pore-scale information

NASA Astrophysics Data System (ADS)

Porta, G.; Ceriotti, G.; Bijeljic, B.

2016-12-01

Information on pore-scale characteristics is becoming increasingly available at unprecedented levels of detail from modern visualization/data-acquisition techniques. These advancements are not completely matched by corresponding developments of operational procedures according to which we can engineer theoretical findings aiming at improving our ability to reduce the uncertainty associated with the outputs of continuum-scale models to be employed at large scales. We present here a modeling approach which rests on pore-scale information to achieve a complete characterization of a double continuum model of transport and fluid-fluid reactive processes. Our model makes full use of pore-scale velocity distributions to identify mobile and immobile regions. We do so on the basis of a pointwise (in the pore space) evaluation of the relative strength of advection and diffusion time scales, as rendered by spatially variable values of local Péclet numbers. After mobile and immobile regions are demarcated, we build a simplified unit cell which is employed as a representative proxy of the real porous domain. This model geometry is then employed to simplify the computation of the effective parameters embedded in the double continuum transport model, while retaining relevant information from the pore-scale characterization of the geometry and velocity field. We document results which illustrate the applicability of the methodology to predict transport of a passive tracer within two- and three-dimensional media upon comparison with direct pore-scale numerical simulation of transport in the same geometrical settings. We also show preliminary results about the extension of this model to fluid-fluid reactive transport processes. In this context, we focus on results obtained in two-dimensional porous systems. We discuss the impact of critical quantities required as input to our modeling approach to obtain continuum-scale outputs. We identify the key limitations of the proposed methodology and discuss its capability also in comparison with alternative approaches grounded, e.g., on nonlocal and particle-based approximations.

Application of regional climate models to the Indian winter monsoon over the western Himalayas.

PubMed

Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

2013-12-01

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

A tri-modular model for the computation of the meteorological and oceanographic fields in the Adriatic Sea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lionello, P.; Pernigotti, D.; Zampato, L.

1994-12-31

The purpose of this research program is the construction of the modelling framework to describe and predict the development of the sea and of the atmosphere in the Adriatic region. There are two time scales that are considered: the medium range time scale of the weather-surge-oceanwave forecast and the interseasonal time scale of the thermohaline circulation in the Adriatic Sea. The phenomenology associated with the medium range is represented by the intense storms that take place in the Adriatic Sea, in spite of its relatively small extension, when the presence of a pressure minimum over Italy generates an intense Sciroccomore » wind which, channeled by the mountain ridges surrounding the basin, blows along its whole length. Because of the long fetch, approximately 1,000 Km., this situation produces high ocean waves and the storm surge that is associated with the flooding of Venice. The interseasonal phenomenology is represented by the formation of dense water in the Northern part of the basin during winter. This is presumably caused by Bora, a strong South-Westerly wind, cold and dry, which produces cooling and evaporation in the shallow water coastal region of the Northern Adriatic. The complex orography surrounding the Adriatic and the short duration of this phenomena require a model framework capable of high space and time resolution on a limited area. This is the motivation for addressing these issues in a coupled model framework consisting of a limited area atmospheric circulation model, an ocean circulation model, and a ocean wave model with high resolution both in space and time.« less

A Small-Scale Comparison of Iceland Scallop Size Distributions Obtained from a Camera Based Autonomous Underwater Vehicle and Dredge Survey

PubMed Central

Singh, Warsha; Örnólfsdóttir, Erla B.; Stefansson, Gunnar

2014-01-01

An approach is developed to estimate size of Iceland scallop shells from AUV photos. A small-scale camera based AUV survey of Iceland scallops was conducted at a defined site off West Iceland. Prior to height estimation of the identified shells, the distortions introduced by the vehicle orientation and the camera lens were corrected. The average AUV pitch and roll was and deg that resulted in error in ground distance rendering these effects negligible. A quadratic polynomial model was identified for lens distortion correction. This model successfully predicted a theoretical grid from a frame photographed underwater, representing the inherent lens distortion. The predicted shell heights were scaled for the distance from the bottom at which the photos were taken. This approach was validated by height estimation of scallops of known sizes. An underestimation of approximately cm was seen, which could be attributed to pixel error, where each pixel represented cm. After correcting for this difference the estimated heights ranged from cm. A comparison of the height-distribution from a small-scale dredge survey carried out in the vicinity showed non-overlapping peaks in size distribution, with scallops of a broader size range visible in the AUV survey. Further investigations are necessary to evaluate any underlying bias and to validate how representative these surveys are of the true population. The low resolution images made identification of smaller scallops difficult. Overall, the observations of very few small scallops in both surveys could be attributed to low recruitment levels in the recent years due to the known scallop parasite outbreak in the region. PMID:25303243

A small-scale comparison of Iceland scallop size distributions obtained from a camera based autonomous underwater vehicle and dredge survey.

PubMed

Singh, Warsha; Örnólfsdóttir, Erla B; Stefansson, Gunnar

2014-01-01

An approach is developed to estimate size of Iceland scallop shells from AUV photos. A small-scale camera based AUV survey of Iceland scallops was conducted at a defined site off West Iceland. Prior to height estimation of the identified shells, the distortions introduced by the vehicle orientation and the camera lens were corrected. The average AUV pitch and roll was 1.3 and 2.3 deg that resulted in <2% error in ground distance rendering these effects negligible. A quadratic polynomial model was identified for lens distortion correction. This model successfully predicted a theoretical grid from a frame photographed underwater, representing the inherent lens distortion. The predicted shell heights were scaled for the distance from the bottom at which the photos were taken. This approach was validated by height estimation of scallops of known sizes. An underestimation of approximately 0.5 cm was seen, which could be attributed to pixel error, where each pixel represented 0.24 x 0.27 cm. After correcting for this difference the estimated heights ranged from 3.8-9.3 cm. A comparison of the height-distribution from a small-scale dredge survey carried out in the vicinity showed non-overlapping peaks in size distribution, with scallops of a broader size range visible in the AUV survey. Further investigations are necessary to evaluate any underlying bias and to validate how representative these surveys are of the true population. The low resolution images made identification of smaller scallops difficult. Overall, the observations of very few small scallops in both surveys could be attributed to low recruitment levels in the recent years due to the known scallop parasite outbreak in the region.

Development and application of a reactive plume-in-grid model: evaluation over Greater Paris

NASA Astrophysics Data System (ADS)

Korsakissok, I.; Mallet, V.

2010-09-01

Emissions from major point sources are badly represented by classical Eulerian models. An overestimation of the horizontal plume dilution, a bad representation of the vertical diffusion as well as an incorrect estimate of the chemical reaction rates are the main limitations of such models in the vicinity of major point sources. The plume-in-grid method is a multiscale modeling technique that couples a local-scale Gaussian puff model with an Eulerian model in order to better represent these emissions. We present the plume-in-grid model developed in the air quality modeling system Polyphemus, with full gaseous chemistry. The model is evaluated on the metropolitan Île-de-France region, during six months (summer 2001). The subgrid-scale treatment is used for 89 major point sources, a selection based on the emission rates of NOx and SO2. Results with and without the subgrid treatment of point emissions are compared, and their performance by comparison to the observations on measurement stations is assessed. A sensitivity study is also carried out, on several local-scale parameters as well as on the vertical diffusion within the urban area. Primary pollutants are shown to be the most impacted by the plume-in-grid treatment. SO2 is the most impacted pollutant, since the point sources account for an important part of the total SO2 emissions, whereas NOx emissions are mostly due to traffic. The spatial impact of the subgrid treatment is localized in the vicinity of the sources, especially for reactive species (NOx and O3). Ozone is mostly sensitive to the time step between two puff emissions which influences the in-plume chemical reactions, whereas the almost-passive species SO2 is more sensitive to the injection time, which determines the duration of the subgrid-scale treatment. Future developments include an extension to handle aerosol chemistry, and an application to the modeling of line sources in order to use the subgrid treatment with road emissions. The latter is expected to lead to more striking results, due to the importance of traffic emissions for the pollutants of interest.

The power of structural modeling of sub-grid scales - application to astrophysical plasmas

NASA Astrophysics Data System (ADS)

Georgiev Vlaykov, Dimitar; Grete, Philipp

2015-08-01

In numerous astrophysical phenomena the dynamical range can span 10s of orders of magnitude. This implies more than billions of degrees-of-freedom and precludes direct numerical simulations from ever being a realistic possibility. A physical model is necessary to capture the unresolved physics occurring at the sub-grid scales (SGS).Structural modeling is a powerful concept which renders itself applicable to various physical systems. It stems from the idea of capturing the structure of the SGS terms in the evolution equations based on the scale-separation mechanism and independently of the underlying physics. It originates in the hydrodynamics field of large-eddy simulations. We apply it to the study of astrophysical MHD.Here, we present a non-linear SGS model for compressible MHD turbulence. The model is validated a priori at the tensorial, vectorial and scalar levels against of set of high-resolution simulations of stochastically forced homogeneous isotropic turbulence in a periodic box. The parameter space spans 2 decades in sonic Mach numbers (0.2 - 20) and approximately one decade in magnetic Mach number ~(1-8). This covers the super-Alfvenic sub-, trans-, and hyper-sonic regimes, with a range of plasma beta from 0.05 to 25. The Reynolds number is of the order of 103.At the tensor level, the model components correlate well with the turbulence ones, at the level of 0.8 and above. Vectorially, the alignment with the true SGS terms is encouraging with more than 50% of the model within 30° of the data. At the scalar level we look at the dynamics of the SGS energy and cross-helicity. The corresponding SGS flux terms have median correlations of ~0.8. Physically, the model represents well the two directions of the energy cascade.In comparison, traditional functional models exhibit poor local correlations with the data already at the scalar level. Vectorially, they are indifferent to the anisotropy of the SGS terms. They often struggle to represent the energy backscatter from small to large scales as well as the turbulent dynamo mechanism.Overall, the new model surpasses the traditional ones in all tests by a large margin.

Generate the scale-free brain music from BOLD signals

PubMed Central

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Abstract Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen–Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon–Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. PMID:29480872

Generate the scale-free brain music from BOLD signals.

PubMed

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Diagnostic evaluation of the Community Earth System Model in simulating mineral dust emission with insight into large-scale dust storm mobilization in the Middle East and North Africa (MENA)

NASA Astrophysics Data System (ADS)

Parajuli, Sagar Prasad; Yang, Zong-Liang; Lawrence, David M.

2016-06-01

Large amounts of mineral dust are injected into the atmosphere during dust storms, which are common in the Middle East and North Africa (MENA) where most of the global dust hotspots are located. In this work, we present simulations of dust emission using the Community Earth System Model Version 1.2.2 (CESM 1.2.2) and evaluate how well it captures the spatio-temporal characteristics of dust emission in the MENA region with a focus on large-scale dust storm mobilization. We explicitly focus our analysis on the model's two major input parameters that affect the vertical mass flux of dust-surface winds and the soil erodibility factor. We analyze dust emissions in simulations with both prognostic CESM winds and with CESM winds that are nudged towards ERA-Interim reanalysis values. Simulations with three existing erodibility maps and a new observation-based erodibility map are also conducted. We compare the simulated results with MODIS satellite data, MACC reanalysis data, AERONET station data, and CALIPSO 3-d aerosol profile data. The dust emission simulated by CESM, when driven by nudged reanalysis winds, compares reasonably well with observations on daily to monthly time scales despite CESM being a global General Circulation Model. However, considerable bias exists around known high dust source locations in northwest/northeast Africa and over the Arabian Peninsula where recurring large-scale dust storms are common. The new observation-based erodibility map, which can represent anthropogenic dust sources that are not directly represented by existing erodibility maps, shows improved performance in terms of the simulated dust optical depth (DOD) and aerosol optical depth (AOD) compared to existing erodibility maps although the performance of different erodibility maps varies by region.

Numerical modelling and experimental study of liquid evaporation during gel formation

NASA Astrophysics Data System (ADS)

Pokusaev, B. G.; Khramtsov, D. P.

2017-11-01

Gels are promising materials in biotechnology and medicine as a medium for storing cells for bioprinting applications. Gel is a two-phase system consisting of solid medium and liquid phase. Understanding of a gel structure evolution and gel aging during liquid evaporation is a crucial step in developing new additive bioprinting technologies. A numerical and experimental study of liquid evaporation was performed. In experimental study an evaporation process of an agarose gel layer located on Petri dish was observed and mass difference was detected using electronic scales. Numerical model was based on a smoothed particle hydrodynamics method. Gel in a model was represented as a solid-liquid system and liquid evaporation was modelled due to capillary forces and heat transfer. Comparison of experimental data and numerical results demonstrated that model can adequately represent evaporation process in agarose gel.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

PubMed

Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David

2018-05-01

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change.

PubMed

Wang, Wen J; He, Hong S; Thompson, Frank R; Spetich, Martin A; Fraser, Jacob S

2018-09-01

Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear -1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates. Copyright © 2018 Elsevier B.V. All rights reserved.

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Qiu, Hong-lie

1998-01-01

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Simulation of the Atmospheric Boundary Layer for Wind Energy Applications

NASA Astrophysics Data System (ADS)

Marjanovic, Nikola

Energy production from wind is an increasingly important component of overall global power generation, and will likely continue to gain an even greater share of electricity production as world governments attempt to mitigate climate change and wind energy production costs decrease. Wind energy generation depends on wind speed, which is greatly influenced by local and synoptic environmental forcings. Synoptic forcing, such as a cold frontal passage, exists on a large spatial scale while local forcing manifests itself on a much smaller scale and could result from topographic effects or land-surface heat fluxes. Synoptic forcing, if strong enough, may suppress the effects of generally weaker local forcing. At the even smaller scale of a wind farm, upstream turbines generate wakes that decrease the wind speed and increase the atmospheric turbulence at the downwind turbines, thereby reducing power production and increasing fatigue loading that may damage turbine components, respectively. Simulation of atmospheric processes that span a considerable range of spatial and temporal scales is essential to improve wind energy forecasting, wind turbine siting, turbine maintenance scheduling, and wind turbine design. Mesoscale atmospheric models predict atmospheric conditions using observed data, for a wide range of meteorological applications across scales from thousands of kilometers to hundreds of meters. Mesoscale models include parameterizations for the major atmospheric physical processes that modulate wind speed and turbulence dynamics, such as cloud evolution and surface-atmosphere interactions. The Weather Research and Forecasting (WRF) model is used in this dissertation to investigate the effects of model parameters on wind energy forecasting. WRF is used for case study simulations at two West Coast North American wind farms, one with simple and one with complex terrain, during both synoptically and locally-driven weather events. The model's performance with different grid nesting configurations, turbulence closures, and grid resolutions is evaluated by comparison to observation data. Improvement to simulation results from the use of more computationally expensive high resolution simulations is only found for the complex terrain simulation during the locally-driven event. Physical parameters, such as soil moisture, have a large effect on locally-forced events, and prognostic turbulence kinetic energy (TKE) schemes are found to perform better than non-local eddy viscosity turbulence closure schemes. Mesoscale models, however, do not resolve turbulence directly, which is important at finer grid resolutions capable of resolving wind turbine components and their interactions with atmospheric turbulence. Large-eddy simulation (LES) is a numerical approach that resolves the largest scales of turbulence directly by separating large-scale, energetically important eddies from smaller scales with the application of a spatial filter. LES allows higher fidelity representation of the wind speed and turbulence intensity at the scale of a wind turbine which parameterizations have difficulty representing. Use of high-resolution LES enables the implementation of more sophisticated wind turbine parameterizations to create a robust model for wind energy applications using grid spacing small enough to resolve individual elements of a turbine such as its rotor blades or rotation area. Generalized actuator disk (GAD) and line (GAL) parameterizations are integrated into WRF to complement its real-world weather modeling capabilities and better represent wind turbine airflow interactions, including wake effects. The GAD parameterization represents the wind turbine as a two-dimensional disk resulting from the rotation of the turbine blades. Forces on the atmosphere are computed along each blade and distributed over rotating, annular rings intersecting the disk. While typical LES resolution (10-20 m) is normally sufficient to resolve the GAD, the GAL parameterization requires significantly higher resolution (1-3 m) as it does not distribute the forces from the blades over annular elements, but applies them along lines representing individual blades. In this dissertation, the GAL is implemented into WRF and evaluated against the GAD parameterization from two field campaigns that measured the inflow and near-wake regions of a single turbine. The data-sets are chosen to allow validation under the weakly convective and weakly stable conditions characterizing most turbine operations. The parameterizations are evaluated with respect to their ability to represent wake wind speed, variance, and vorticity by comparing fine-resolution GAD and GAL simulations along with coarse-resolution GAD simulations. Coarse-resolution GAD simulations produce aggregated wake characteristics similar to both GAD and GAL simulations (saving on computational cost), while the GAL parameterization enables resolution of near wake physics (such as vorticity shedding and wake expansion) for high fidelity applications. (Abstract shortened by ProQuest.).

Predicting Upscaled Behavior of Aqueous Reactants in Heterogeneous Porous Media

NASA Astrophysics Data System (ADS)

Wright, E. E.; Hansen, S. K.; Bolster, D.; Richter, D. H.; Vesselinov, V. V.

2017-12-01

When modeling reactive transport, reaction rates are often overestimated due to the improper assumption of perfect mixing at the support scale of the transport model. In reality, fronts tend to form between participants in thermodynamically favorable reactions, leading to segregation of reactants into islands or fingers. When such a configuration arises, reactions are limited to the interface between the reactive solutes. Closure methods for estimating control-volume-effective reaction rates in terms of quantities defined at the control volume scale do not presently exist, but their development is crucial for effective field-scale modeling. We attack this problem through a combination of analytical and numerical means. Specifically, we numerically study reactive transport through an ensemble of realizations of two-dimensional heterogeneous porous media. We then employ regression analysis to calibrate an analytically-derived relationship between reaction rate and various dimensionless quantities representing conductivity-field heterogeneity and the respective strengths of diffusion, reaction and advection.

Higher-Order Factors of Personality: Do They Exist?

PubMed Central

Ashton, Michael C.; Lee, Kibeom; Goldberg, Lewis R.; de Vries, Reinout E.

2010-01-01

Scales that measure the Big Five personality factors are often substantially intercorrelated. These correlations are sometimes interpreted as implying the existence of two higher-order factors of personality. We show that correlations between measures of broad personality factors do not necessarily imply the existence of higher-order factors, and might instead be due to variables that represent same-signed blends of orthogonal factors. Therefore, the hypotheses of higher-order factors and blended variables can only be tested with data on lower-level personality variables that define the personality factors. We compared the higher-order factor model and the blended variable model in three participant samples using the Big Five Aspect Scales, and found better fit for the latter model. In other analyses using the HEXACO Personality Inventory, we identified mutually uncorrelated markers of six personality factors. We conclude that correlations between personality factor scales can be explained without postulating any higher-order dimensions of personality. PMID:19458345

A PRACTICAL ONTOLOGY FOR THE LARGE-SCALE MODELING OF SCHOLARLY ARTIFACTS AND THEIR USAGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

RODRIGUEZ, MARKO A.; BOLLEN, JOHAN; VAN DE SOMPEL, HERBERT

2007-01-30

The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real worldmore » instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. They present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.« less

Ising Criticality of the Clock Model from Density of States Obtained by the Replica Exchange-Wang-Landau Method

NASA Astrophysics Data System (ADS)

Cadilhe, Antonio

2018-04-01

We performed extensive simulations, using the Replica Exchange-Wang-Landau method, of the clock model for orders 3 and 4 on a square lattice, where critical behaviors are expected to belong to the Ising universality class. Though order 2 represents the Ising model, thus, being exactly solvable in two-dimensions, we still provide such results for comparison to the other two orders. Results for various energy related quantities such as the mean energy per spin, specific heat, as well as logarithm scaling of the peak of the specific heat are presented and shown to follow Ising behavior. Additionally, we also present results related to magnetic quantities, such as the magnetization, magnetic susceptibility, and corresponding scaling behavior of the peak of the magnetic susceptibility. Again, our results show scaling in conformity to Ising critical behavior.

Aerodynamic Performance of a 0.27-Scale Model of an AH-64 Helicopter with Baseline and Alternate Rotor Blade Sets

NASA Technical Reports Server (NTRS)

Kelley, Henry L.

1990-01-01

Performance of a 27 percent scale model rotor designed for the AH-64 helicopter (alternate rotor) was measured in hover and forward flight and compared against and AH-64 baseline rotor model. Thrust, rotor tip Mach number, advance ratio, and ground proximity were varied. In hover, at a nominal thrust coefficient of 0.0064, the power savings was about 6.4 percent for the alternate rotor compared to the baseline. The corresponding thrust increase at this condition was approx. 4.5 percent which represents an equivalent full scale increase in lift capability of about 660 lbs. Comparable results were noted in forward flight except for the high thrust, high speed cases investigated where the baseline rotor was slightly superior. Reduced performance at the higher thrusts and speeds was likely due to Reynolds number effects and blade elasticity differences.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bishop, Joseph E.; Emery, John M.; Battaile, Corbett C.

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cellmore » represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Furthermore, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.« less

Dynamics Under Location Uncertainty: Model Derivation, Modified Transport and Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Resseguier, V.; Memin, E.; Chapron, B.; Fox-Kemper, B.

2017-12-01

In order to better observe and predict geophysical flows, ensemble-based data assimilation methods are of high importance. In such methods, an ensemble of random realizations represents the variety of the simulated flow's likely behaviors. For this purpose, randomness needs to be introduced in a suitable way and physically-based stochastic subgrid parametrizations are promising paths. This talk will propose a new kind of such a parametrization referred to as modeling under location uncertainty. The fluid velocity is decomposed into a resolved large-scale component and an aliased small-scale one. The first component is possibly random but time-correlated whereas the second is white-in-time but spatially-correlated and possibly inhomogeneous and anisotropic. With such a velocity, the material derivative of any - possibly active - tracer is modified. Three new terms appear: a correction of the large-scale advection, a multiplicative noise and a possibly heterogeneous and anisotropic diffusion. This parameterization naturally ensures attractive properties such as energy conservation for each realization. Additionally, this stochastic material derivative and the associated Reynolds' transport theorem offer a systematic method to derive stochastic models. In particular, we will discuss the consequences of the Quasi-Geostrophic assumptions in our framework. Depending on the turbulence amount, different models with different physical behaviors are obtained. Under strong turbulence assumptions, a simplified diagnosis of frontolysis and frontogenesis at the surface of the ocean is possible in this framework. A Surface Quasi-Geostrophic (SQG) model with a weaker noise influence has also been simulated. A single realization better represents small scales than a deterministic SQG model at the same resolution. Moreover, an ensemble accurately predicts extreme events, bifurcations as well as the amplitudes and the positions of the simulation errors. Figure 1 highlights this last result and compares it to the strong error underestimation of an ensemble simulated from the deterministic dynamic with random initial conditions.

Probing Mantle Heterogeneity Across Spatial Scales

NASA Astrophysics Data System (ADS)

Hariharan, A.; Moulik, P.; Lekic, V.

2017-12-01

Inferences of mantle heterogeneity in terms of temperature, composition, grain size, melt and crystal structure may vary across local, regional and global scales. Probing these scale-dependent effects require quantitative comparisons and reconciliation of tomographic models that vary in their regional scope, parameterization, regularization and observational constraints. While a range of techniques like radial correlation functions and spherical harmonic analyses have revealed global features like the dominance of long-wavelength variations in mantle heterogeneity, they have limited applicability for specific regions of interest like subduction zones and continental cratons. Moreover, issues like discrepant 1-D reference Earth models and related baseline corrections have impeded the reconciliation of heterogeneity between various regional and global models. We implement a new wavelet-based approach that allows for structure to be filtered simultaneously in both the spectral and spatial domain, allowing us to characterize heterogeneity on a range of scales and in different geographical regions. Our algorithm extends a recent method that expanded lateral variations into the wavelet domain constructed on a cubed sphere. The isolation of reference velocities in the wavelet scaling function facilitates comparisons between models constructed with arbitrary 1-D reference Earth models. The wavelet transformation allows us to quantify the scale-dependent consistency between tomographic models in a region of interest and investigate the fits to data afforded by heterogeneity at various dominant wavelengths. We find substantial and spatially varying differences in the spectrum of heterogeneity between two representative global Vp models constructed using different data and methodologies. Applying the orthonormality of the wavelet expansion, we isolate detailed variations in velocity from models and evaluate additional fits to data afforded by adding such complexities to long-wavelength variations. Our method provides a way to probe and evaluate localized features in a multi-scale description of mantle heterogeneity.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Effect of Logarithmic and Linear Frequency Scales on Parametric Modelling of Tissue Dielectric Data.

PubMed

Salahuddin, Saqib; Porter, Emily; Meaney, Paul M; O'Halloran, Martin

2017-02-01

The dielectric properties of biological tissues have been studied widely over the past half-century. These properties are used in a vast array of applications, from determining the safety of wireless telecommunication devices to the design and optimisation of medical devices. The frequency-dependent dielectric properties are represented in closed-form parametric models, such as the Cole-Cole model, for use in numerical simulations which examine the interaction of electromagnetic (EM) fields with the human body. In general, the accuracy of EM simulations depends upon the accuracy of the tissue dielectric models. Typically, dielectric properties are measured using a linear frequency scale; however, use of the logarithmic scale has been suggested historically to be more biologically descriptive. Thus, the aim of this paper is to quantitatively compare the Cole-Cole fitting of broadband tissue dielectric measurements collected with both linear and logarithmic frequency scales. In this way, we can determine if appropriate choice of scale can minimise the fit error and thus reduce the overall error in simulations. Using a well-established fundamental statistical framework, the results of the fitting for both scales are quantified. It is found that commonly used performance metrics, such as the average fractional error, are unable to examine the effect of frequency scale on the fitting results due to the averaging effect that obscures large localised errors. This work demonstrates that the broadband fit for these tissues is quantitatively improved when the given data is measured with a logarithmic frequency scale rather than a linear scale, underscoring the importance of frequency scale selection in accurate wideband dielectric modelling of human tissues.

Effect of Logarithmic and Linear Frequency Scales on Parametric Modelling of Tissue Dielectric Data

PubMed Central

Salahuddin, Saqib; Porter, Emily; Meaney, Paul M.; O’Halloran, Martin

2016-01-01

The dielectric properties of biological tissues have been studied widely over the past half-century. These properties are used in a vast array of applications, from determining the safety of wireless telecommunication devices to the design and optimisation of medical devices. The frequency-dependent dielectric properties are represented in closed-form parametric models, such as the Cole-Cole model, for use in numerical simulations which examine the interaction of electromagnetic (EM) fields with the human body. In general, the accuracy of EM simulations depends upon the accuracy of the tissue dielectric models. Typically, dielectric properties are measured using a linear frequency scale; however, use of the logarithmic scale has been suggested historically to be more biologically descriptive. Thus, the aim of this paper is to quantitatively compare the Cole-Cole fitting of broadband tissue dielectric measurements collected with both linear and logarithmic frequency scales. In this way, we can determine if appropriate choice of scale can minimise the fit error and thus reduce the overall error in simulations. Using a well-established fundamental statistical framework, the results of the fitting for both scales are quantified. It is found that commonly used performance metrics, such as the average fractional error, are unable to examine the effect of frequency scale on the fitting results due to the averaging effect that obscures large localised errors. This work demonstrates that the broadband fit for these tissues is quantitatively improved when the given data is measured with a logarithmic frequency scale rather than a linear scale, underscoring the importance of frequency scale selection in accurate wideband dielectric modelling of human tissues. PMID:28191324

Land use and climate affect Black Tern, Northern Harrier, and Marsh Wren abundance in the Prairie Pothole Region of the United States

USGS Publications Warehouse

Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.

2014-01-01

Bird populations are influenced by many environmental factors at both large and small scales. Our study evaluated the influences of regional climate and land-use variables on the Northern Harrier (Circus cyaneus), Black Tern (Childonias niger), and Marsh Wren (Cistothorus palustris) in the prairie potholes of the upper Midwest of the United States. These species were chosen because their diverse habitat preference represent the spectrum of habitat conditions present in the Prairie Potholes, ranging from open prairies to dense cattail marshes. We evaluated land-use covariates at three logarithmic spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and constructed models a priori using information from published habitat associations and climatic influences. The strongest influences on the abundance of each of the three species were the percentage of wetland area across all three spatial scales and precipitation in the year preceding that when bird surveys were conducted. Even among scales ranging over three orders of magnitude the influence of spatial scale was small, as models with the same variables expressed at different scales were often in the best model subset. Examination of the effects of large-scale environmental variables on wetland birds elucidated relationships overlooked in many smaller-scale studies, such as the influences of climate and habitat variables at landscape scales. Given the spatial variation in the abundance of our focal species within the prairie potholes, our model predictions are especially useful for targeting locations, such as northeastern South Dakota and central North Dakota, where management and conservation efforts would be optimally beneficial. This modeling approach can also be applied to other species and geographic areas to focus landscape conservation efforts and subsequent small-scale studies, especially in constrained economic climates.

An Evaluation Tool for CONUS-Scale Estimates of Components of the Water Balance

NASA Astrophysics Data System (ADS)

Saxe, S.; Hay, L.; Farmer, W. H.; Markstrom, S. L.; Kiang, J. E.

2016-12-01

Numerous research groups are independently developing data products to represent various components of the water balance (e.g. runoff, evapotranspiration, recharge, snow water equivalent, soil moisture, and climate) at the scale of the conterminous United States. These data products are derived from a range of sources, including direct measurement, remotely-sensed measurement, and statistical and deterministic model simulations. An evaluation tool is needed to compare these data products and the components of the water balance they contain in order to identify the gaps in the understanding and representation of continental-scale hydrologic processes. An ideal tool will be an objective, universally agreed upon, framework to address questions related to closing the water balance. This type of generic, model agnostic evaluation tool would facilitate collaboration amongst different hydrologic research groups and improve modeling capabilities with respect to continental-scale water resources. By adopting a comprehensive framework to consider hydrologic modeling in the context of a complete water balance, it is possible to identify weaknesses in process modeling, data product representation and regional hydrologic variation. As part of its National Water Census initiative, the U.S. Geological survey is facilitating this dialogue to developing prototype evaluation tools.

CO 2 Leakage Into Shallow Aquifers: Modeling CO 2 Gas Evolution and Accumulation at Interfaces of Heterogeneity

DOE PAGES

Porter, Mark L.; Plampin, Michael; Pawar, Rajesh; ...

2014-12-31

The physicochemical processes associated with CO 2 leakage into shallow aquifer systems are complex and span multiple spatial and time scales. Continuum-scale numerical models that faithfully represent the underlying pore-scale physics are required to predict the long-term behavior and aid in risk analysis regarding regulatory and management decisions. This study focuses on benchmarking the numerical simulator, FEHM, with intermediate-scale column experiments of CO 2 gas evolution in homogeneous and heterogeneous sand configurations. Inverse modeling was conducted to calibrate model parameters and determine model sensitivity to the observed steady-state saturation profiles. It is shown that FEHM is a powerful tool thatmore » is capable of capturing the experimentally observed out ow rates and saturation profiles. Moreover, FEHM captures the transition from single- to multi-phase flow and CO 2 gas accumulation at interfaces separating sands. We also derive a simple expression, based on Darcy's law, for the pressure at which CO 2 free phase gas is observed and show that it reliably predicts the location at which single-phase flow transitions to multi-phase flow.« less

Posttest Analyses of the Steel Containment Vessel Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costello, J.F.; Hessheimer, M.F.; Ludwigsen, J.S.

A high pressure test of a scale model of a steel containment vessel (SCV) was conducted on December 11-12, 1996 at Sandia National Laboratories, Albuquerque, NM, USA. The test model is a mixed-scaled model (1:10 in geometry and 1:4 in shell thickness) of an improved Mark II boiling water reactor (BWR) containment. This testis part of a program to investigate the response of representative models of nuclear containment structures to pressure loads beyond the design basis accident. The posttest analyses of this test focused on three areas where the pretest analysis effort did not adequately predict the model behavior duringmore » the test. These areas are the onset of global yielding, the strain concentrations around the equipment hatch and the strain concentrations that led to a small tear near a weld relief opening that was not modeled in the pretest analysis.« less

Back to "the Future": Evidence of a Bifactor Solution for Scores on the Consideration of Future Consequences Scale.

PubMed

McKay, Michael T; Morgan, Grant B; van Exel, N Job; Worrell, Frank C

2015-01-01

Despite its widespread use, disagreement remains regarding the structure of the Consideration of Future Consequences Scale (CFCS). In particular there is disagreement regarding whether the scale assesses future orientation as a unidimensional or multidimensional (immediate and future) construct. Using 2 samples of high school students in the United Kingdom, 4 models were tested. The totality of results including item loadings, goodness-of-fit indexes, and reliability estimates all supported the bifactor model, suggesting that the 2 hypothesized factors are better understood as grouping or method factors rather than as representative of latent constructs. Accordingly this study supports the unidimensionality of the CFCS and the scoring of all 12 items to produce a global future orientation score. Researchers intending to use the CFCS, and those with existing data, are encouraged to examine a bifactor solution for the scale.

Postinflationary Higgs relaxation and the origin of matter-antimatter asymmetry.

PubMed

Kusenko, Alexander; Pearce, Lauren; Yang, Louis

2015-02-13

The recent measurement of the Higgs boson mass implies a relatively slow rise of the standard model Higgs potential at large scales, and a possible second minimum at even larger scales. Consequently, the Higgs field may develop a large vacuum expectation value during inflation. The relaxation of the Higgs field from its large postinflationary value to the minimum of the effective potential represents an important stage in the evolution of the Universe. During this epoch, the time-dependent Higgs condensate can create an effective chemical potential for the lepton number, leading to a generation of the lepton asymmetry in the presence of some large right-handed Majorana neutrino masses. The electroweak sphalerons redistribute this asymmetry between leptons and baryons. This Higgs relaxation leptogenesis can explain the observed matter-antimatter asymmetry of the Universe even if the standard model is valid up to the scale of inflation, and any new physics is suppressed by that high scale.

Virtual Patterson Experiment - A Way to Access the Rheology of Aggregates and Melanges

NASA Astrophysics Data System (ADS)

Delannoy, Thomas; Burov, Evgueni; Wolf, Sylvie

2014-05-01

Understanding the mechanisms of lithospheric deformation requires bridging the gap between human-scale laboratory experiments and the huge geological objects they represent. Those experiments are limited in spatial and time scale as well as in choice of materials (e.g., mono-phase minerals, exaggerated temperatures and strain rates), which means that the resulting constitutive laws may not fully represent real rocks at geological spatial and temporal scales. We use the thermo-mechanical numerical modelling approach as a tool to link both experiments and nature and hence better understand the rheology of the lithosphere, by enabling us to study the behavior of polymineralic aggregates and their impact on the localization of the deformation. We have adapted the large strain visco-elasto-plastic Flamar code to allow it to operate at all spatial and temporal scales, from sub-grain to geodynamic scale, and from seismic time scales to millions of years. Our first goal was to reproduce real rock mechanics experiments on deformation of mono and polymineralic aggregates in Patterson's load machine in order to deepen our understanding of the rheology of polymineralic rocks. In particular, we studied in detail the deformation of a 15x15 mm mica-quartz sample at 750 °C and 300 MPa. This mixture includes a molten phase and a solid phase in which shear bands develop as a result of interactions between ductile and brittle deformation and stress concentration at the boundaries between weak and strong phases. We used digitized x-ray scans of real samples as initial configuration for the numerical models so the model-predicted deformation and stress-strain behavior can match those observed in the laboratory experiment. Analyzing the numerical experiments providing the best match with the press experiments and making other complementary models by changing different parameters in the initial state (strength contrast between the phases, proportions, microstructure, etc.) provides a number of new elements of understanding of the mechanisms governing the localization of the deformation across the aggregates. We next used stress-strain curves derived from the numerical experiments to study in detail the evolution of the rheological behavior of each mineral phase as well as that of the mixtures in order to formulate constitutive relations for mélanges and polymineralic aggregates. The next step of our approach would be to link the constitutive laws obtained at small scale (laws that govern the rheology of a polymineralic aggregate, the effect of the presence of a molten phase, etc.) to the large-scale behavior of the Earth by implementing them in lithosphere-scale models.

"The Effect of Alternative Representations of Lake Temperatures and Ice on WRF Regional Climate Simulations"

EPA Science Inventory

Lakes can play a significant role in regional climate, modulating inland extremes in temperature and enhancing precipitation. Representing these effects becomes more important as regional climate modeling (RCM) efforts focus on simulating smaller scales. When using the Weathe...

Roughness configuration matters for aeolian sediment flux

USDA-ARS?s Scientific Manuscript database

The parameterisation of surface roughness effects on aeolian sediment transport is a key source of uncertainty in wind erosion models. Roughness effects are typically represented by bulk drag-partitioning schemes that scale the threshold friction velocity (u*t) for soil entrainment by the ratio of s...

Impact of model complexity and multi-scale data integration on the estimation of hydrogeological parameters in a dual-porosity aquifer

NASA Astrophysics Data System (ADS)

Tamayo-Mas, Elena; Bianchi, Marco; Mansour, Majdi

2018-03-01

This study investigates the impact of model complexity and multi-scale prior hydrogeological data on the interpretation of pumping test data in a dual-porosity aquifer (the Chalk aquifer in England, UK). In order to characterize the hydrogeological properties, different approaches ranging from a traditional analytical solution (Theis approach) to more sophisticated numerical models with automatically calibrated input parameters are applied. Comparisons of results from the different approaches show that neither traditional analytical solutions nor a numerical model assuming a homogenous and isotropic aquifer can adequately explain the observed drawdowns. A better reproduction of the observed drawdowns in all seven monitoring locations is instead achieved when medium and local-scale prior information about the vertical hydraulic conductivity (K) distribution is used to constrain the model calibration process. In particular, the integration of medium-scale vertical K variations based on flowmeter measurements lead to an improvement in the goodness-of-fit of the simulated drawdowns of about 30%. Further improvements (up to 70%) were observed when a simple upscaling approach was used to integrate small-scale K data to constrain the automatic calibration process of the numerical model. Although the analysis focuses on a specific case study, these results provide insights about the representativeness of the estimates of hydrogeological properties based on different interpretations of pumping test data, and promote the integration of multi-scale data for the characterization of heterogeneous aquifers in complex hydrogeological settings.

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE PAGES

Fierce, Laura; McGraw, Robert L.

2017-07-26

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fierce, Laura; McGraw, Robert L.

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

A fusion of top-down and bottom-up modeling techniques to constrain regional scale carbon budgets

NASA Astrophysics Data System (ADS)

Goeckede, M.; Turner, D. P.; Michalak, A. M.; Vickers, D.; Law, B. E.

2009-12-01

The effort to constrain regional scale carbon budgets benefits from assimilating as many high quality data sources as possible in order to reduce uncertainties. Two of the most common approaches used in this field, bottom-up and top-down techniques, both have their strengths and weaknesses, and partly build on very different sources of information to train, drive, and validate the models. Within the context of the ORCA2 project, we follow both bottom-up and top-down modeling strategies with the ultimate objective of reconciling their surface flux estimates. The ORCA2 top-down component builds on a coupled WRF-STILT transport module that resolves the footprint function of a CO2 concentration measurement in high temporal and spatial resolution. Datasets involved in the current setup comprise GDAS meteorology, remote sensing products, VULCAN fossil fuel inventories, boundary conditions from CarbonTracker, and high-accuracy time series of atmospheric CO2 concentrations. Surface fluxes of CO2 are normally provided through a simple diagnostic model which is optimized against atmospheric observations. For the present study, we replaced the simple model with fluxes generated by an advanced bottom-up process model, Biome-BGC, which uses state-of-the-art algorithms to resolve plant-physiological processes, and 'grow' a biosphere based on biogeochemical conditions and climate history. This approach provides a more realistic description of biomass and nutrient pools than is the case for the simple model. The process model ingests various remote sensing data sources as well as high-resolution reanalysis meteorology, and can be trained against biometric inventories and eddy-covariance data. Linking the bottom-up flux fields to the atmospheric CO2 concentrations through the transport module allows evaluating the spatial representativeness of the BGC flux fields, and in that way assimilates more of the available information than either of the individual modeling techniques alone. Bayesian inversion is then applied to assign scaling factors that align the surface fluxes with the CO2 time series. Our project demonstrates how bottom-up and top-down techniques can be reconciled to arrive at a more robust and balanced spatial carbon budget. We will show how to evaluate existing flux products through regionally representative atmospheric observations, i.e. how well the underlying model assumptions represent processes on the regional scale. Adapting process model parameterizations sets for e.g. sub-regions, disturbance regimes, or land cover classes, in order to optimize the agreement between surface fluxes and atmospheric observations can lead to improved understanding of the underlying flux mechanisms, and reduces uncertainties in the regional carbon budgets.

Three-dimensional hydrogeologic framework model of the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico

USGS Publications Warehouse

Sweetkind, Donald S.

2017-09-08

As part of a U.S. Geological Survey study in cooperation with the Bureau of Reclamation, a digital three-dimensional hydrogeologic framework model was constructed for the Rio Grande transboundary region of New Mexico and Texas, USA, and northern Chihuahua, Mexico. This model was constructed to define the aquifer system geometry and subsurface lithologic characteristics and distribution for use in a regional numerical hydrologic model. The model includes five hydrostratigraphic units: river channel alluvium, three informal subdivisions of Santa Fe Group basin fill, and an undivided pre-Santa Fe Group bedrock unit. Model input data were compiled from published cross sections, well data, structure contour maps, selected geophysical data, and contiguous compilations of surficial geology and structural features in the study area. These data were used to construct faulted surfaces that represent the upper and lower subsurface hydrostratigraphic unit boundaries. The digital three-dimensional hydrogeologic framework model is constructed through combining faults, the elevation of the tops of each hydrostratigraphic unit, and boundary lines depicting the subsurface extent of each hydrostratigraphic unit. The framework also compiles a digital representation of the distribution of sedimentary facies within each hydrostratigraphic unit. The digital three-dimensional hydrogeologic model reproduces with reasonable accuracy the previously published subsurface hydrogeologic conceptualization of the aquifer system and represents the large-scale geometry of the subsurface aquifers. The model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

Genome Informed Trait-Based Models

NASA Astrophysics Data System (ADS)

Karaoz, U.; Cheng, Y.; Bouskill, N.; Tang, J.; Beller, H. R.; Brodie, E.; Riley, W. J.

2013-12-01

Trait-based approaches are powerful tools for representing microbial communities across both spatial and temporal scales within ecosystem models. Trait-based models (TBMs) represent the diversity of microbial taxa as stochastic assemblages with a distribution of traits constrained by trade-offs between these traits. Such representation with its built-in stochasticity allows the elucidation of the interactions between the microbes and their environment by reducing the complexity of microbial community diversity into a limited number of functional ';guilds' and letting them emerge across spatio-temporal scales. From the biogeochemical/ecosystem modeling perspective, the emergent properties of the microbial community could be directly translated into predictions of biogeochemical reaction rates and microbial biomass. The accuracy of TBMs depends on the identification of key traits of the microbial community members and on the parameterization of these traits. Current approaches to inform TBM parameterization are empirical (i.e., based on literature surveys). Advances in omic technologies (such as genomics, metagenomics, metatranscriptomics, and metaproteomics) pave the way to better-initialize models that can be constrained in a generic or site-specific fashion. Here we describe the coupling of metagenomic data to the development of a TBM representing the dynamics of metabolic guilds from an organic carbon stimulated groundwater microbial community. Illumina paired-end metagenomic data were collected from the community as it transitioned successively through electron-accepting conditions (nitrate-, sulfate-, and Fe(III)-reducing), and used to inform estimates of growth rates and the distribution of metabolic pathways (i.e., aerobic and anaerobic oxidation, fermentation) across a spatially resolved TBM. We use this model to evaluate the emergence of different metabolisms and predict rates of biogeochemical processes over time. We compare our results to observational outputs.

Methods of testing parameterizations: Vertical ocean mixing

NASA Technical Reports Server (NTRS)

Tziperman, Eli

1992-01-01

The ocean's velocity field is characterized by an exceptional variety of scales. While the small-scale oceanic turbulence responsible for the vertical mixing in the ocean is of scales a few centimeters and smaller, the oceanic general circulation is characterized by horizontal scales of thousands of kilometers. In oceanic general circulation models that are typically run today, the vertical structure of the ocean is represented by a few tens of discrete grid points. Such models cannot explicitly model the small-scale mixing processes, and must, therefore, find ways to parameterize them in terms of the larger-scale fields. Finding a parameterization that is both reliable and plausible to use in ocean models is not a simple task. Vertical mixing in the ocean is the combined result of many complex processes, and, in fact, mixing is one of the less known and less understood aspects of the oceanic circulation. In present models of the oceanic circulation, the many complex processes responsible for vertical mixing are often parameterized in an oversimplified manner. Yet, finding an adequate parameterization of vertical ocean mixing is crucial to the successful application of ocean models to climate studies. The results of general circulation models for quantities that are of particular interest to climate studies, such as the meridional heat flux carried by the ocean, are quite sensitive to the strength of the vertical mixing. We try to examine the difficulties in choosing an appropriate vertical mixing parameterization, and the methods that are available for validating different parameterizations by comparing model results to oceanographic data. First, some of the physical processes responsible for vertically mixing the ocean are briefly mentioned, and some possible approaches to the parameterization of these processes in oceanographic general circulation models are described in the following section. We then discuss the role of the vertical mixing in the physics of the large-scale ocean circulation, and examine methods of validating mixing parameterizations using large-scale ocean models.

Macro Scale Independently Homogenized Subcells for Modeling Braided Composites

NASA Technical Reports Server (NTRS)

Blinzler, Brina J.; Goldberg, Robert K.; Binienda, Wieslaw K.

2012-01-01

An analytical method has been developed to analyze the impact response of triaxially braided carbon fiber composites, including the penetration velocity and impact damage patterns. In the analytical model, the triaxial braid architecture is simulated by using four parallel shell elements, each of which is modeled as a laminated composite. Currently, each shell element is considered to be a smeared homogeneous material. The commercial transient dynamic finite element code LS-DYNA is used to conduct the simulations, and a continuum damage mechanics model internal to LS-DYNA is used as the material constitutive model. To determine the stiffness and strength properties required for the constitutive model, a top-down approach for determining the strength properties is merged with a bottom-up approach for determining the stiffness properties. The top-down portion uses global strengths obtained from macro-scale coupon level testing to characterize the material strengths for each subcell. The bottom-up portion uses micro-scale fiber and matrix stiffness properties to characterize the material stiffness for each subcell. Simulations of quasi-static coupon level tests for several representative composites are conducted along with impact simulations.

A Decade-long Continental-Scale Convection-Resolving Climate Simulation on GPUs

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph

2016-04-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. Using horizontal grid spacings of O(1km), they allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer-designs that involve conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation using the GPU-enabled COSMO version. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss the performance of the convection-resolving modeling approach on the European scale. Specifically we focus on the annual cycle of convection in Europe, on the organization of convective clouds and on the verification of hourly rainfall with various high resolution datasets.

Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Fewtrell, Timothy J.; Duncan, Alastair; Sampson, Christopher C.; Neal, Jeffrey C.; Bates, Paul D.

2011-01-01

This paper describes benchmark testing of a diffusive and an inertial formulation of the de St. Venant equations implemented within the LISFLOOD-FP hydraulic model using high resolution terrestrial LiDAR data. The models are applied to a hypothetical flooding scenario in a section of Alcester, UK which experienced significant surface water flooding in the June and July floods of 2007 in the UK. The sensitivity of water elevation and velocity simulations to model formulation and grid resolution are analyzed. The differences in depth and velocity estimates between the diffusive and inertial approximations are within 10% of the simulated value but inertial effects persist at the wetting front in steep catchments. Both models portray a similar scale dependency between 50 cm and 5 m resolution which reiterates previous findings that errors in coarse scale topographic data sets are significantly larger than differences between numerical approximations. In particular, these results confirm the need to distinctly represent the camber and curbs of roads in the numerical grid when simulating surface water flooding events. Furthermore, although water depth estimates at grid scales coarser than 1 m appear robust, velocity estimates at these scales seem to be inconsistent compared to the 50 cm benchmark. The inertial formulation is shown to reduce computational cost by up to three orders of magnitude at high resolutions thus making simulations at this scale viable in practice compared to diffusive models. For the first time, this paper highlights the utility of high resolution terrestrial LiDAR data to inform small-scale flood risk management studies.

Construction and Operation Costs of Wastewater Treatment and Implications for the Paper Industry in China.

PubMed

Niu, Kunyu; Wu, Jian; Yu, Fang; Guo, Jingli

2016-11-15

This paper aims to develop a construction and operation cost model of wastewater treatment for the paper industry in China and explores the main factors that determine these costs. Previous models mainly involved factors relating to the treatment scale and efficiency of treatment facilities for deriving the cost function. We considered the factors more comprehensively by adding a regional variable to represent the economic development level, a corporate ownership factor to represent the plant characteristics, a subsector variable to capture pollutant characteristics, and a detailed-classification technology variable. We applied a unique data set from a national pollution source census for the model simulation. The major findings include the following: (1) Wastewater treatment costs in the paper industry are determined by scale, technology, degree of treatment, ownership, and regional factors; (2) Wastewater treatment costs show a large decreasing scale effect; (3) The current level of pollutant discharge fees is far lower than the marginal treatment costs for meeting the wastewater discharge standard. Key implications are as follows: (1) Cost characteristics and impact factors should be fully recognized when planning or making policies relating to wastewater treatment projects or technology development; (2) There is potential to reduce treatment costs by centralizing wastewater treatment via industrial parks; (3) Wastewater discharge fee rates should be increased; (4) Energy efficient technology should become the future focus of wastewater treatment.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Monte Carlo simulation of turnover processes in the lunar regolith

NASA Technical Reports Server (NTRS)

Arnold, J. R.

1975-01-01

A Monte Carlo model for the gardening of the lunar surface by meteoritic impact is described, and some representative results are given. The model accounts with reasonable success for a wide variety of properties of the regolith. The smoothness of the lunar surface on a scale of centimeters to meters, which was not reproduced in an earlier version of the model, is accounted for by the preferential downward movement of low-energy secondary particles. The time scale for filling lunar grooves and craters by this process is also derived. The experimental bombardment ages (about 4 x 10 to the 8th yr for spallogenic rare gases, about 10 to the 9th yr for neutron capture Gd and Sm isotopes) are not reproduced by the model. The explanation is not obvious.

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

DOE PAGES

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

2018-04-02

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Generalized linear mixed models with varying coefficients for longitudinal data.

PubMed

Zhang, Daowen

2004-03-01

The routinely assumed parametric functional form in the linear predictor of a generalized linear mixed model for longitudinal data may be too restrictive to represent true underlying covariate effects. We relax this assumption by representing these covariate effects by smooth but otherwise arbitrary functions of time, with random effects used to model the correlation induced by among-subject and within-subject variation. Due to the usually intractable integration involved in evaluating the quasi-likelihood function, the double penalized quasi-likelihood (DPQL) approach of Lin and Zhang (1999, Journal of the Royal Statistical Society, Series B61, 381-400) is used to estimate the varying coefficients and the variance components simultaneously by representing a nonparametric function by a linear combination of fixed effects and random effects. A scaled chi-squared test based on the mixed model representation of the proposed model is developed to test whether an underlying varying coefficient is a polynomial of certain degree. We evaluate the performance of the procedures through simulation studies and illustrate their application with Indonesian children infectious disease data.

Scale-dependency of effective hydraulic conductivity on fire-affected hillslopes

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Lane, Patrick N. J.; Nyman, Petter; Noske, Philip J.; Cawson, Jane G.; Oono, Akiko; Sheridan, Gary J.

2016-07-01

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution (KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire-affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment-scale estimates. Furthermore, the distribution of Ks was not clearly log-normal and scale-independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply-limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.