Carbon Capture Simulation Initiative: A Case Study in Multi-Scale Modeling and New Challenges
Miller, David; Syamlal, Madhava; Mebane, David; Storlie, Curtis; Bhattacharyya, Debangsu; Sahinidis, Nikolaos V.; Agarwal, Deborah A.; Tong, Charles; Zitney, Stephen E.; Sarkar, Avik; Sun, Xin; Sundaresan, Sankaran; Ryan, Emily M.; Engel, David W.; Dale, Crystal
2014-04-01
Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry and universities that is developing and deploying a suite of multi-scale modeling and simulation tools including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamic (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.
Carbon Capture Simulation Initiative: A Case Study in Multi-Scale Modeling and New Challenges
Miller, David C; Syamlal, Madhava; Zitney, Stephen E.
2014-06-07
Abstract: Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry and universities that is developing and deploying a suite of multi-scale modeling and simulation tools including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamic (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.
Plank, G; Prassl, AJ; Augustin, C
2014-01-01
Despite the evident multiphysics nature of the heart – it is an electrically controlled mechanical pump – most modeling studies considered electrophysiology and mechanics in isolation. In no small part, this is due to the formidable modeling challenges involved in building strongly coupled anatomically accurate and biophyically detailed multi-scale multi-physics models of cardiac electro-mechanics. Among the main challenges are the selection of model components and their adjustments to achieve integration into a consistent organ-scale model, dealing with technical difficulties such as the exchange of data between electro-physiological and mechanical model, particularly when using different spatio-temporal grids for discretization, and, finally, the implementation of advanced numerical techniques to deal with the substantial computational. In this study we report on progress made in developing a novel modeling framework suited to tackle these challenges. PMID:24043050
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
NASA Astrophysics Data System (ADS)
Wilson, C. R.; Kramer, S. C.; Collins, G. S.
2010-12-01
Linear wave models cannot reproduce the highly nonlinear generation mechanisms required to accurately predict the consequences of landslide-generated tsunamis. Models based on the nonlinear Navier-Stokes equations can simulate complex landslide-water interactions at realistic scales; however, the computing power required for such a simulation can be prohibitively high for large domains with realistic bathymetries. The variable resolution available with the use of unstructured adaptive meshes allows larger domains to be modeled at the same resolution for a lower computational cost than on structured meshes; they are also better at representing complex geometries and bathymetries. However, unstructured meshes introduce extra numerical challenges requiring the use of novel interface preservation techniques coupled with velocity-pressure discretisations that ensure the conservation and boundedness of all materials in the simulation. In this study we describe some of the challenges encountered extending the finite element, finite volume multiple-material fluid dynamics model Fluidity to large-scale landslide-generated tsunami simulations. In particular, we focus on the ability of the model to preserve the balance between the buoyancy and pressure gradient forces. Failure to discretely satisfy this relationship is shown to result in spurious waves that contaminate any physical tsunami signal. However, ensuring that balance is preserved in a computationally efficient manner imposes extra constraints on the dynamic mesh optimisation process. Incorporating these restrictions allows us to validate our model against multi-scale experimental simulations of landslide generated tsunami (see figure). Experimental (top, taken from Di Risio et. al. 2009, doi:10.1029/2008JC004858) and equivalent numerical simulation (bottom) of a subaerial landslide impacting into water. In the experiment the 80cm long landslide produces waves of amplitude 1-2cm around a 9m diameter island in a 50x
NASA Astrophysics Data System (ADS)
Kim, Jongho; Ivanov, Valeriy Y.
2015-03-01
We present a state-of-the-art holistic, multi-scale dynamic downscaling approach suited to address climate change impacts on hydrologic metrics and hydraulic regime of surface flow at the "scale of human decisions" in ungauged basins. The framework rests on stochastic and physical downscaling techniques that permit one-way crossing 106-100 m scales, with a specific emphasis on 'nesting' hydraulic assessments within a coarser-scale hydrologic model. Future climate projections for the location of Manchester watershed (MI) are obtained from an ensemble of General Circulation Models of the 3rd phase of the Coupled Model Intercomparison Project database and downscaled to a "point" scale using a weather generator. To represent the natural variability of historic and future climates, we generated continuous time series of 300 years for the locations of 3 meteorological stations located in the vicinity of the ungauged basin. To make such a multi-scale approach computationally feasible, we identified the months of May and August as the periods of specific interest based on ecohydrologic considerations. Analyses of historic and future simulation results for the identified periods show that the same median rainfall obtained by accounting for climate natural variability triggers hydrologically-mediated non-uniqueness in flow variables resolved at the hydraulic scale. An emerging challenge is that uncertainty initiated at the hydrologic scale is not necessarily preserved at smaller-scale flow variables, because of non-linearity of underlying physical processes, which ultimately can mask climate uncertainty. We stress the necessity of augmenting climate-level uncertainties of emission scenario, multi-model, and natural variability with uncertainties arising due to non-linearities in smaller-scale processes.
Multi-Scale Infrastructure Assessment
The U.S. Environmental Protection Agency’s (EPA) multi-scale infrastructure assessment project supports both water resource adaptation to climate change and the rehabilitation of the nation’s aging water infrastructure by providing tools, scientific data and information to progra...
Energy Science and Technology Software Center (ESTSC)
2009-08-01
The code to be released is a new addition to the LAMMPS molecular dynamics code. LAMMPS is developed and maintained by Sandia, is publicly available, and is used widely by both natioanl laboratories and academics. The new addition to be released enables LAMMPS to perform molecular dynamics simulations of shock waves using the Multi-scale Shock Simulation Technique (MSST) which we have developed and has been previously published. This technique enables molecular dynamics simulations of shockmore » waves in materials for orders of magnitude longer timescales than the direct, commonly employed approach.« less
The Adaptive Multi-scale Simulation Infrastructure
Tobin, William R.
2015-09-01
The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
A framework for multi-scale modelling
Chopard, B.; Borgdorff, Joris; Hoekstra, A. G.
2014-01-01
We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology. PMID:24982249
Simulating and mapping spatial complexity using multi-scale techniques
De Cola, L.
1994-01-01
A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author
Construction of Multi-Scale Consistent Brain Networks: Methods and Applications
Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming
2015-01-01
Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data. PMID:25876038
Construction of multi-scale consistent brain networks: methods and applications.
Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming
2015-01-01
Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data. PMID:25876038
Functional derivatives for multi-scale modeling
NASA Astrophysics Data System (ADS)
Reeve, Samuel; Strachan, Alejandro
2015-03-01
As we look beyond petascale computing and towards the exascale, effectively utilizing computational resources by using multi-fidelity and multi-scale materials simulations becomes increasingly important. Determining when and where to run high-fidelity simulations in order to have the most effect on a given quantity of interest (QoI) is a difficult problem. This work utilizes functional uncertainty quantification (UQ) for this task. While most UQ focuses on uncertainty in output from uncertainty in input parameters, we focus on uncertainty from the function itself (e.g. from using a specific functional form for an interatomic potential or constitutive law). In the case of a multi-scale simulation with a given constitutive law, calculating the functional derivative of the QoI with respect to that constitutive law can determine where a fine-scale model evaluation will maximize the increase in accuracy of the predicted QoI. Additionally, for a given computational budget the optimal set of coarse and fine-scale simulations can be determined. Numerical calculation of the functional derivative has been developed and methods of including this work within existing multi-fidelity and multi-scale orchestrators are explored.
Multi-scale gravity and cosmology
Calcagni, Gianluca
2013-12-01
The gravitational dynamics and cosmological implications of three classes of recently introduced multi-scale spacetimes (with, respectively, ordinary, weighted and q-derivatives) are discussed. These spacetimes are non-Riemannian: the metric structure is accompanied by an independent measure-differential structure with the characteristics of a multi-fractal, namely, different dimensionality at different scales and, at ultra-short distances, a discrete symmetry known as discrete scale invariance. Under this minimal paradigm, five general features arise: (a) the big-bang singularity can be replaced by a finite bounce, (b) the cosmological constant problem is reinterpreted, since accelerating phases can be mimicked by the change of geometry with the time scale, without invoking a slowly rolling scalar field, (c) the discreteness of geometry at Planckian scales can leave an observable imprint of logarithmic oscillations in cosmological spectra and (d) give rise to an alternative mechanism to inflation or (e) to a fully analytic model of cyclic mild inflation, where near scale invariance of the perturbation spectrum can be produced without strong acceleration. Various properties of the models and exact dynamical solutions are discussed. In particular, the multi-scale geometry with weighted derivatives is shown to be a Weyl integrable spacetime.
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education
ERIC Educational Resources Information Center
Schwalbe, Michelle Kristin
2010-01-01
This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…
Multi-scaling modelling in financial markets
NASA Astrophysics Data System (ADS)
Liu, Ruipeng; Aste, Tomaso; Di Matteo, T.
2007-12-01
In the recent years, a new wave of interest spurred the involvement of complexity in finance which might provide a guideline to understand the mechanism of financial markets, and researchers with different backgrounds have made increasing contributions introducing new techniques and methodologies. In this paper, Markov-switching multifractal models (MSM) are briefly reviewed and the multi-scaling properties of different financial data are analyzed by computing the scaling exponents by means of the generalized Hurst exponent H(q). In particular we have considered H(q) for price data, absolute returns and squared returns of different empirical financial time series. We have computed H(q) for the simulated data based on the MSM models with Binomial and Lognormal distributions of the volatility components. The results demonstrate the capacity of the multifractal (MF) models to capture the stylized facts in finance, and the ability of the generalized Hurst exponents approach to detect the scaling feature of financial time series.
MUSIC: MUlti-Scale Initial Conditions
NASA Astrophysics Data System (ADS)
Hahn, Oliver; Abel, Tom
2013-11-01
MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10-4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.
Magnetospheric MultiScale (MMS) System Manager
NASA Technical Reports Server (NTRS)
Schiff, Conrad; Maher, Francis Alfred; Henely, Sean Philip; Rand, David
2014-01-01
The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.
Metadata and Annotations for Multi-scale Electrophysiological Data
Bower, Mark R.; Stead, Matt; Brinkmann, Benjamin H.; Dufendach, Kevin; Worrell, Gregory A.
2010-01-01
The increasing use of high-frequency (kHz), long-duration (days) intracranial monitoring from multiple electrodes during pre-surgical evaluation for epilepsy produces large amounts of data that are challenging to store and maintain. Descriptive metadata and clinical annotations of these large data sets also pose challenges to simple, often manual, methods of data analysis. The problems of reliable communication of metadata and annotations between programs, the maintenance of the meanings within that information over long time periods, and the flexibility to re-sort data for analysis place differing demands on data structures and algorithms. Solutions to these individual problem domains (communication, storage and analysis) can be configured to provide easy translation and clarity across the domains. The Multi-scale Annotation Format (MAF) provides an integrated metadata and annotation environment that maximizes code reuse, minimizes error probability and encourages future changes by reducing the tendency to over-fit information technology solutions to current problems. An example of a graphical utility for generating and evaluating metadata and annotations for “big data” files is presented. PMID:19964266
Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success.
Yankeelov, Thomas E; An, Gary; Saut, Oliver; Luebeck, E Georg; Popel, Aleksander S; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A; Ye, Kaiming; Genin, Guy M
2016-09-01
Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology. PMID:27384942
Software Integration in Multi-scale Simulations: the PUPIL System
NASA Astrophysics Data System (ADS)
Torras, J.; Deumens, E.; Trickey, S. B.
2006-10-01
The state of the art for computational tools in both computational chemistry and computational materials physics includes many algorithms and functionalities which are implemented again and again. Several projects aim to reduce, eliminate, or avoid this problem. Most such efforts seem to be focused within a particular specialty, either quantum chemistry or materials physics. Multi-scale simulations, by their very nature however, cannot respect that specialization. In simulation of fracture, for example, the energy gradients that drive the molecular dynamics (MD) come from a quantum mechanical treatment that most often derives from quantum chemistry. That “QM” region is linked to a surrounding “CM” region in which potentials yield the forces. The approach therefore requires the integration or at least inter-operation of quantum chemistry and materials physics algorithms. The same problem occurs in “QM/MM” simulations in computational biology. The challenge grows if pattern recognition or other analysis codes of some kind must be used as well. The most common mode of inter-operation is user intervention: codes are modified as needed and data files are managed “by hand” by the user (interactively and via shell scripts). User intervention is however inefficient by nature, difficult to transfer to the community, and prone to error. Some progress (e.g Sethna’s work at Cornell [C.R. Myers et al., Mat. Res. Soc. Symp. Proc., 538(1999) 509, C.-S. Chen et al., Poster presented at the Material Research Society Meeting (2000)]) has been made on using Python scripts to achieve a more efficient level of interoperation. In this communication we present an alternative approach to merging current working packages without the necessity of major recoding and with only a relatively light wrapper interface. The scheme supports communication among the different components required for a given multi-scale calculation and access to the functionalities of those components
NASA Astrophysics Data System (ADS)
Nykanen, D. K.
2006-12-01
Hydrometeorological events that produce heavy rainfall and catastrophic flooding in mountainous regions present a great challenge for forecasters. Accurate predictions of flooding resulting from this type of storm require high resolution rainfall data. In a forecast mode, output from Numerical Weather Prediction (NWP) models must be used to drive the hydrologic models. Although much progress has been made in the past decade, the output from NWP models remains at a coarser resolution than what is needed for hydrologic predictions. Bridging the scale gap between precipitation forecasts from NWP models and the resolution needs of hydrologic models for streamflow prediction requires alternative methods such as statistical downscaling of the rainfall fields. This study quantifies the multi-scale statistical properties of rainfall for extreme hydrometeorological events in mountainous regions across scales of 1~20 km. The Buffalo Creek flood of 1996, Fort Collins flood of 1997, and several other extreme hydrometerological events in the Appalachian region and Front Range of the Rocky Mountains are included in the analysis. The following questions will be investigated: (1) does spatial scaling exist as a common feature in convective rainfall events in mountainous regions?, (2) at what spatial scales do meteorological and topographic controls manifest themselves in the space-time variability of the rainfall fields?, and (3) how does meteorological forcings and geographic location impact trends in topographic influences on the multi-scale statistical properties of rainfall? Focus is placed on linking changes in the multi-scale statistical properties with orographic influences on the rainfall and developing predictive relationships between multi-scale parameters and meteorological and topographic forcings. Differences in geographic region and predominant orographic controls (e.g., windward versus leeward forcing) on trends in multi-scale properties of rainfall is investigated
Microphysics in Multi-scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2012-01-01
Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
Multi-scale Modelling of the Ocean Beneath Ice Shelves
NASA Astrophysics Data System (ADS)
Candy, A. S.; Kimura, S.; Holland, P.; Kramer, S. C.; Piggott, M. D.; Jenkins, A.; Pain, C. C.
2011-12-01
Quantitative prediction of future sea-level is currently limited because we lack an understanding of how the mass balance of the Earth's great ice sheets respond to and influence the climate. Understanding the behaviour of the ocean beneath an ice shelf and its interaction with the sheet above presents a great scientific challenge. A solid ice cover, in many places kilometres thick, bars access to the water column, so that observational data can only be obtained by drilling holes through, or launching autonomous vehicles beneath, the ice. In the absence of a comprehensive observational database, numerical modelling can be a key tool to advancing our understanding of the sub-ice-shelf regime. While we have a reasonable understanding of the overall ocean circulation and basic sensitivities, there remain critical processes that are difficult or impossible to represent in current operational models. Resolving these features adequately within a domain that includes the entire ice shelf and continental shelf to the north can be difficult with a structured horizontal resolution. It is currently impossible to adequately represent the key grounding line region, where the water column thickness reduces to zero, with a structured vertical grid. In addition, fronts and pycnoclines, the ice front geometry, shelf basal irregularities and modelling surface pressure all prove difficult in current approaches. The Fluidity-ICOM model (Piggott et al. 2008, doi:10.1002/fld.1663) simulates non-hydrostatic dynamics on meshes that can be unstructured in all three dimensions and uses anisotropic adaptive resolution which optimises the mesh and calculation in response to evolving solution dynamics. These features give it the flexibility required to tackle the challenges outlined above and the opportunity to develop a model that can improve understanding of the physical processes occurring under ice shelves. The approaches taken to develop a multi-scale model of ice shelf ocean cavity
A Collaborative Informatics Infrastructure for Multi-scale Science
Myers, J D; Allison, T C; Bittner, S; Didier, B; Frenklach, M; Green, Jr., W H; Ho, Y; Hewson, J; Koegler, W; Lansing, C; Leahy, D; Lee, M; McCoy, R; Minkoff, M; Nijsure, S; von Laszewski, G; Montoya, D; Pancerella, C; Pinzon, R; Pitz, W J; Rahn, L A; Ruscis, B; Schuchardt, K; Stephan, E; Wagner, A; Windus, T; Yang, C
2005-05-11
The Collaboratory for Multi-scale Chemical Science (CMCS) is developing a powerful informatics-based approach to synthesizing multi-scale information to support a systems-based research approach and is applying it in support of combustion research. An open source multi-scale informatics toolkit is being developed that addresses a number of issues core to the emerging concept of knowledge grids including provenance tracking and lightweight federation of data and application resources into cross-scale information flows. The CMCS portal is currently in use by a number of high-profile pilot groups and is playing a significant role in enabling their efforts to improve and extend community maintained chemical reference information.
Multi-scale modeling of hemodynamics in the cardiovascular system
NASA Astrophysics Data System (ADS)
Liu, Hao; Liang, Fuyou; Wong, Jasmin; Fujiwara, Takashi; Ye, Wenjing; Tsubota, Ken-iti; Sugawara, Michiko
2015-08-01
The human cardiovascular system is a closed-loop and complex vascular network with multi-scaled heterogeneous hemodynamic phenomena. Here, we give a selective review of recent progress in macro-hemodynamic modeling, with a focus on geometrical multi-scale modeling of the vascular network, micro-hemodynamic modeling of microcirculation, as well as blood cellular, subcellular, endothelial biomechanics, and their interaction with arterial vessel mechanics. We describe in detail the methodology of hemodynamic modeling and its potential applications in cardiovascular research and clinical practice. In addition, we present major topics for future study: recent progress of patient-specific hemodynamic modeling in clinical applications, micro-hemodynamic modeling in capillaries and blood cells, and the importance and potential of the multi-scale hemodynamic modeling.
Multi-scale Plasmonic Nanoparticles and the Inverse Problem
Odom, Teri W.; You, Eun-Ah; Sweeney, Christina M.
2012-01-01
This Perspective describes how multi-scale plasmonic structures with two or more length scales (fine, medium, coarse) provide an experimental route for addressing the inverse problem. Specific near-field and far-field optical properties can be targeted and compiled into a plasmon resonance library by taking advantage of length scales spanning three orders of magnitude, from 1 nm to greater than 1000 nm, in a single particle. Examples of multi-scale 1D, 2D, and 3D gold structures created by nanofabrication tools and templates are discussed, and unexpected optical properties compared to those from their smaller counterparts are emphasized. One application of multi-scale particle dimers for surface-enhanced Raman spectroscopy is also described. PMID:23066451
Bio-inspired homogeneous multi-scale place recognition.
Chen, Zetao; Lowry, Stephanie; Jacobson, Adam; Hasselmo, Michael E; Milford, Michael
2015-12-01
Robotic mapping and localization systems typically operate at either one fixed spatial scale, or over two, combining a local metric map and a global topological map. In contrast, recent high profile discoveries in neuroscience have indicated that animals such as rodents navigate the world using multiple parallel maps, with each map encoding the world at a specific spatial scale. While a number of theoretical-only investigations have hypothesized several possible benefits of such a multi-scale mapping system, no one has comprehensively investigated the potential mapping and place recognition performance benefits for navigating robots in large real world environments, especially using more than two homogeneous map scales. In this paper we present a biologically-inspired multi-scale mapping system mimicking the rodent multi-scale map. Unlike hybrid metric-topological multi-scale robot mapping systems, this new system is homogeneous, distinguishable only by scale, like rodent neural maps. We present methods for training each network to learn and recognize places at a specific spatial scale, and techniques for combining the output from each of these parallel networks. This approach differs from traditional probabilistic robotic methods, where place recognition spatial specificity is passively driven by models of sensor uncertainty. Instead we intentionally create parallel learning systems that learn associations between sensory input and the environment at different spatial scales. We also conduct a systematic series of experiments and parameter studies that determine the effect on performance of using different neural map scaling ratios and different numbers of discrete map scales. The results demonstrate that a multi-scale approach universally improves place recognition performance and is capable of producing better than state of the art performance compared to existing robotic navigation algorithms. We analyze the results and discuss the implications with respect to
Multi-scale analysis for environmental dispersion in wetland flow
NASA Astrophysics Data System (ADS)
Wu, Zi; Li, Z.; Chen, G. Q.
2011-08-01
Presented in this work is a multi-scale analysis for longitudinal evolution of contaminant concentration in a fully developed flow through a shallow wetland channel. An environmental dispersion model for the mean concentration is devised as an extension of Taylor's classical formulation by a multi-scale analysis. Corresponding environmental dispersivity is found identical to that determined by the method of concentration moments. For typical contaminant constituents of chemical oxygen demand, biochemical oxygen demand, total phosphorus, total nitrogen and heavy metal, the evolution of contaminant cloud is illustrated with the critical length and duration of the contaminant cloud with constituent concentration beyond some given environmental standard level.
Multi-scale grid generated turbulence in an internal flow application
NASA Astrophysics Data System (ADS)
Ranade, Piyush; Morris, Scott
2013-11-01
Turbulence generation using multi-scale, or fractal grids, is a method of creating high turbulence intensity flows passively by utilizing the intrinsic scales associated with the grid. This has become the topic of research in many external flow applications. In turbomachinery, the flow at the exit of the combustor and into the first nozzle stage is highly turbulent. In order to create high turbulence intensities in a lab setting passively, multi-scale turbulence generation grids are proposed. The presence of multiple length scales in the grid geometry innately gives rise to turbulent motions of a wide spectrum being shed immediately downstream of the grid, leading to high turbulence intensity flow. The biggest challenge with using such a grid in an internal flow, however, is to achieve spatial uniformity. In this research, three grid geometries commonly found in literature were tested in an experimental set-up consisting of flow between two flat plates. In addition, several other fractal grid geometries were created and tested in an attempt to maximize turbulence intensity while maintaining spatial homogeneity. This research hopes to begin giving insight into the development of turbulence downstream of a multi-scale grid in an internal flow setting.
Multi-scale feature learning on pixels and super-pixels for seminal vesicles MRI segmentation
NASA Astrophysics Data System (ADS)
Gao, Qinquan; Asthana, Akshay; Tong, Tong; Rueckert, Daniel; Edwards, Philip "Eddie"
2014-03-01
We propose a learning-based approach to segment the seminal vesicles (SV) via random forest classifiers. The proposed discriminative approach relies on the decision forest using high-dimensional multi-scale context-aware spatial, textual and descriptor-based features at both pixel and super-pixel level. After affine transformation to a template space, the relevant high-dimensional multi-scale features are extracted and random forest classifiers are learned based on the masked region of the seminal vesicles from the most similar atlases. Using these classifiers, an intermediate probabilistic segmentation is obtained for the test images. Then, a graph-cut based refinement is applied to this intermediate probabilistic representation of each voxel to get the final segmentation. We apply this approach to segment the seminal vesicles from 30 MRI T2 training images of the prostate, which presents a particularly challenging segmentation task. The results show that the multi-scale approach and the augmentation of the pixel based features with the super-pixel based features enhances the discriminative power of the learnt classifier which leads to a better quality segmentation in some very difficult cases. The results are compared to the radiologist labeled ground truth using leave-one-out cross-validation. Overall, the Dice metric of 0:7249 and Hausdorff surface distance of 7:0803 mm are achieved for this difficult task.
Geoelectrical Measurement of Multi-Scale Mass Transfer Parameters
Day-Lewis, Frederick; Singha, Kamini; Haggerty, Roy; Johnson, Tim; Binley, Andrew; Lane, John
2014-01-16
-part research plan involving (1) development of computer codes and techniques to estimate mass-transfer parameters from time-lapse electrical data; (2) bench-scale experiments on synthetic materials and materials from cores from the Hanford 300 Area; and (3) field demonstration experiments at the DOE’s Hanford 300 Area. In a synergistic add-on to our workplan, we analyzed data from field experiments performed at the DOE Naturita Site under a separate DOE SBR grant, on which PI Day-Lewis served as co-PI. Techniques developed for application to Hanford datasets also were applied to data from Naturita. 1. Introduction The Department of Energy (DOE) faces enormous scientific and engineering challenges associated with the remediation of legacy contamination at former nuclear weapons production facilities. Selection, design and optimization of appropriate site remedies (e.g., pump-and-treat, biostimulation, or monitored natural attenuation) requires reliable predictive models of radionuclide fate and transport; however, our current modeling capabilities are limited by an incomplete understanding of multi-scale mass transfer—its rates, scales, and the heterogeneity of controlling parameters. At many DOE sites, long “tailing” behavior, concentration rebound, and slower-than-expected cleanup are observed; these observations are all consistent with multi-scale mass transfer [Haggerty and Gorelick, 1995; Haggerty et al., 2000; 2004], which renders pump-and-treat remediation and biotransformation inefficient and slow [Haggerty and Gorelick, 1994; Harvey et al., 1994; Wilson, 1997]. Despite the importance of mass transfer, there are significant uncertainties associated with controlling parameters, and the prevalence of mass transfer remains a point of debate [e.g., Hill et al., 2006; Molz et al., 2006] for lack of experimental methods to verify and measure it in situ or independently of tracer breakthrough. There is a critical need for new field-experimental techniques to
Multi-scale characterization of nanostructured sodium aluminum hydride
NASA Astrophysics Data System (ADS)
NaraseGowda, Shathabish
Complex metal hydrides are the most promising candidate materials for onboard hydrogen storage. The practicality of this class of materials is counter-poised on three critical attributes: reversible hydrogen storage capacity, high hydrogen uptake/release kinetics, and favorable hydrogen uptake/release thermodynamics. While a majority of modern metallic hydrides that are being considered are those that meet the criteria of high theoretical storage capacity, the challenges lie in addressing poor kinetics, thermodynamics, and reversibility. One emerging strategy to resolve these issues is via nanostructuring or nano-confinement of complex hydrides. By down-sizing and scaffolding them to retain their nano-dimensions, these materials are expected to improve in performance and reversibility. This area of research has garnered immense interest lately and there is active research being pursued to address various aspects of nanostructured complex hydrides. The research effort documented here is focused on a detailed investigation of the effects of nano-confinement on aspects such as the long range atomic hydrogen diffusivities, localized hydrogen dynamics, microstructure, and dehydrogenation mechanism of sodium alanate. A wide variety of microporous and mesoporous materials (metal organic frameworks, porous silica and alumina) were investigated as scaffolds and the synthesis routes to achieve maximum pore-loading are discussed. Wet solution infiltration technique was adopted using tetrahydrofuran as the medium and the precursor concentrations were found to have a major role in achieving maximum pore loading. These concentrations were optimized for each scaffold with varying pore sizes and confinement was quantitatively characterized by measuring the loss in specific surface area. This work is also aimed at utilizing neutron and synchrotron x-ray characterization techniques to study and correlate multi-scale material properties and phenomena. Some of the most advanced
Multi-Scale Modeling of Magnetospheric Dynamics
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Toth, G.
2012-01-01
Magnetic reconnection is a key element in many phenomena in space plasma, e.g. Coronal mass Ejections, Magnetosphere substorms. One of the major challenges in modeling the dynamics of large-scale systems involving magnetic reconnection is to quantifY the interaction between global evolution of the magnetosphere and microphysical kinetic processes in diffusion regions near reconnection sites. Recent advances in small-scale kinetic modeling of magnetic reconnection significantly improved our understanding of physical mechanisms controlling the dissipation in the vicinity of the reconnection site in collisionless plasma. However the progress in studies of small-scale geometries was not very helpful for large scale simulations. Global magnetosphere simulations usually include non-ideal processes in terms of numerical dissipation and/or ad hoc anomalous resistivity. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term 11 J did not produce fast reconnection rates observed in kinetic simulations. In collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is nongyrotropic pressure effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and replace ad hoc parameters such as "critical current density" and "anomalous resistivity" with a physically motivated model of dissipation. The primary mechanism controlling the dissipation in the vicinity of the reconnection site in incorporated into MHD description in terms of non-gyrotropic corrections to the induction equation. We will demonstrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution. Our approach allowed for the first time to model loading/unloading cycle in response to steady southward IMF driving. The role of solar wind parameters and
Multi-Scale Modeling of Magnetospheric Reconnection
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Rastatter, L.; Toth, G.; Dezeeuw, D.; Gomobosi, T.
2007-01-01
One of the major challenges in modeling the magnetospheric magnetic reconnection is to quantify the interaction between large-scale global magnetospheric dynamics and microphysical processes in diffusion regions near reconnection sites. There is still considerable debate as to what degree microphysical processes on kinetic scales affect the global evolution and how important it is to substitute numerical dissipation and/or ad hoc anomalous resistivity by a physically motivated model of dissipation. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term $\\eta J$ did not produce the fast reconnection rates observed in kinetic simulations. For a broad range of physical parameters in collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is non-gyrotropic effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and incorporate nongyrotropic effects in diffusion regions in terms of corrections to the induction equation. We developed an algorithm to search for magnetotail reconnection sites, specifically where the magnetic field components perpendicular to the local current direction approaches zero and form an X-type configuration. Spatial scales of the diffusion region and magnitude of the reconnection electric field are calculated selfconsistently using MHD plasma and field parameters in the vicinity of the reconnection site. The location of the reconnection sites is updated during the simulations. To clarify the role of nongyrotropic effects in diffusion region on the global magnetospheric dynamic we perform simulations with steady southward IMF driving of the magnetosphere. Ideal MHD simulations with magnetic reconnection supported by numerical resistivity produce steady configuration with almost stationary near-earth neutral
Blood Flow: Multi-scale Modeling and Visualization (July 2011)
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 blood 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.
Blood Flow: Multi-scale Modeling and Visualization
2010-01-01
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 developing methods for multi-scale computations, techniques for multi-scale visualizations must be designed. This animation presents early results of joint efforts of teams from Brown University and Argonne National Laboratory to develop a multi-scale visualization methodology. It illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each blood cell is represented by a mesh made of 500 DPD-particles, and small spheres show a sub-set of the DPD particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. Credits: Science: Leopold Grinberg and George Karniadakis, Brown University Visualization: Joseph A. Insley and Michael E. Papka, Argonne National Laboratory This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. This research was supported in part by the National Science Foundation through the PetaApps program and used TeraGrid resources provided by National Institute for Computational Sciences.
Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.
2005-01-01
This document is the final report for the project entitled, "Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components," funded under the NRA entitled "Cross-Enterprise Technology Development Program" issued by the NASA Office of Space Science in 2000. The project was funded in 2001, and spanned a four year period from March, 2001 to February, 2005. Through enhancements to and synthesis of unique, state of the art structural mechanics and micromechanics analysis software, a new multi-scale tool has been developed that enables design, analysis, and sizing of advance lightweight composite and smart materials and structures from the full vehicle, to the stiffened structure, to the micro (fiber and matrix) scales. The new software tool has broad, cross-cutting value to current and future NASA missions that will rely on advanced composite and smart materials and structures.
Complexity of carbon market from multi-scale entropy analysis
NASA Astrophysics Data System (ADS)
Fan, Xinghua; Li, Shasha; Tian, Lixin
2016-06-01
Complexity of carbon market is the consequence of economic dynamics and extreme social political events in global carbon markets. The multi-scale entropy can measure the long-term structures in the daily price return time series. By using multi-scale entropy analysis, we explore the complexity of carbon market and mean reversion trend of daily price return. The logarithmic difference of data Dec16 from August 6, 2010 to May 22, 2015 is selected as the sample. The entropy is higher in small time scale, while lower in large. The dependence of the entropy on the time scale reveals the mean reversion of carbon prices return in the long run. A relatively great fluctuation over some short time period indicates that the complexity of carbon market evolves consistently with economic development track and the events of international climate conferences.
Kolmogorov spectrum consistent optimization for multi-scale flow decomposition
NASA Astrophysics Data System (ADS)
Mishra, M.; Liu, X.; Skote, M.; Fu, C.-W.
2014-05-01
Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter, we can efficiently perform scale decomposition using Fourier transform directly while adequately suppressing Gibbs ringing artifacts. Both 2D and 3D scale decomposition results are presented, together with qualitative and quantitative analysis. The comparison with existing multi-scale analysis technique is conducted to verify the effectiveness of our method. Validation of this decomposition technique is demonstrated both qualitatively and quantitatively. The advantage of the proposed methodology enables a precise specification of continuous length scales while preserving the original structures. These unique features of the proposed methodology may provide future insights into the evolution of turbulent flow structures.
Reconfigurable multi-scale colloidal assembly on excluded volume patterns
NASA Astrophysics Data System (ADS)
Edwards, Tara D.; Yang, Yuguang; Everett, W. Neil; Bevan, Michael A.
2015-09-01
The ability to create multi-scale, periodic colloidal assemblies with unique properties is important to emerging applications. Dynamically manipulating colloidal structures via tunable kT-scale attraction can provide the opportunity to create particle-based nano- and microstructured materials that are reconfigurable. Here, we report a novel tactic to obtain reconfigurable, multi-scale, periodic colloidal assemblies by combining thermoresponsive depletant particles and patterned topographical features that, together, reversibly mediate local kT-scale depletion interactions. This method is demonstrated in optical microscopy experiments to produce colloidal microstructures that reconfigure between well-defined ordered structures and disordered fluid states as a function of temperature and pattern feature depth. These results are well described by Monte Carlo simulations using theoretical depletion potentials that include patterned excluded volume. Ultimately, the approach reported here can be extended to control the size, shape, orientation, and microstructure of colloidal assemblies on multiple lengths scales and on arbitrary pre-defined pattern templates.
Peripheral nerve enhancement based on multi-scale Hessian matrix
NASA Astrophysics Data System (ADS)
Ma, Xiuli; Li, Hui; Zhou, Xueli; Wan, Wanggen
2011-06-01
To improve the precision of nerve segmentation in CT images, a new comparability function is proposed in this paper to enhance the contrast between nerve structure and other surrounding tissues. It is based on nerve's characteristic, i.e. dark tubular structure, and a thorough analysis of the multi-scale Hessian matrix. By comparability function, the gray range of interested nerve structure can be automatically determined, which combines the multi-scale Hessian matrix eigenvalues with intensity information of original nerve CT images. The experimental results show that the improved algorithm can not only enhance the continuous nerve of tubular structure, but also clearly reflect its bifurcations and crossovers. It is very important and significant to the computer-aided disease diagnosis of peripheral nervous system.
Multi-Scale Simulation and Optimization of Lithium Battery Performance
NASA Astrophysics Data System (ADS)
Golmon, Stephanie L.
The performance and degradation of lithium batteries strongly depends on electrochemical, mechanical, and thermal phenomena. While a large volume of work has focused on thermal management, mechanical phenomena relevant to battery design are not fully understood. Mechanical degradation of electrode particles has been experimentally linked to capacity fade and failure of batteries; an understanding of the interplay between mechanics and electrochemistry in the battery is necessary in order to improve the overall performance of the battery. A multi-scale model to simulate the coupled electrochemical and mechanical behavior of Li batteries has been developed, which models the porous electrode and separator regions of the battery. The porous electrode includes a liquid electrolyte and solid active materials. A multi-scale finite element approach is used to analyze the electrochemical and mechanical performance. The multi-scale model includes a macro- and micro-scale with analytical volume-averaging methods to relate the scales. The macro-scale model describes Li-ion transport through the electrolyte, electric potentials, and displacements throughout the battery. The micro-scale considers the surface kinetics and electrochemical and mechanical response of a single particle of active material evaluated locally within the cathode region. Both scales are non-linear and dependent on the other. The electrochemical and mechanical response of the battery are highly dependent on the porosity in the electrode, the active material particle size, and discharge rate. Balancing these parameters can improve the overall performance of the battery. A formal design optimization approach with multi-scale adjoint sensitivity analysis is developed to find optimal designs to improve the performance of the battery model. Optimal electrode designs are presented which maximize the capacity of the battery while mitigating stress levels during discharge over a range of discharge rates.
A multi-scale Monte Carlo method for electrolytes
NASA Astrophysics Data System (ADS)
Liang, Yihao; Xu, Zhenli; Xing, Xiangjun
2015-08-01
Artifacts arise in the simulations of electrolytes using periodic boundary conditions (PBCs). We show the origin of these artifacts are the periodic image charges and the constraint of charge neutrality inside the simulation box, both of which are unphysical from the view point of real systems. To cure these problems, we introduce a multi-scale Monte Carlo (MC) method, where ions inside a spherical cavity are simulated explicitly, while ions outside are treated implicitly using a continuum theory. Using the method of Debye charging, we explicitly derive the effective interactions between ions inside the cavity, arising due to the fluctuations of ions outside. We find that these effective interactions consist of two types: (1) a constant cavity potential due to the asymmetry of the electrolyte, and (2) a reaction potential that depends on the positions of all ions inside. Combining the grand canonical Monte Carlo (GCMC) with a recently developed fast algorithm based on image charge method, we perform a multi-scale MC simulation of symmetric electrolytes, and compare it with other simulation methods, including PBC + GCMC method, as well as large scale MC simulation. We demonstrate that our multi-scale MC method is capable of capturing the correct physics of a large system using a small scale simulation.
Moist multi-scale models for the hurricane embryo
Majda, Andrew J.; Xing, Yulong; Mohammadian, Majid
2010-01-01
Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heat sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.
Multi-scale Heat Kernel based Volumetric Morphology Signature
Wang, Gang; Wang, Yalin
2015-01-01
Here we introduce a novel multi-scale heat kernel based regional shape statistical approach that may improve statistical power on the structural analysis. The mechanism of this analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral mesh. In order to capture profound volumetric changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between two boundary surfaces by computing the streamline in the tetrahedral mesh. Secondly, we propose a multi-scale volumetric morphology signature to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the volumetric morphology signatures and generate the internal structure features. The multi-scale and physics based internal structure features may bring stronger statistical power than other traditional methods for volumetric morphology analysis. To validate our method, we apply support vector machine to classify synthetic data and brain MR images. In our experiments, the proposed work outperformed FreeSurfer thickness features in Alzheimer's disease patient and normal control subject classification analysis. PMID:26550613
Local variance for multi-scale analysis in geomorphometry
Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas
2011-01-01
Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138
Multi-scale particle simulation of bounded plasmas
Parker, S.E.; Birdsall, C.K. . Electronics Research Lab.); Friedman, A.; Ray, S.L. )
1989-01-01
We are using the multi-scale technique to model bounded systems. Certain bounded systems are a naturally suited for the multi-scale method because of the boundary layer that forms at the wall, which is usually a short spatial and time scale structure, can significantly affect the bulk plasma behavior. One goal is to understand the interaction between the bulk plasma and the sheath. If the relevant short time scale physics is local to a few known spatial regions, then one can take advantage of this by advancing particles with variable {Delta}t depending on position, hence reducing computing time. The unmagnetized sheath problem is such a case. The model is a one dimensional bounded slab with kinetic ions and electrons. We start with a collisionless and unmagnetized system for simplicity. The right boundary is a conducting wall that absorbs all particles that come in contact with it. The left boundary is a symmetry point, where the particles are reflected. We allow a specified initial distribution: f(x,v,t = 0). In order to test the numerics of both multi-scale method and boundary conditions we are using the following test problem: a cutoff Maxwellian distribution for the electrons and fixed ions. The system has an analytic solution, so the run may be started from equilibrium. This gives us a benchmark and tests the fast time scale electron sheath dynamics. Results using variable {Delta}t will be given. In the future, we intend to use the more general model to study time dependent bounded plasma problems, such as a plasma expanding toward a conducting wall.
Global and Multi-scale Dynamics of the Magnetosphere
NASA Astrophysics Data System (ADS)
Sharma, A. S.; Sitnov, M. I.
2001-05-01
Earth's magnetosphere during substorms demonstrates a number of characteristic features such as low effective dimension, hysteresis and power-law spectra of fluctuations on different scales. The dynamics, on the largest scale, associated with substorms, are in reasonable agreement with low-dimensional magnetospheric models and in particular those of inverse bifurcations. However, deviations from the low-dimensional picture are not negligible, making the nonequilibrium phase transition more appropriate as a dynamical analogue of the substorm activity. On the other hand, the multi- scale magnetospheric dynamics cannot be restricted to the self-organized criticality (SOC), which is based on a class of mathematical analogues of sandpiles. Like real sandpiles the magnetosphere demonstrates during substorms the features, which are distinct from SOC and more reminiscent again to conventional phase transitions. While the multi-scale substorm activity resembles second-order phase transitions, the largest substorm avalanches are shown to reveal the features of first-order nonequilibrium transitions including hysteresis phenomenon and global structure of the type of the "temperature-pressure-density" diagram. Moreover, this diagram allows one to compute a critical exponent, consistent with the second-order phase transitions, and reflects the multiscale aspect of the substorm activity, different from power-law frequency and scale spectra of autonomous systems. In contrast to SOC exponents, the exponent relates input and output parameters of the magnetosphere. Using an analogy with the dynamical Ising model in the mean-field approximation we show the connection between this data-derived exponent of nonequilibrium transitions in the magnetosphere and the standard critical exponent β of equilibrium second-order phase transitions. We discuss also further developments of the phase tarnsition approach to modeling magnetospheric activity using the multifractal, mutual information
Multi-Scale Multi-Dimensional Ion Battery Performance Model
Energy Science and Technology Software Center (ESTSC)
2007-05-07
The Multi-Scale Multi-Dimensional (MSMD) Lithium Ion Battery Model allows for computer prediction and engineering optimization of thermal, electrical, and electrochemical performance of lithium ion cells with realistic geometries. The model introduces separate simulation domains for different scale physics, achieving much higher computational efficiency compared to the single domain approach. It solves a one dimensional electrochemistry model in a micro sub-grid system, and captures the impacts of macro-scale battery design factors on cell performance and materialmore » usage by solving cell-level electron and heat transports in a macro grid system.« less
Multi-scale statistical analysis of coronal solar activity
NASA Astrophysics Data System (ADS)
Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.
2016-07-01
Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.
Multi-Scale Dynamics, Control, and Simulation of Granular Spacecraft
NASA Technical Reports Server (NTRS)
Quadrelli, Marco B.; Basinger, Scott; Swartzlander, Grover
2013-01-01
In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of grains in orbit. An example of application is a spaceborne observatory for exoplanet imaging, where the primary aperture is a cloud instead of a monolithic aperture. A model is proposed of a multi-scale dynamics of the grains and cloud in orbit, as well as a control approach for cloud shape maintenance and alignment, and preliminary simulation studies are carried out for the representative imaging system.
Multi-scale statistical analysis of coronal solar activity
Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.
2016-07-08
Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.; Kumar, S.; Lapenta, W.; Li, X.; Matsui, T.; Rienecker, M.; Shen, B.W.; Shi, J.J.; Simpson, J.; Zeng, X.
2008-01-01
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite
Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features
Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie
2014-01-01
Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694
Recognizing objects in 3D point clouds with multi-scale local features.
Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie
2014-01-01
Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms. PMID:25517694
Metadata in the Collaboratory for Multi-Scale Chemical Science
Pancerella, Carmen M.; Hewson, John; Koegler, Wendy S.; Leahy, David; Lee, Michael; Rahn, Larry; Yang, Christine; Myers, James D.; Didier, Brett T.; McCoy, Renata; Schuchardt, Karen L.; Stephan, Eric G.; Windus, Theresa L.; Amin, Kaizer; Bittner, Sandra; Lansing, Carina S.; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Pinzon, Reinhardt; Ruscic, Branko; Wagner, Albert F.; Wang, Baoshan; Pitz, William; Ho, Yen-Ling; Montoya, David W.; Xu, Lili; Allison, Thomas C.; Green, William H.; Frenklach, Michael
2003-10-02
The goal of the Collaboratory for the Multi-scale Chemical Sciences (CMCS) [1] is to develop an informatics-based approach to synthesizing multi-scale chemistry information to create knowledge in the chemical sciences. CMCS is using a portal and metadata-aware content store as a base for building a system to support inter-domain knowledge exchange in chemical science. Key aspects of the system include configurable metadata extraction and translation, a core schema for scientific pedigree, and a suite of tools for managing data and metadata and visualizing pedigree relationships between data entries. CMCS metadata is represented using Dublin Core with metadata extensions that are useful to both the chemical science community and the science community in general. CMCS is working with several chemistry groups who are using the system to collaboratively assemble and analyze existing data to derive new chemical knowledge. In this paper we discuss the project’s metadata-related requirements, the relevant software infrastructure, core metadata schema, and tools that use the metadata to enhance science
A hybrid approach to multi-scale modelling of cancer.
Osborne, J M; Walter, A; Kershaw, S K; Mirams, G R; Fletcher, A G; Pathmanathan, P; Gavaghan, D; Jensen, O E; Maini, P K; Byrne, H M
2010-11-13
In this paper, we review multi-scale models of solid tumour growth and discuss a middle-out framework that tracks individual cells. By focusing on the cellular dynamics of a healthy colorectal crypt and its invasion by mutant, cancerous cells, we compare a cell-centre, a cell-vertex and a continuum model of cell proliferation and movement. All models reproduce the basic features of a healthy crypt: cells proliferate near the crypt base, they migrate upwards and are sloughed off near the top. The models are used to establish conditions under which mutant cells are able to colonize the crypt either by top-down or by bottom-up invasion. While the continuum model is quicker and easier to implement, it can be difficult to relate system parameters to measurable biophysical quantities. Conversely, the greater detail inherent in the multi-scale models means that experimentally derived parameters can be incorporated and, therefore, these models offer greater scope for understanding normal and diseased crypts, for testing and identifying new therapeutic targets and for predicting their impacts. PMID:20921009
Multi-Scale Dynamics From Earth's Surface into the Thermosphere
NASA Astrophysics Data System (ADS)
Fritts, David
2016-07-01
Atmospheric structures ranging from very small scales near Earth's surface to much larger scales in the mesosphere and lower thermosphere (MLT) appear to exhibit common features and underlying dynamics. Above the turbopause at ~110 km, kinematic viscosity and thermal diffusivity largely suppress flow instabilities leading to turbulence. Below the turbopause, however, multi-scale dynamics appear to drive systematic transfers of energy both among quasi-two-dimensional (2D) motions at larger scales and to three-dimensional (3D) instabilities and turbulence at smaller scales. Such multi-scale dynamics arise due to superposed GWs and background wind shears and readily drive local layered structures comprising thinner, strongly stratified and sheared "sheets" and thicker, weakly stratified and sheared "layers". These environments initiate various types of instabilities that yield local turbulence and mixing that contribute to maintenance of the "sheet and layer" (S&L) structures. Idealized modeling of these dynamics describe many S&L flow, instability, and turbulence features that are confirmed by observations from the stable boundary layer into the mesosphere. Similar dynamics accompany larger-scale gravity waves that encounter variable stratification and shear, and that induce strong local body forces, throughout the atmosphere.
A Global and Regional Multi-scale Advanced Prediction System
NASA Astrophysics Data System (ADS)
Chen, D.; Xue, J.; Yang, X.; Zhang, H.; Liu, J.; Jin, Z.; Huang, L.; Wu, X.
With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will be- come more and more complicated, and more and more ?huge?. The costs for improve- ment and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally(4) variable or uniform resolution in option (5) possibility to run in regional or global mode(6) finite difference in the vertical dis- cretization in option (7) semi-implicit and semi-Lagrangian scheme; (8) height terrain- following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993).
Multi-scale modeling for sustainable chemical production.
Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J
2013-09-01
With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. PMID:23520143
Dehazing method through polarimetric imaging and multi-scale analysis
NASA Astrophysics Data System (ADS)
Cao, Lei; Shao, Xiaopeng; Liu, Fei; Wang, Lin
2015-05-01
An approach for haze removal utilizing polarimetric imaging and multi-scale analysis has been developed to solve one problem that haze weather weakens the interpretation of remote sensing because of the poor visibility and short detection distance of haze images. On the one hand, the polarization effects of the airlight and the object radiance in the imaging procedure has been considered. On the other hand, one fact that objects and haze possess different frequency distribution properties has been emphasized. So multi-scale analysis through wavelet transform has been employed to make it possible for low frequency components that haze presents and high frequency coefficients that image details or edges occupy are processed separately. According to the measure of the polarization feather by Stokes parameters, three linear polarized images (0°, 45°, and 90°) have been taken on haze weather, then the best polarized image min I and the worst one max I can be synthesized. Afterwards, those two polarized images contaminated by haze have been decomposed into different spatial layers with wavelet analysis, and the low frequency images have been processed via a polarization dehazing algorithm while high frequency components manipulated with a nonlinear transform. Then the ultimate haze-free image can be reconstructed by inverse wavelet reconstruction. Experimental results verify that the dehazing method proposed in this study can strongly promote image visibility and increase detection distance through haze for imaging warning and remote sensing systems.
Reconfigurable multi-scale colloidal assembly on excluded volume patterns
Edwards, Tara D.; Yang, Yuguang; Everett, W. Neil; Bevan, Michael A.
2015-01-01
The ability to create multi-scale, periodic colloidal assemblies with unique properties is important to emerging applications. Dynamically manipulating colloidal structures via tunable kT-scale attraction can provide the opportunity to create particle-based nano- and microstructured materials that are reconfigurable. Here, we report a novel tactic to obtain reconfigurable, multi-scale, periodic colloidal assemblies by combining thermoresponsive depletant particles and patterned topographical features that, together, reversibly mediate local kT-scale depletion interactions. This method is demonstrated in optical microscopy experiments to produce colloidal microstructures that reconfigure between well-defined ordered structures and disordered fluid states as a function of temperature and pattern feature depth. These results are well described by Monte Carlo simulations using theoretical depletion potentials that include patterned excluded volume. Ultimately, the approach reported here can be extended to control the size, shape, orientation, and microstructure of colloidal assemblies on multiple lengths scales and on arbitrary pre-defined pattern templates. PMID:26330058
Reconfigurable multi-scale colloidal assembly on excluded volume patterns.
Edwards, Tara D; Yang, Yuguang; Everett, W Neil; Bevan, Michael A
2015-01-01
The ability to create multi-scale, periodic colloidal assemblies with unique properties is important to emerging applications. Dynamically manipulating colloidal structures via tunable kT-scale attraction can provide the opportunity to create particle-based nano- and microstructured materials that are reconfigurable. Here, we report a novel tactic to obtain reconfigurable, multi-scale, periodic colloidal assemblies by combining thermoresponsive depletant particles and patterned topographical features that, together, reversibly mediate local kT-scale depletion interactions. This method is demonstrated in optical microscopy experiments to produce colloidal microstructures that reconfigure between well-defined ordered structures and disordered fluid states as a function of temperature and pattern feature depth. These results are well described by Monte Carlo simulations using theoretical depletion potentials that include patterned excluded volume. Ultimately, the approach reported here can be extended to control the size, shape, orientation, and microstructure of colloidal assemblies on multiple lengths scales and on arbitrary pre-defined pattern templates. PMID:26330058
Automatic reconstruction of neural morphologies with multi-scale tracking.
Choromanska, Anna; Chang, Shih-Fu; Yuste, Rafael
2012-01-01
Neurons have complex axonal and dendritic morphologies that are the structural building blocks of neural circuits. The traditional method to capture these morphological structures using manual reconstructions is time-consuming and partly subjective, so it appears important to develop automatic or semi-automatic methods to reconstruct neurons. Here we introduce a fast algorithm for tracking neural morphologies in 3D with simultaneous detection of branching processes. The method is based on existing tracking procedures, adding the machine vision technique of multi-scaling. Starting from a seed point, our algorithm tracks axonal or dendritic arbors within a sphere of a variable radius, then moves the sphere center to the point on its surface with the shortest Dijkstra path, detects branching points on the surface of the sphere, scales it until branches are well separated and then continues tracking each branch. We evaluate the performance of our algorithm on preprocessed data stacks obtained by manual reconstructions of neural cells, corrupted with different levels of artificial noise, and unprocessed data sets, achieving 90% precision and 81% recall in branch detection. We also discuss limitations of our method, such as reconstructing highly overlapping neural processes, and suggest possible improvements. Multi-scaling techniques, well suited to detect branching structures, appear a promising strategy for automatic neuronal reconstructions. PMID:22754498
Strong, Multi-Scale Heterogeneity in Earth's Lowermost Mantle.
Tkalčić, Hrvoje; Young, Mallory; Muir, Jack B; Davies, D Rhodri; Mattesini, Maurizio
2015-01-01
The core mantle boundary (CMB) separates Earth's liquid iron outer core from the solid but slowly convecting mantle. The detailed structure and dynamics of the mantle within ~300 km of this interface remain enigmatic: it is a complex region, which exhibits thermal, compositional and phase-related heterogeneity, isolated pockets of partial melt and strong variations in seismic velocity and anisotropy. Nonetheless, characterising the structure of this region is crucial to a better understanding of the mantle's thermo-chemical evolution and the nature of core-mantle interactions. In this study, we examine the heterogeneity spectrum from a recent P-wave tomographic model, which is based upon trans-dimensional and hierarchical Bayesian imaging. Our tomographic technique avoids explicit model parameterization, smoothing and damping. Spectral analyses reveal a multi-scale wavelength content and a power of heterogeneity that is three times larger than previous estimates. Inter alia, the resulting heterogeneity spectrum gives a more complete picture of the lowermost mantle and provides a bridge between the long-wavelength features obtained in global S-wave models and the short-scale dimensions of seismic scatterers. The evidence that we present for strong, multi-scale lowermost mantle heterogeneity has important implications for the nature of lower mantle dynamics and prescribes complex boundary conditions for Earth's geodynamo. PMID:26674394
A Novel Spectral Approach to Multi-Scale Modeling
NASA Astrophysics Data System (ADS)
Landi, Giacomo
2011-12-01
In this work, we present a novel approach for predicting the elastic, thermo-elastic and plastic fields in three-dimensional (3-D) voxel-based microstructure datasets subjected to uniform periodic boundary conditions. Such localization relationships (linkages) lie at the core of all multi-scale modeling frameworks and can be efficiently formulated in a Discrete Fourier Transforms (DFT) -based knowledge system. This new formalism has its theoretical roots in the statistical continuum theories developed originally by Kroner [1]. However, in the approach described by Kroner, the terms in the series were established by selecting a reference medium and numerically evaluating a complex series of nested convolution integrals. This approach is largely hampered by the principal value problem, and exhibits high sensitivity to the properties of the selected reference medium. In the present work, the same series expressions have been recast into much more computationally efficient representations using DFTs. The spectral analysis transforms the complex integral relations into relatively simple algebraic expressions involving polynomials of structure parameters and morphology-independent influence coefficients. These coefficients need to be established only once for a given material system. The main advantage of the new DFT-based framework is that it allows easy calibration of Kroner's expansions to results from finite element methods, thereby overcoming all of the main obstacles associated with the principal value problem and the need to select a reference medium. This approach can be seen as an efficient procedure for data-mining the results from computationally expensive numerical models and establishing the underlying knowledge systems at a selected length scale in multi-scale modeling problems. The set of influence coefficients described above constitutes the underlying knowledge for a given deformation and can be easily stored and recalled as and when needed in a multi-scale
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
Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering
Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita
2014-01-01
Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively. PMID:24761376
NASA Astrophysics Data System (ADS)
Wang, Wen-Jing; Cui, Ling-Li; Chen, Dao-Yun
2016-04-01
Monitoring of potential bearing faults in operation is of critical importance to safe operation of high speed trains. One of the major challenges is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment. In this work, we report a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum (MPS) through a multi-scale morphology analysis procedure. The results show that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves. Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes.
A Multi-scale Approach to Designing Therapeutics for Tuberculosis
Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; Gong, Chang; Kirschner, Denise E.
2015-01-01
Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. We describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oral and inhaled antibiotics, and (c) the effect of vaccination. PMID:25924949
Multi-Scale Jacobi Method for Anderson Localization
NASA Astrophysics Data System (ADS)
Imbrie, John Z.
2015-11-01
A new KAM-style proof of Anderson localization is obtained. A sequence of local rotations is defined, such that off-diagonal matrix elements of the Hamiltonian are driven rapidly to zero. This leads to the first proof via multi-scale analysis of exponential decay of the eigenfunction correlator (this implies strong dynamical localization). The method has been used in recent work on many-body localization (Imbrie in On many-body localization for quantum spin chains,
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2008-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. The following is presented in this report: (1) a brief review of the GCE model and its applications on the impact of aerosols on deep precipitation processes, (2) the Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) a discussion on the Goddard WRF version (its developments and applications).
A Multi-Scale Settlement Matching Algorithm Based on ARG
NASA Astrophysics Data System (ADS)
Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia
2016-06-01
Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Multi-scale simulation of ductile iron casting
NASA Astrophysics Data System (ADS)
Kubo, J.
2015-06-01
It has been well known that addition of rare earth elements was indispensable for production of ductile cast iron. The addition reduces solidification shrinkage. However there are still ambiguities in understanding the mechanism and predicting the casting defects. A possible explanation for the reduction of shrinkage is that the addition of rare earth promotes expansion of castings due to the graphite formation, which is related to cooling rate. In this study, the effect of rare earth addition was considered as a function of cooling rate and solidification shrinkage rate was determined by the macro-scale simulation. In the meso-scale and the micro-scale simulations, distribution of graphite nodules was compared with the experimental results. The multi-scale simulation result well reproduced the experimental results.
Predictive rendering of composite materials: a multi-scale approach
NASA Astrophysics Data System (ADS)
Muller, T.; Callet, P.; da Graça, F.; Paljic, A.; Porral, P.; Hoarau, R.
2015-03-01
Predictive rendering of material appearance means going deep into the understanding of the physical interaction between light and matter and how these interactions are perceived by the human brain. In this paper we describe our approach to predict the appearance of composite materials by relying on the multi-scale nature of the involved phenomena. Using recent works on physical modeling of complex materials, we show how to predict the aspect of a composite material based on its composition and its morphology. Specifically, we focus on the materials whose morphological structures are defined at several embedded scales. We rely on the assumption that when the inclusions in a composite material are smaller than the considered wavelength, the optical constants of the corresponding effective media can be computed by a homogenization process (or analytically for special cases) to be used into the Fresnel formulas.
Bounded multi-scale plasma simulation: Application to sheath problems
Parker, S.E. ); Friedman, A.; Ray. S.L. ); Birdsall, C.K. )
1993-08-01
In our previous paper we introduced the multi-scale method, a self-consistent plasma simulation technique that allowed particles to have independent timesteps. Here we apply the method to one-dimensional electrostatic bounded plasma problems and demonstrate a significant reduction in computing time. We describe a technique to allow for variable grid spacing and develop consistent boundary conditions for the direct implicit method. Also discussed are criteria for specifying timestep size as a function of position in phase space. Next, an analytically solvable sheath problem is presented, and a comparison to simulation results in made. Finally, we show results for an ion acoustic shock front propagating toward a conducting wall. 20 refs., 16 figs., 2 tabs.
Automatic image enhancement based on multi-scale image decomposition
NASA Astrophysics Data System (ADS)
Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong
2014-01-01
In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.
Multi-Scale Coupling in Ocean and Climate Modeling
Zhengyu Liu, Leslie Smith
2009-08-14
We have made significant progress on several projects aimed at understanding multi-scale dynamics in geophysical flows. Large-scale flows in the atmosphere and ocean are influenced by stable density stratification and rotation. The presence of stratification and rotation has important consequences through (i) the conservation of potential vorticity q = {omega} {center_dot} {del} {rho}, where {omega} is the total vorticity and {rho} is the density, and (ii) the existence of waves that affect the redistribution of energy from a given disturbance to the flow. Our research is centered on quantifying the effects of potential vorticity conservation and of wave interactions for the coupling of disparate time and space scales in the oceans and the atmosphere. Ultimately we expect the work to help improve predictive capabilities of atmosphere, ocean and climate modelers. The main findings of our research projects are described.
Multi-scale evaporator architectures for geothermal binary power plants
Sabau, Adrian S; Nejad, Ali; Klett, James William; Bejan, Adrian
2016-01-01
In this paper, novel geometries of heat exchanger architectures are proposed for evaporators that are used in Organic Rankine Cycles. A multi-scale heat exchanger concept was developed by employing successive plenums at several length-scale levels. Flow passages contain features at both macro-scale and micro-scale, which are designed from Constructal Theory principles. Aside from pumping power and overall thermal resistance, several factors were considered in order to fully assess the performance of the new heat exchangers, such as weight of metal structures, surface area per unit volume, and total footprint. Component simulations based on laminar flow correlations for supercritical R134a were used to obtain performance indicators.
The Potential Vorticity Budget of Multi-Scale MJO Models
NASA Astrophysics Data System (ADS)
Back, A.; Biello, J. A.; Majda, A.
2015-12-01
Zhang and Ling (J. Atmos. Sci. 2012) performed a comprehensive analysis of the potential vorticity budget of the Madden-Julian Oscillation throughout its initiation and evolution. Biello and Majda have used the Intraseasonal Planetary Equatorial Synoptic-Scale Dynamics (IPESD) framework of Majda and Klein (J. Atmos. Sci. 2003) to create kinematic models of the MJO which distinguish MJO events forced by large-scale heating from MJO events forced by the upscale fluxes of momentum and temperature from the synoptic scales. In the present study, the results of Zhang and Ling provide a benchmark for comparing the different multi-scale MJO models. In particular, a potential vorticity budget can be obtained in the multiscale framework, and the advection, in-scale generation and upscale transfer of PV are considered.
Multi-scale structures of turbulent magnetic reconnection
NASA Astrophysics Data System (ADS)
Nakamura, T. K. M.; Nakamura, R.; Narita, Y.; Baumjohann, W.; Daughton, W.
2016-05-01
We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in which modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.
Multi-Scale Patch-Based Image Restoration.
Papyan, Vardan; Elad, Michael
2016-01-01
Many image restoration algorithms in recent years are based on patch processing. The core idea is to decompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to the state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior is imposed on intermediate (patch) results, rather than on the final outcome, and this is typically manifested by visual artifacts. The expected patch log likelihood (EPLL) method by Zoran and Weiss was conceived for addressing this very problem. Their algorithm imposes the prior on the patches of the final image, which in turn leads to an iterative restoration of diminishing effect. In this paper, we propose to further extend and improve the EPLL by considering a multi-scale prior. Our algorithm imposes the very same prior on different scale patches extracted from the target image. While all the treated patches are of the same size, their footprint in the destination image varies due to subsampling. Our scheme comes to alleviate another shortcoming existing in patch-based restoration algorithms--the fact that a local (patch-based) prior is serving as a model for a global stochastic phenomenon. We motivate the use of the multi-scale EPLL by restricting ourselves to the simple Gaussian case, comparing the aforementioned algorithms and showing a clear advantage to the proposed method. We then demonstrate our algorithm in the context of image denoising, deblurring, and super-resolution, showing an improvement in performance both visually and quantitatively. PMID:26571527
Multi-scale edge detection with local noise estimate
NASA Astrophysics Data System (ADS)
Jiang, Bo; Rahman, Zia-ur
2010-08-01
The (unrealistic) assumption that noise can be modeled as independent, additive and uniform can lead to problems when edge detection methods are applied to real or natural images. The main reason for this is because filter scale and threshold for the gradient are difficult to determine at a regional or local scale when the noise estimate is on a global scale. A filter with one global scale might under-smooth areas of high noise, but over-smooth less noisy area. Similarly, a static, global threshold may not be appropriate for the entire image because different regions have different degrees of detail. Thus, some methods use more than one filter for detecting edges and discard the thresholding method in edge discrimination. Multi-scale description of the image mimics the receptive fields of neurons in the early visual cortex of animals. At the small scale, details can be reliably detected. At the larger scale, the contours or the frame get more attention. So, the image features can be fully represented by combining a range of scales. The proposed multi-scale edge detection algorithm utilizes this hierarchical organization to detect and localize edges. Furthermore, instead of using one default global threshold, local dynamic threshold is introduced to discriminate edge or non-edge. Based on a critical value function, the local dynamic threshold for each scale is determined using a novel local noise estimation (LNE) method. Additionally, the proposed algorithm performs connectivity analysis on edge map to ensure that small, disconnected edges are removed. Experiments where this method is applied to a sequence of images of the same scene but with different signal-noise-ratio (SNR), show the method to be robust to noise.
Multi-scale, multi-resolution brain cancer modeling.
Zhang, Le; Chen, L Leon; Deisboeck, Thomas S
2009-03-01
In advancing discrete-based computational cancer models towards clinical applications, one faces the dilemma of how to deal with an ever growing amount of biomedical data that ought to be incorporated eventually in one form or another. Model scalability becomes of paramount interest. In an effort to start addressing this critical issue, here, we present a novel multi-scale and multi-resolution agent-based in silico glioma model. While 'multi-scale' refers to employing an epidermal growth factor receptor (EGFR)-driven molecular network to process cellular phenotypic decisions within the micro-macroscopic environment, 'multi-resolution' is achieved through algorithms that classify cells to either active or inactive spatial clusters, which determine the resolution they are simulated at. The aim is to assign computational resources where and when they matter most for maintaining or improving the predictive power of the algorithm, onto specific tumor areas and at particular times. Using a previously described 2D brain tumor model, we have developed four different computational methods for achieving the multi-resolution scheme, three of which are designed to dynamically train on the high-resolution simulation that serves as control. To quantify the algorithms' performance, we rank them by weighing the distinct computational time savings of the simulation runs versus the methods' ability to accurately reproduce the high-resolution results of the control. Finally, to demonstrate the flexibility of the underlying concept, we show the added value of combining the two highest-ranked methods. The main finding of this work is that by pursuing a multi-resolution approach, one can reduce the computation time of a discrete-based model substantially while still maintaining a comparably high predictive power. This hints at even more computational savings in the more realistic 3D setting over time, and thus appears to outline a possible path to achieve scalability for the all
Multi-Scale Clustering by Building a Robust and Self Correcting Ultrametric Topology on Data Points
Fushing, Hsieh; Wang, Hui; VanderWaal, Kimberly; McCowan, Brenda; Koehl, Patrice
2013-01-01
The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets. PMID:23424653
Multi-scale clustering by building a robust and self correcting ultrametric topology on data points.
Fushing, Hsieh; Wang, Hui; Vanderwaal, Kimberly; McCowan, Brenda; Koehl, Patrice
2013-01-01
The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets. PMID:23424653
Object-Oriented Change Detection Based on Multi-Scale Approach
NASA Astrophysics Data System (ADS)
Jia, Yonghong; Zhou, Mingting; Jinshan, Ye
2016-06-01
The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.
Coupled Workflow Approach to Scalable Multi-Scale Subsurface Simulations
NASA Astrophysics Data System (ADS)
Schuchardt, K.; Agarwal, K.; Chase, J.; Scheibe, T. D.; Palmer, B. J.; Tartakovsky, A. M.
2012-12-01
Continuum scale models have been used to study subsurface flow, transport, and reactions for many years but lack the capability to resolve fine-grained processes. Recently, pore scale models, which operate at scales of individual soil grains, have been developed to more accurately model pore scale phenomena, such as mineral precipitation and dissolution reactions. Pore-scale methods to study microbially-mediated surface reactions are also under development. However, these finer-grained models are prohibitively expensive for modeling realistic domains. To apply these new techniques to realistic systems, we are developing a hybrid, multi-scale model which initially simulates the full domain at continuum scale and applies the pore scale model only to areas of high reactivity. Since the location and number of pore regions in the model varies as the reactions proceed, an adaptive Pore Generator code defines the number and location of pore regions at each continuum iteration. A fourth code provides data transformation from the pore scale back to the continuum scale. These components are loosely coupled into a single multi-scale model using the Swift workflow system for two reasons: we have several choices of simulators for the continuum and pore codes, and the mathematical model integration methods, data transformations, and adaptive behavior are all highly problem dependent at this time. Our approach provides a framework to solve new problems by replacing individual components. Our initial experiment simulates the parallel transport of two solutes with an irreversible mixing-controlled kinetic bimolecular reaction occurring at the interface between the two solutes. The system is filled with porous medium like sand. The sand is saturated with water, and two solutes (denoted A and B) are injected at the bottom and flow to the top at a specified rate. As the solutions flow upward through the flow cell, they mix along the centerline, leading to reaction and formation of a
Fractional-order elastic models of cartilage: A multi-scale approach
NASA Astrophysics Data System (ADS)
Magin, Richard L.; Royston, Thomas J.
2010-03-01
The objective of this research is to develop new quantitative methods to describe the elastic properties (e.g., shear modulus, viscosity) of biological tissues such as cartilage. Cartilage is a connective tissue that provides the lining for most of the joints in the body. Tissue histology of cartilage reveals a multi-scale architecture that spans a wide range from individual collagen and proteoglycan molecules to families of twisted macromolecular fibers and fibrils, and finally to a network of cells and extracellular matrix that form layers in the connective tissue. The principal cells in cartilage are chondrocytes that function at the microscopic scale by creating nano-scale networks of proteins whose biomechanical properties are ultimately expressed at the macroscopic scale in the tissue's viscoelasticity. The challenge for the bioengineer is to develop multi-scale modeling tools that predict the three-dimensional macro-scale mechanical performance of cartilage from micro-scale models. Magnetic resonance imaging (MRI) and MR elastography (MRE) provide a basis for developing such models based on the nondestructive biomechanical assessment of cartilage in vitro and in vivo. This approach, for example, uses MRI to visualize developing proto-cartilage structure, MRE to characterize the shear modulus of such structures, and fractional calculus to describe the dynamic behavior. Such models can be extended using hysteresis modeling to account for the non-linear nature of the tissue. These techniques extend the existing computational methods to predict stiffness and strength, to assess short versus long term load response, and to measure static versus dynamic response to mechanical loads over a wide range of frequencies (50-1500 Hz). In the future, such methods can perhaps be used to help identify early changes in regenerative connective tissue at the microscopic scale and to enable more effective diagnostic monitoring of the onset of disease.
Multi scale Disaster Risk Reduction Systems Space and Community based Experiences over HKH Region
NASA Astrophysics Data System (ADS)
Gurung, D. R.; Shrestha, M.; Shrestha, N.; Debnath, B.; Jishi, G.; Bajracharya, R.; Dhonju, H. K.; Pradhan, S.
2014-11-01
An increasing trend in the recurrence of natural disasters and associated impacts due to Floods, Glacier Lake out bursts, landslides and forest fire is reported over Hindu Kush Himalyan (HKH) region. Climate change and anthropogenic coupled factors are identified as primary factors for such increased vulnerability. The large degree of poverty, lack of infrastructure, poor accessibility and uncertainties involved in understanding high altitude land surface and climate dynamics poses serious challenges in reducing disaster vulnerability and mitigating disaster impacts. In this context effective development of Disaster Risk Reduction (DRR) protocols and mechanisms have been realized as an urgent need. The paper presents the adoption and experiences of multi scale DRR systems across different Himalayan member countries ranging from community based indigenous early warning to space based emergency response and decision support systems. The Establishment of a Regional Flood Information System (HKH-HYCOS) over Ganges-Brahmaputra-Meghna (GBM) and Indus river basins promoted the timely exchange of flood data and information for the reduction of flood vulnerability within and among the participating countries. Satellite based forest fire alert systems evoked significant response among diverse stakeholders to optimize fire incidence and control. Satellite rainfall estimation products, satellite altimetry based flood early warning systems, flood inundation modelling and products, model derived hydrology flow products from different global data-sharing networks constitutes diverse information to support multi scale DRR systems. Community-based Flood Early Warning System (FEWS) enabled by wireless technology established over the Singara and Jiadhal rivers in Assam also stands as one of the promising examples of minimizing flood risk. Disaster database and information system and decision support tools in Nepal serves as potential tool to support diverse stakeholders.
Kiviniemi, Vesa; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Haapea, Marianne; Silven, Olli; Tervonen, Osmo
2009-01-01
Temporal blood oxygen level dependent (BOLD) contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD) trends of the form 1/fα. Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF) after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant α, fractal dimension Df, and, Hurst exponent H) characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The α was able to differentiate also blood vessels from grey matter changes. Df was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow. PMID:19636388
A multi-scale strength model with phase transformation
NASA Astrophysics Data System (ADS)
Barton, Nathan; Arsenlis, Athanasios; Rhee, Moono; Marian, Jaime; Bernier, Joel V.; Tang, Meijie; Yang, Lin
2012-03-01
We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength model construction employs an information passing paradigm to span from the atomistic level to the continuum level. Simulation methods in the overall hierarchy include density functional theory, molecular statics, molecular dynamics, dislocation dynamics, and continuum based approaches. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate.
A multi-scale strength model with phase transformation
NASA Astrophysics Data System (ADS)
Barton, N.; Arsenlis, A.; Rhee, M.; Marian, J.; Bernier, J.; Tang, M.; Yang, L.
2011-06-01
We present a multi-scale strength model that includes phase transformation. In each phase, strength depends on pressure, strain rate, temperature, and evolving dislocation density descriptors. A donor cell type of approach is used for the transfer of dislocation density between phases. While the shear modulus can be modeled as smooth through the BCC to rhombohedral transformation in vanadium, the multi-phase strength model predicts abrupt changes in the material strength due to changes in dislocation kinetics. In the rhombohedral phase, the dislocation density is decomposed into populations associated with short and long Burgers vectors. Strength model construction employs an information passing paradigm to span from the atomistic level to the continuum level. Simulation methods in the overall hierarchy include density functional theory, molecular statics, molecular dynamics, dislocation dynamics, and continuum based approaches. We demonstrate the behavior of the model through simulations of Rayleigh Taylor instability growth experiments of the type used to assess material strength at high pressure and strain rate. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-ABS-464695).
Multi-Scale Investigation of Sheared Flows In Magnetized Plasmas
Edward, Jr., Thomas
2014-09-19
Flows parallel and perpendicular to magnetic fields in a plasma are important phenomena in many areas of plasma science research. The presence of these spatially inhomogeneous flows is often associated with the stability of the plasma. In fusion plasmas, these sheared flows can be stabilizing while in space plasmas, these sheared flows can be destabilizing. Because of this, there is broad interest in understanding the coupling between plasma stability and plasma flows. This research project has engaged in a study of the plasma response to spatially inhomogeneous plasma flows using three different experimental devices: the Auburn Linear Experiment for Instability Studies (ALEXIS) and the Compact Toroidal Hybrid (CTH) stellarator devices at Auburn University, and the Space Plasma Simulation Chamber (SPSC) at the Naval Research Laboratory. This work has shown that there is a commonality of the plasma response to sheared flows across a wide range of plasma parameters and magnetic field geometries. The goal of this multi-device, multi-scale project is to understand how sheared flows established by the same underlying physical mechanisms lead to different plasma responses in fusion, laboratory, and space plasmas.
Multi-scale modeling of the CD8 immune response
NASA Astrophysics Data System (ADS)
Barbarroux, Loic; Michel, Philippe; Adimy, Mostafa; Crauste, Fabien
2016-06-01
During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself in case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.
Physics of Multi-scale Convection In The Earth's Mantle
NASA Astrophysics Data System (ADS)
Korenaga, J.; Jordan, T. H.
We investigate the physics of multi-scale convection in the Earth's mantle, character- ized by the coexistence of large-scale mantle circulation associated plate tectonics and small-scale sublithospheric convection. Several basic scaling laws are derived, using a series of 2-D numerical modeling and 3-D linear stability analyses, for the following three distinct phases of sublithospheric convection: (1) onset of convection, (2) lay- ered convection in the upper mantle, and (3) breakdown of layered convection. First, the onset of convection with temperature-dependent viscosity is studied with 2-D con- vection models. A robust scaling law for onset time is derived by a nonlinear scaling analysis based on the concept of the differential Rayleigh number. Next, the planform of sublithospheric convection is studied by a 3-D linear stability analysis of longitu- dinal rolls in the presence of vertical shear. Finally, the temporal and spatial evolu- tion of sublithospheric convection is studied by 2-D whole-mantle convection models with temperature- and depth-dependent viscosity and an endothermic phase transition. Scaling laws for the breakdown of layered convection as well as the strength of con- vection are derived as a function of viscosity layering, the phase buoyancy parameter, and the thermal Rayleigh number. All of these scaling laws are combined to delineate possible dynamic regimes beneath evolving lithosphere.
Multi-Scale Dynamics of Twinning in SMA
NASA Astrophysics Data System (ADS)
Faran, Eilon; Shilo, Doron
2015-06-01
The mechanical response of shape memory alloys (SMA) is determined by the dynamics of discrete twin boundaries, and is quantified through constitutive material laws called kinetic relations. Extracting reliable kinetic relations, as well as revealing the physical characteristics of the energy barriers that dictate these relations, are essential for understanding and modeling the overall twinning phenomena. Here, we present a comprehensive, multi-scale study of discrete twin boundary dynamics in a ferromagnetic SMA, NiMnGa. The combination of dynamic-pulsed magnetic field experiments, in conjunction with low-rate uniaxial compression tests, leads to the identification of the dominant energy barriers for twinning. In particular, we show how different mechanisms of motion for overcoming the atomic-scale lattice potential give rise to several kinetic relations that are valid at different ranges of the driving force. In addition, a unique statistical analysis of the low-rate loading curve allows distinguishing between events at different length scales. This analysis leads to the identification of a characteristic length scale (~15 μm) for the distance between barriers that are responsible for the twinning stress property. This characteristic distance is in agreement with the typical thickness of the internal micro-twin structure, which was recently found in these materials.
Proximity graphs based multi-scale image segmentation
Skurikhin, Alexei N
2008-01-01
We present a novel multi-scale image segmentation approach based on irregular triangular and polygonal tessellations produced by proximity graphs. Our approach consists of two separate stages: polygonal seeds generation followed by an iterative bottom-up polygon agglomeration into larger chunks. We employ constrained Delaunay triangulation combined with the principles known from the visual perception to extract an initial ,irregular polygonal tessellation of the image. These initial polygons are built upon a triangular mesh composed of irregular sized triangles and their shapes are ad'apted to the image content. We then represent the image as a graph with vertices corresponding to the polygons and edges reflecting polygon relations. The segmentation problem is then formulated as Minimum Spanning Tree extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal grids by an iterative graph contraction constructing Minimum Spanning Tree. The contraction uses local information and merges the polygons bottom-up based on local region-and edge-based characteristics.
Detecting multi-scale filaments in galaxy distribution
NASA Astrophysics Data System (ADS)
Tempel, Elmo
2014-05-01
The main feature of the spatial large-scale galaxy distribution is its intricate network of galaxy filaments. This network is spanned by the galaxy locations that can be interpreted as a three-dimensional point distribution. The global properties of the point process can be measured by different statistical methods, which, however, do not describe directly the structure elements. The morphology of the large-scale structure, on the other hand, is an important property of the galaxy distribution. Here, we apply an object point process with interactions (the Bisous model) to trace and extract the filamentary network in the presently largest galaxy redshift survey, the Sloan Digital Sky Survey (SDSS data release 10). We search for multi-scale filaments in the galaxy distribution that have a radius of about 0.5, 1.0, 2.0, and 4.0 h -1 Mpc. We extract the spines of the filamentary network and divide the detected network into single filaments.
Multi-scale modelling of uranyl chloride solutions
Nguyen, Thanh-Nghi; Duvail, Magali Villard, Arnaud; Dufrêche, Jean-François; Molina, John Jairo; Guilbaud, Philippe
2015-01-14
Classical molecular dynamics simulations with explicit polarization have been successfully used to determine the structural and thermodynamic properties of binary aqueous solutions of uranyl chloride (UO{sub 2}Cl{sub 2}). Concentrated aqueous solutions of uranyl chloride have been studied to determine the hydration properties and the ion-ion interactions. The bond distances and the coordination number of the hydrated uranyl are in good agreement with available experimental data. Two stable positions of chloride in the second hydration shell of uranyl have been identified. The UO{sub 2}{sup 2+}-Cl{sup −} association constants have also been calculated using a multi-scale approach. First, the ion-ion potential averaged over the solvent configurations at infinite dilution (McMillan-Mayer potential) was calculated to establish the dissociation/association processes of UO{sub 2}{sup 2+}-Cl{sup −} ion pairs in aqueous solution. Then, the association constant was calculated from this potential. The value we obtained for the association constant is in good agreement with the experimental result (K{sub UO{sub 2Cl{sup +}}} = 1.48 l mol{sup −1}), but the resulting activity coefficient appears to be too low at molar concentration.
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems
Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei
2015-01-01
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems. In addition, high - resolution (spatial. 2km, and temporal, I minute) visualization showing the model results will be presented.
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
A multi-scale modeling system with unified physics has been developed at NASA Goddard Space Flight Center (GSFC). The system consists of an MMF, the coupled NASA Goddard finite-volume GCM (fvGCM) and Goddard Cumulus Ensemble model (GCE, a CRM); the state-of-the-art Weather Research and Forecasting model (WRF) and the stand alone GCE. These models can share the same microphysical schemes, radiation (including explicitly calculated cloud optical properties), and surface models that have been developed, improved and tested for different environments. In this talk, I will present: (1) A brief review on GCE model and its applications on the impact of the aerosol on deep precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications). We are also performing the inline tracer calculation to comprehend the ph ysical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.
Multi-scale investigation of shrub encroachment in southern Africa
NASA Astrophysics Data System (ADS)
Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah
2016-04-01
There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.
Progress in fast, accurate multi-scale climate simulations
Collins, W. D.; Johansen, H.; Evans, K. J.; Woodward, C. S.; Caldwell, P. M.
2015-06-01
We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less
Progress in fast, accurate multi-scale climate simulations
Collins, W. D.; Johansen, H.; Evans, K. J.; Woodward, C. S.; Caldwell, P. M.
2015-06-01
We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.
Multi-scale study of the isotope effect in ISTTOK
NASA Astrophysics Data System (ADS)
Liu, B.; Silva, C.; Figueiredo, H.; Pedrosa, M. A.; van Milligen, B. Ph.; Pereira, T.; Losada, U.; Hidalgo, C.
2016-05-01
The isotope effect, namely the isotope dependence of plasma confinement, is still one of the principal scientific conundrums facing the magnetic fusion community. We have investigated the impact of isotope mass on multi-scale mechanisms, including the characterization of radial correlation lengths (\\boldsymbol{L}{r} ) and long-range correlations (LRC) of plasma fluctuations using multi-array Langmuir probe system, in hydrogen (H) and deuterium (D) plasmas in the ISTTOK tokamak. We found that when changing plasma composition from the H dominated to D dominated, the LRC amplitude increased markedly (10–30%) and the \\boldsymbol{L}{r} increased slightly (~10%). The particle confinement also improved by about 50%. The changes of LRC and \\boldsymbol{L}{r} are congruent with previous findings in the TEXTOR tokamak (Xu et al 2013 Phys. Rev. Lett. 110 265005). In addition, using biorthogonal decomposition, both geodesic acoustic modes and very low frequency (<5 kHz) coherent modes were found to be contributing to LRC.
Probabilistic Simulation of Multi-Scale Composite Behavior
NASA Technical Reports Server (NTRS)
Chamis, Christos C.
2012-01-01
A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.
Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.
Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei
2015-01-01
The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063
Progress in Fast, Accurate Multi-scale Climate Simulations
Collins, William D; Johansen, Hans; Evans, Katherine J; Woodward, Carol S.; Caldwell, Peter
2015-01-01
We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy and fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.
Spontaneous Neural Dynamics and Multi-scale Network Organization
Foster, Brett L.; He, Biyu J.; Honey, Christopher J.; Jerbi, Karim; Maier, Alexander; Saalmann, Yuri B.
2016-01-01
Spontaneous neural activity has historically been viewed as task-irrelevant noise that should be controlled for via experimental design, and removed through data analysis. However, electrophysiology and functional MRI studies of spontaneous activity patterns, which have greatly increased in number over the past decade, have revealed a close correspondence between these intrinsic patterns and the structural network architecture of functional brain circuits. In particular, by analyzing the large-scale covariation of spontaneous hemodynamics, researchers are able to reliably identify functional networks in the human brain. Subsequent work has sought to identify the corresponding neural signatures via electrophysiological measurements, as this would elucidate the neural origin of spontaneous hemodynamics and would reveal the temporal dynamics of these processes across slower and faster timescales. Here we survey common approaches to quantifying spontaneous neural activity, reviewing their empirical success, and their correspondence with the findings of neuroimaging. We emphasize invasive electrophysiological measurements, which are amenable to amplitude- and phase-based analyses, and which can report variations in connectivity with high spatiotemporal precision. After summarizing key findings from the human brain, we survey work in animal models that display similar multi-scale properties. We highlight that, across many spatiotemporal scales, the covariance structure of spontaneous neural activity reflects structural properties of neural networks and dynamically tracks their functional repertoire. PMID:26903823
Multi-scale elastic graph matching for face detection
NASA Astrophysics Data System (ADS)
Sato, Yasuomi D.; Kuriya, Yasutaka
2013-12-01
We propose a multi-scale elastic graph matching (MS-EGM) algorithm for face detection, in which the conventional EGM is improved with two simple image processing techniques of the Gabor wavelet-based pyramid and the weak Gabor feature elimination. It is expected to solve difficulties of the real-time process in the conventional EGM. The Gabor wavelet-based pyramid effectively reduces not only the computational cost of the Gabor filtering but also the computational complexity of feature representation of a model face, preserving the facial information. The elimination of the weak Gabor feature extracted from an input image facilitates an accuracy of the Gabor feature similarity computations as unexpected. We then test that the MS-EGM can be capable of rapid face detection processing while achieving a high correct detection rate, comparable to the AdaBoost Haar-like (HL) feature cascade. We also show that the MS-EGM has strong robustness to the image of a face occluded with sunglasses and scarfs because of topologically preserved feature representations.
Extreme Precipitation in a Multi-Scale Modeling Framework
NASA Astrophysics Data System (ADS)
Phillips, M.; Denning, S.; Arabi, M.
2015-12-01
Extreme precipitation events are characterized by infrequent but large magnitude accummulatations that generally occur on scales belowthat resolved by the typical Global Climate Model. The Multi-scale Modeling Framework allows for information about the precipitation on these scales to be simulated for long periods of time without the large computational resources required for the use of a full cloud permitting model. The Community Earth System Model was run for 30 years in both its MMF and GCM modes, and the annual maximum series of 24 hour precipitation accumulations were used to estimate the parameters of statistical distributions. The distributions generated from model ouput were then t to a General Extreme Value distribution and evaluated against observations. These results indicate that the MMF produces extreme precipitation with a statistical distribution that closely resembles that of observations and motivates the continued use of the MMF for analysis of extreme precipitation, and shows an improvement over the traditional GCM. The improvement in statistical distributions of annual maxima is greatest in regions that are dominated by convective precipitation where the small-scale information provided by the MMF heavily influences precipitation processes.
Multi-Scale Modeling of Cross-Linked Nanotube Materials
NASA Technical Reports Server (NTRS)
Frankland, S. J. V.; Odegard, G. M.; Herzog, M. N.; Gates, T. S.; Fay, C. C.
2005-01-01
The effect of cross-linking single-walled carbon nanotubes on the Young's modulus of a nanotube-reinforced composite is modeled with a multi-scale method. The Young's modulus is predicted as a function of nanotube volume fraction and cross-link density. In this method, the constitutive properties of molecular representative volume elements are determined using molecular dynamics simulation and equivalent-continuum modeling. The Young's modulus is subsequently calculated for cross-linked nanotubes in a matrix which consists of the unreacted cross-linking agent. Two different cross-linking agents are used in this study, one that is short and rigid (Molecule A), and one that is long and flexible (Molecule B). Direct comparisons between the predicted elastic constants are made for the models in which the nanotubes are either covalently bonded or not chemically bonded to the cross-linking agent. At a nanotube volume fraction of 10%, the Young's modulus of Material A is not affected by nanotube crosslinking, while the Young's modulus of Material B is reduced by 64% when the nanotubes are cross-linked relative to the non-cross-linked material with the same matrix.
Multi-scale micromorphic theory for hierarchical materials
NASA Astrophysics Data System (ADS)
Vernerey, Franck; Liu, Wing Kam; Moran, Brian
2007-12-01
For the design of materials, it is important to faithfully model macroscopic materials response together with mechanisms and interactions occurring at the microstructural scales. While brute-force modeling of all the details of the microstructure is too costly, many of the current homogenized continuum models suffer from their inability to capture the correct underlying deformation mechanisms—especially when localization and failure are concerned. To overcome this limitation, a multi-scale continuum theory is proposed so that kinematic variables representing the deformation at various scales are incorporated. The method of virtual power is then used to derive a system of coupled governing equations, each representing a particular scale and its interactions with the macro-scale. A constitutive relation is then introduced to preserve the underlying physics associated with each scale. The inelastic behavior is represented by multiple yield functions, each representing a particular scale of microstructure, but collectively coupled through the same set of internal variables. The theory is illustrated by two applications. First, a one-dimensional example of a three-scale material is presented. After the onset of softening, the model shows that the localization zone is distributed according to two distinct length scale determined by the model. Second, a two-scale continuum model is introduced for the failure of porous metals. By comparing the theory to a direct numerical simulation (DNS) of the microstructure for a specimen in tension, we show that the model capture the main physics, and at the same time, remains computationally affordable.
Bridging the PSI Knowledge Gap: A Multi-Scale Approach
Wirth, Brian D
2015-01-08
Plasma-surface interactions (PSI) pose an immense scientific hurdle in magnetic confinement fusion and our present understanding of PSI in confinement environments is highly inadequate; indeed, a recent Fusion Energy Sciences Advisory Committee report found that 4 out of the 5 top five fusion knowledge gaps were related to PSI. The time is appropriate to develop a concentrated and synergistic science effort that would expand, exploit and integrate the wealth of laboratory ion-beam and plasma research, as well as exciting new computational tools, towards the goal of bridging the PSI knowledge gap. This effort would broadly advance plasma and material sciences, while providing critical knowledge towards progress in fusion PSI. This project involves the development of a Science Center focused on a new approach to PSI science; an approach that both exploits access to state-of-the-art PSI experiments and modeling, as well as confinement devices. The organizing principle is to develop synergistic experimental and modeling tools that treat the truly coupled multi-scale aspect of the PSI issues in confinement devices. This is motivated by the simple observation that while typical lab experiments and models allow independent manipulation of controlling variables, the confinement PSI environment is essentially self-determined with few outside controls. This means that processes that may be treated independently in laboratory experiments, because they involve vastly different physical and time scales, will now affect one another in the confinement environment. Also, lab experiments cannot simultaneously match all exposure conditions found in confinement devices typically forcing a linear extrapolation of lab results. At the same time programmatic limitations prevent confinement experiments alone from answering many key PSI questions. The resolution to this problem is to usefully exploit access to PSI science in lab devices, while retooling our thinking from a linear and de
Multi-Scale Initial Conditions For Cosmological Simulations
Hahn, Oliver; Abel, Tom; /KIPAC, Menlo Park /ZAH, Heidelberg /HITS, Heidelberg
2011-11-04
We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological 'zoom-in' simulations. The method uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). The new algorithm achieves rms relative errors of the order of 10{sup -4} for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier-space-induced interference ringing. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier-space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real-space-based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh-based codes that is consistent with the Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.
Modeling of Multi-Scale Channeling Phenomena in Porous Flow
NASA Astrophysics Data System (ADS)
Räss, Ludovic; Omlin, Samuel; Yarushina, Viktoriya; Simon, Nina; Podladchikov, Yuri
2015-04-01
Predictive modeling of fluid percolation through tight porous rocks is critical to evaluate environmental risks associated with waste storage and reservoir operations. To understand the evolution of two-phase mixtures of fluid and solid it is insufficient to only combine single-phase fluid flow methods and solid mechanics. A proper coupling of these two different multi-scales physical processes is required to describe the complex evolution of permeability and porosity in space and in time. We conduct numerical modeling experiments in geometrically simple but physically complex systems of stressed rocks containing self-focusing porous flow. Our model is physically and thermodynamically consistent and describes the formation and evolution of fluid pathways. The model consists of a system of coupled equations describing poro-elasto-viscous deformation and flow. Nonlinearity of the solid rheology is also taken into account. We have developed a numerical application based on an iterative finite difference scheme that runs on mutli-GPUs cluster in parallel. In order to validate these models, we consider the largest CO2 sequestration project in operation at the Sleipner field in the Norwegian North Sea. Attempts to match the observations at Sleipner using conventional reservoir simulations fail to capture first order observations, such as the seemingly effortless vertical flow of CO2 through low permeability shale layers and the formation of focused flow channels or chimneys. Conducted high-resolution three-dimensional numerical simulations predict the formation of dynamically evolving high porosity and permeability pathways as a natural outcome of porous flow nonlinearly coupled with rock deformation, which may trigger leakage through low permeability barriers.
Multi-scale photoacoustic remote sensing (PARS) (Conference Presentation)
NASA Astrophysics Data System (ADS)
Haji Reza, Parsin; Bell, Kevan; Shi, W.; Zemp, Roger J.
2016-03-01
We introduce a novel multi-scale photoacoustic remote sensing (PARS) imaging system. Our system can provide optical resolution details for superficial structures as well as acoustic resolution for deep-tissue imaging down to 5 cm, in a non-contact setting. PARS system does not require any contact with the sample or ultrasound coupling medium. The optical resolution PARS (OR-OARS) system uses optically focused pulsed excitation with optical detection of photoacoustic signatures using a long-coherence interrogation beam co-focused and co-scanned with the excitation spot. In the OR-PARS initial pressures are sampled right at their subsurface origin where acoustic pressures are largest. The Acoustic resolution PARS (AR-PARS) picks up the surface oscillation of the tissue caused by generated photoacoustic signal using a modified version of Michelson interferometry. By taking advantage of 4-meters polarization maintaining single-mode fiber and a green fiber laser we have generated a multi-wavelength source using stimulated Raman scattering. Remote functional imaging using this multi-wavelength excitation source and PARS detection mechanism has been demonstrated. The oxygen saturation estimations are shown for both phantom and in vivo studies. Images of blood vessel structures for an In vivo chicken embryo model is demonstrated. The Phantom studies indicates ~3µm and ~300µm lateral resolution for OR-PARS and AR-PARS respectively. To the best of our knowledge this is the first dual modality non-contact optical and acoustic resolution system used for in vivo imaging.
Multi-Scale Continuum Modeling of Biological Processes
Cheng, Y; Kekenes-Huskey, P; Hake, JE; Holst, MJ; McCammon, JA; Michailova, AP
2012-01-01
This article provides a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally-validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times with increasing ionic strength and demonstrate the role of an enzyme’s electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a non-linear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally-derived rodent ventricular myocyte geometries. Results reveal the important role for mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that the alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate subcellular Ca2+ signals. Model predicts that reduced off-rate in whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for integration of molecular-scale information into simulations of cellular-scale systems. PMID:23505398
Multi-scale surface-groundwater interactions: Processes and Implications
NASA Astrophysics Data System (ADS)
Packman, A. I.; Harvey, J. W.; Worman, A.; Cardenas, M. B.; Schumer, R.; Jerolmack, D. J.; Tank, J. L.; Stonedahl, S. H.
2009-05-01
Site-based investigations of stream-subsurface interactions normally focus on a limited range of spatial scales - typically either very shallow subsurface flows in the hyporheic zone, or much larger scale surface- groundwater interactions - but subsurface flows are linked across this entire continuum. Broad, multi-scale surface-groundwater interactions produce complex patterns in porewater flows, and interfacial fluxes do not average in a simple fashion because of the competitive effects of flows induced at different scales. For example, reach-scale stream-groundwater interactions produce sequences of gaining and losing reaches that can either suppress or enhance local-scale hyporheic exchange. Many individual topographic features also produce long power-law tails in surface residence time distributions, and the duration of these tails is greatly extended by interactions over a wide range of spatial scales. Simultaneous sediment transport and landscape evolution further complicates the analysis of porewater flow dynamics in rivers. Finally, inhomogeneity in important biogeochemical processes, particularly microbial processes that are stimulated near the sediment- water interface, leads to a great degree of non-linearity in chemical transformation rates in stream channels. This high degree of complexity in fluvial systems requires that careful approaches be used to extend local observations of hyporheic exchange and associated nutrient, carbon, and contaminant transformations to larger spatial scales. It is important to recognize that conventional advection-dispersion models are not expected to apply, and instead anomalous transport models must be used. Unfortunately, no generally applicable model is available for stream-groundwater interactions at the present time. Alternative approaches for modeling conservative and reactive transport will be discussed, and a strategy articulated for coping with the complexity of coupled surface-subsurface dynamics in fluvial
Multi-scale interactions during the Indonesian monsoon
NASA Astrophysics Data System (ADS)
Moron, Vincent; Robertson, Andrew W.; Qian, Jian-Hua
2010-05-01
The multi-scale interactions between El Niño Southern Oscillation (ENSO) and Indonesian monsoonal rainfall are analyzed using various datasets including daily rain gauges, high resolution satellites estimates of rainfall, atmospheric data taken from the National Center for Environmental Prediction (NCEP)/NCAR reanalysis and regional climate model version 3 (RegCM3) simulations with an horizontal resolution of 25 km from 1979 to 2006. We analyze interactions between large-scale ENSO-induced seasonal anomalies, synoptic scale of weather regimes defined through a k-means clustering of daily 850 hPa NCEP/NCAR winds and local scale and diurnal cycle of rainfall. The impact of ENSO is found to be largely spatially-uniform across the most of Indonesia during the spring-to-summer transition when the monsoon advances southeastward with a large delay (small advance) observed during warm (cold) ENSO events. The ENSO signal becomes more fragmented during the rainy season, from December. In particular, the large-scale seasonal easterly anomaly observed in low tropospheric levels (i.e. weakening of the austral summer monsoon) across Indonesia during warm ENSO events is found to be related to an increased frequency of a weather regime characterized by "quiescent" winds. RegCM3 outputs suggest that these weak winds tend to enhance the diurnal cycle and this leads to locally increased rainfall over mountains and the southern/western faces of the islands, such as Java. The ENSO signal is thus temporally and spatially coherent over the seas (i.e. anomalously dry during warm ENSO events), but more complex over the islands, with the spatially-uniform signal across Indonesia restricted to onset phase of the monsoon.
Strong, Multi-Scale Heterogeneity in Earth's Lowermost Mantle
NASA Astrophysics Data System (ADS)
Tkalčić, Hrvoje; Young, Mallory
2014-05-01
The ~300 km thick layer above the Earth's core mantle boundary remains largely an enigma and has proven to be far more than a simple dividing line; rather it is a complex region with a range of proposed phenomena such as thermal and compositional heterogeneity, partial melting and anisotropy. Characterizing the heterogeneity in the lowermost mantle will prove crucial to accurately understanding key geodynamical processes within our planet. Here we obtain compressional wave (P-wave) velocity images and uncertainty estimates for the lowermost mantle using old and newly collected travel time data sensitive to the lowermost mantle and core and collected by waveform cross-correlation. The images obtained by the inversion technique are void of explicit model parameterization and smoothing. To attest to the impressive capabilities of the transdimensional and hierarchical Bayesian inversion scheme, we design a comprehensive, all-embracing synthetic resolution test demonstrating the retrieval of velocity discontinuities, smooth velocity transitions, structures of varying scales and strengths. Subsequent spectral analyses reveal a power of heterogeneity three times larger than previous estimates and a multi-scale wavelength content in the P-wave velocity field of the lowermost mantle. The newly obtained P-wave tomographic images of the lowermost mantle are not dominated by harmonic degree 2 structure as is the case for tomographic images derived from S-wave data. Instead, the heterogeneity size is more uniformly distributed between about 500 and 6000 km. Inter alia, the resulting heterogeneity spectrum provides a bridge between the long-wavelength features of previous global models and the very short-scale dimensions of scatterers mapped in independent studies. Because the long scale features are less dominant in our model than in S-wave velocity maps, we cannot reasonably determine a correlation between them and the position of detected ultra-low velocity zones.
Multi-scale Modeling of Plasticity in Tantalum.
Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay; Buchheit, Thomas E.; Boyce, Brad; Weinberger, Christopher
2015-12-01
In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct
DAG Software Architectures for Multi-Scale Multi-Physics Problems at Petascale and Beyond
NASA Astrophysics Data System (ADS)
Berzins, Martin
2015-03-01
The challenge of computations at Petascale and beyond is to ensure how to make possible efficient calculations on possibly hundreds of thousands for cores or on large numbers of GPUs or Intel Xeon Phis. An important methodology for achieving this is at present thought to be that of asynchronous task-based parallelism. The success of this approach will be demonstrated using the Uintah software framework for the solution of coupled fluid-structure interaction problems with chemical reactions. The layered approach of this software makes it possible for the user to specify the physical problems without parallel code, for that specification to be translated into a parallel set of tasks. These tasks are executed using a runtime system that executes tasks asynchronously and sometimes out-of-order. The scalability and portability of this approach will be demonstrated using examples from large scale combustion problems, industrial detonations and multi-scale, multi-physics models. The challenges of scaling such calculations to the next generations of leadership class computers (with more than a hundred petaflops) will be discussed. Thanks to NSF, XSEDE, DOE NNSA, DOE NETL, DOE ALCC and DOE INCITE.
Multi-Scale Optical Imaging of the Delayed Type Hypersensitivity Reaction Attenuated by Rapamycin
Luo, Meijie; Zhang, Zhihong; Li, Hui; Qiao, Sha; Liu, Zheng; Fu, Ling; Shen, Guanxin; Luo, Qingming
2014-01-01
Neutrophils and monocytes/macrophages (MMs) play important roles in the development of cell-mediated delayed type hypersensitivity (DTH). However, the dynamics of neutrophils and MMs during the DTH reaction and how the immunosuppressant rapamycin modulates their behavior in vivo are rarely reported. Here, we take advantage of multi-scale optical imaging techniques and a footpad DTH reaction model to non-invasively investigate the dynamic behavior and properties of immune cells from the whole field of the footpad to the cellular level. During the classic elicitation phase of the DTH reaction, both neutrophils and MMs obviously accumulated at inflammatory foci at 24 h post-challenge. Rapamycin treatment resulted in advanced neutrophil recruitment and vascular hyperpermeability at an early stage (4 h), the reduced accumulation of neutrophils (> 50% inhibition ratio) at 48 h, and the delayed involvement of MMs in inflammatory foci. The motility parameters of immune cells in the rapamycin-treated reaction at 4 h post-challenge displayed similar mean velocities, arrest durations, mean displacements, and confinements as the classic DTH reaction at 24 h. These results indicate that rapamycin treatment shortened the initial preparation stage of the DTH reaction and attenuated its intensity, which may be due to the involvement of T helper type 2 cells or regulatory T cells. PMID:24465276
Progression to multi-scale models and the application to food system intervention strategies.
Gröhn, Yrjö T
2015-02-01
The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scale systems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an
Multi-scale evolution of a derecho-producing MCS
NASA Astrophysics Data System (ADS)
Bernardet, Ligia Ribeiro
1997-12-01
In this dissertation we address one type of severe weather: strong straight-line winds. In particular, we focus on derechos, a type of wind storm caused by a convective system and characterized by its long duration and by the large area it covers. One interesting characteristic of these storms is that they develop at night, on the cold side of a thermal boundary. This region is not characterized by large convective instability. In fact, surface parcels are generally stable with respect to vertical displacements. To gain understanding of the physical processes involved in these storms, we focused on the case of a MCS that developed in eastern Colorado on 12-13 May, 1985. The system formed in the afternoon, was active until early morning, and caused strong winds during the night. A multi-scale full physics simulation of this case was performed using a non-hydrostatic mesoscale model. Four telescopically nested grids covering from the synoptic scale down to cloud scale circulations were used. A Lagrangian model was used to follow trajectories of parcels that took part in the updraft and in the downdraft, and balance of forces were computed along the trajectories. Our results show that the synoptic and mesoscale environment of the storm largely influences convective organization and cloud-scale circulations. During the day, when the boundary layer is well mixed, the source of air for the clouds is located within the boundary layer. At night, when the boundary layer becomes stable, the source of air shifts to the top of the boundary layer. It is composed of warm, moist air that is brought by the nocturnal low-level jet. The downdraft structure also changes from day to night. During the day, parcels acquire negative buoyancy because of cooling due to evaporation and melting. As they sink, they remain colder than the environment, and end up at the surface constituting the cold pool. During the night, downdrafts are stronger, generating the strong surface winds. The most
Multi-scale indicators in CropWatch
NASA Astrophysics Data System (ADS)
Wu, B.; Gommes, R.; Zhang, M.; Zeng, H.; Yan, N.; Zhang, N.; Zou, W.; Chang, S.; Liu, G.
2013-12-01
separately. For China, a special indicator (crop type proportion, CTP) will be used to estimate planting area by crop type. Based on the multi-scale remote sensing based indicators, CropWatch can identify recent and noteworthy changes affecting wheat, maize, rice and soybean, and focus on trends that are likely to continue.
The Brera Multi-scale Wavelet ROSAT HRI source catalogue
NASA Astrophysics Data System (ADS)
Panzera, M. R.; Campana, S.; Covino, S.; Lazzati, D.; Mignani, R. P.; Moretti, A.; Tagliaferri, G.
2003-02-01
We present the Brera Multi-scale Wavelet ROSAT HRI source catalogue (BMW-HRI) derived from all ROSAT HRI pointed observations with exposure times longer than 100 s available in the ROSAT public archives. The data were analyzed automatically using a wavelet detection algorithm suited to the detection and characterization of both point-like and extended sources. This algorithm is able to detect and disentangle sources in very crowded fields and/or in the presence of extended or bright sources. Images have been also visually inspected after the analysis to ensure verification. The final catalogue, derived from 4303 observations, consists of 29 089 sources detected with a detection probability of >=4.2 sigma . For each source, the primary catalogue entries provide name, position, count rate, flux and extension along with the relative errors. In addition, results of cross-correlations with existing catalogues at different wavelengths (FIRST, IRAS, 2MASS and GSC2) are also reported. Some information is available on the web via the DIANA Interface. As an external check, we compared our catalogue with the previously available ROSHRICAT catalogue (both in its short and long versions) and we were able to recover, for the short version, ~ 90% of the entries. We computed the sky coverage of the entire HRI data set by means of simulations. The complete BMW-HRI catalogue provides a sky coverage of 732 deg2 down to a limiting flux of ~ 10-12 erg s-1 cm-2 and of 10 deg2 down to ~ 10-14 erg s-1 cm-2. We were able to compute the cosmological log(N)-log(S) distribution down to a flux of =~ 1.2 x 10-14 erg s-1 cm-2. The catalogue is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/399/351
Goal-oriented robot navigation learning using a multi-scale space representation.
Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A
2015-12-01
There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. PMID:26548944
Change detection based on integration of multi-scale mixed-resolution information
NASA Astrophysics Data System (ADS)
Wei, Li; Wang, Cheng; Wen, Chenglu
2016-03-01
In this paper, a new method of unsupervised change detection is proposed by modeling multi-scale change detector based on local mixed information and we present a method of automated threshold. A theoretical analysis is presented to demonstrate that more comprehensive information is taken into account by the integration of multi-scale information. The ROC curves show that change detector based on multi-scale mixed information(MSM) is more effective than based on mixed information(MIX). Experiments on artificial and real-world datasets indicate that the multi-scale change detection of mixed information can eliminate the pseudo-change part of the area. Therefore, the proposed algorithm MSM is an effective method for the application of change detection.
Weisgerber, D W; Erning, K; Flanagan, C L; Hollister, S J; Harley, B A C
2016-08-01
A particular challenge in biomaterial development for treating orthopedic injuries stems from the need to balance bioactive design criteria with the mechanical and geometric constraints governed by the physiological wound environment. Such trade-offs are of particular importance in large craniofacial bone defects which arise from both acute trauma and chronic conditions. Ongoing efforts in our laboratory have demonstrated a mineralized collagen biomaterial that can promote human mesenchymal stem cell osteogenesis in the absence of osteogenic media but that possesses suboptimal mechanical properties in regards to use in loaded wound sites. Here we demonstrate a multi-scale composite consisting of a highly bioactive mineralized collagen-glycosaminoglycan scaffold with micron-scale porosity and a polycaprolactone support frame (PCL) with millimeter-scale porosity. Fabrication of the composite was performed by impregnating the PCL support frame with the mineral scaffold precursor suspension prior to lyophilization. Here we evaluate the mechanical properties, permeability, and bioactivity of the resulting composite. Results indicated that the PCL support frame dominates the bulk mechanical response of the composite resulting in a 6000-fold increase in modulus compared to the mineral scaffold alone. Similarly, the incorporation of the mineral scaffold matrix into the composite resulted in a higher specific surface area compared to the PCL frame alone. The increased specific surface area in the collagen-PCL composite promoted increased initial attachment of porcine adipose derived stem cells versus the PCL construct. PMID:27104930
Self-Adaptive Event-Driven Simulation of Multi-Scale Plasma Systems
NASA Astrophysics Data System (ADS)
Omelchenko, Yuri; Karimabadi, Homayoun
2005-10-01
Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.
Multi-scale mechanical characterization of highly swollen photo-activated collagen hydrogels.
Tronci, Giuseppe; Grant, Colin A; Thomson, Neil H; Russell, Stephen J; Wood, David J
2015-01-01
Biological hydrogels have been increasingly sought after as wound dressings or scaffolds for regenerative medicine, owing to their inherent biofunctionality in biological environments. Especially in moist wound healing, the ideal material should absorb large amounts of wound exudate while remaining mechanically competent in situ. Despite their large hydration, however, current biological hydrogels still leave much to be desired in terms of mechanical properties in physiological conditions. To address this challenge, a multi-scale approach is presented for the synthetic design of cyto-compatible collagen hydrogels with tunable mechanical properties (from the nano- up to the macro-scale), uniquely high swelling ratios and retained (more than 70%) triple helical features. Type I collagen was covalently functionalized with three different monomers, i.e. 4-vinylbenzyl chloride, glycidyl methacrylate and methacrylic anhydride, respectively. Backbone rigidity, hydrogen-bonding capability and degree of functionalization (F: 16 ± 12-91 ± 7 mol%) of introduced moieties governed the structure-property relationships in resulting collagen networks, so that the swelling ratio (SR: 707 ± 51-1996 ± 182 wt%), bulk compressive modulus (Ec: 30 ± 7-168 ± 40 kPa) and atomic force microscopy elastic modulus (EAFM: 16 ± 2-387 ± 66 kPa) were readily adjusted. Because of their remarkably high swelling and mechanical properties, these tunable collagen hydrogels may be further exploited for the design of advanced dressings for chronic wound care. PMID:25411409
Multi-scale mechanical characterization of highly swollen photo-activated collagen hydrogels
Tronci, Giuseppe; Grant, Colin A.; Thomson, Neil H.; Russell, Stephen J.; Wood, David J.
2015-01-01
Biological hydrogels have been increasingly sought after as wound dressings or scaffolds for regenerative medicine, owing to their inherent biofunctionality in biological environments. Especially in moist wound healing, the ideal material should absorb large amounts of wound exudate while remaining mechanically competent in situ. Despite their large hydration, however, current biological hydrogels still leave much to be desired in terms of mechanical properties in physiological conditions. To address this challenge, a multi-scale approach is presented for the synthetic design of cyto-compatible collagen hydrogels with tunable mechanical properties (from the nano- up to the macro-scale), uniquely high swelling ratios and retained (more than 70%) triple helical features. Type I collagen was covalently functionalized with three different monomers, i.e. 4-vinylbenzyl chloride, glycidyl methacrylate and methacrylic anhydride, respectively. Backbone rigidity, hydrogen-bonding capability and degree of functionalization (F: 16 ± 12–91 ± 7 mol%) of introduced moieties governed the structure–property relationships in resulting collagen networks, so that the swelling ratio (SR: 707 ± 51–1996 ± 182 wt%), bulk compressive modulus (Ec: 30 ± 7–168 ± 40 kPa) and atomic force microscopy elastic modulus (EAFM: 16 ± 2–387 ± 66 kPa) were readily adjusted. Because of their remarkably high swelling and mechanical properties, these tunable collagen hydrogels may be further exploited for the design of advanced dressings for chronic wound care. PMID:25411409
Kinetic Approaches to Shear-Driven Magnetic Reconnection for Multi-Scale Modeling of CME Initiation
NASA Astrophysics Data System (ADS)
Black, C.; Antiochos, S. K.; DeVore, C.; Germaschewski, K.; Karpen, J. T.
2013-12-01
In the standard model for coronal mass ejections (CME) and/or solar flares, the free energy for the event resides in the strongly sheared magnetic field of a filament channel. The pre-eruption force balance, consisting of an upward force due to the magnetic pressure of the sheared field balanced by a downward tension due to overlying un-sheared field, is widely believed to be disrupted by magnetic reconnection. Therefore, understanding initiation of solar explosive phenomena requires a true multi-scale model of reconnection onset driven by the buildup of magnetic shear. While the application of magnetic-field shear is a trivial matter in MHD simulations, it is a significant challenge in a PIC code. The driver must be implemented in a self-consistent manner and with boundary conditions that avoid the generation of waves that destroy the applied shear. In this work, we describe drivers for 2.5D, aperiodic, PIC systems and discuss the implementation of driver-consistent boundary conditions that allow a net electric current to flow through the walls. Preliminary tests of these boundaries with a MHD equilibrium are shown. This work was supported, in part, by the NASA Living With a Star TR&T Program.
A Kinetic Approach to Shear Driven Magnetic Reconnection for Multi-Scale Modeling of CME Initiation
NASA Astrophysics Data System (ADS)
Black, Carrie; Antiochos, Spiro; DeVore, Rick; Germaschewski, Kai; Karpen, Judy
2013-10-01
In the standard model for coronal mass ejections (CME) and/or solar flares, the free energy for the event resides in the strongly sheared magnetic field of a filament channel. The pre-eruption force balance consisting of an upward force due to the magnetic pressure of the sheared field balanced by a downward tension due to overlying, un-sheared field is widely believed to be disrupted by magnetic reconnection. Therefore, understanding initiation of solar explosive phenomena requires a true multi-scale model of reconnection onset driven by the buildup of magnetic shear. While, the application of a magnetic field shear is a trivial matter in MHD simulations, it is significantly challenging to do so in a PIC code. The driver must be implemented in a self-consistent manner and with boundary conditions that avoid the generation of waves that destroy the applied shear. In this work, we describe such a driver for 2.5D, aperiodic, PIC system and discuss the implementation of driver consistent boundary conditions that allow a net electric current to flow through the walls. Preliminary tests of these boundaries with a MHD equilibrium are shown.
A multi-scale approach to the electronic structure of doped semiconductor surfaces
NASA Astrophysics Data System (ADS)
Sinai, Ofer; Hofmann, Oliver T.; Rinke, Patrick; Scheffler, Matthias; Heimel, Georg; Kronik, Leeor
2015-03-01
The inclusion of the global effects of semiconductor doping poses a unique challenge for first-principles simulations, because the typically low concentration of dopants renders an explicit treatment intractable. Furthermore, the width of the space-charge region (SCR) at charged surfaces often exceeds realistic supercell dimensions. We present a multi-scale technique that addresses these difficulties. It is based on the introduction of excess charge, mimicking free charge carriers from the SCR, along with a fixed sheet of counter-charge mimicking the SCR-related field. Self-consistency is obtained by imposing charge conservation and Fermi level equilibration between the bulk, treated semi-classically, and the electronic states of the slab/surface, which are treated quantum-mechanically. The method, called CREST - the Charge-Reservoir Electrostatic Sheet Technique - can be used with standard electronic structure codes. We validate CREST using a simple tight-binding model, which allows for comparison of its results with calculations encompassing the full SCR explicitly. We then employ it with density functional theory, obtaining insight into the doping dependence of the electronic structures of the metallic clean-cleaved Si(111) surface and its semiconducting (2x1) reconstructions.
NASA Astrophysics Data System (ADS)
Ling, Yue; Zaleski, Stéphane; Institut Jean Le Rond d'Alembert Team
2014-11-01
Numerical simulation is conducted to investigate the drop formation and evolution in gas-assisted atomization. The atomizer consists of two parallel planar jets: the fast gas jet and the slow liquid jet. Due to the shear between gas and liquid streams, the liquid-gas interface is unstable, and this eventually leads to full atomization. A fundamental challenge in atomization simulations is the existence of multiple length scales involved. In order to accurately capture both the gas-liquid interface instability and the drop dynamics, a multi-scale multiphase flow simulation strategy is proposed. In the present model, the gas-liquid interface is resolved by the Volume-of-Fluid (VOF) method, while the small drops are represented by Lagrangian point-particle (LPP) models. Particular attention is paid on validating the coupling and conversion between LPP and VOF. The present model is validated by comparing with direct numerical simulation (DNS) results and also experimental data. The simulation results show complex coupling between the interface instability and the turbulent gas jet, which in turn influence the formation and evolution of the drops formed in atomization. ANR-11-MONU-0011.
Properties of shocked polymers : Mbar experiments on Z and multi-scale simulations.
Mattsson, Thomas Kjell Rene
2010-03-01
Significant progress has been made over the last few years in understanding properties of matter subject to strong shocks and other extreme conditions. High-accuracy multi-Mbar experiments and first-principles theoretical studies together provide detailed insights into the physics and chemistry of high energy-density matter. While comprehensive advances have been made for pure elements like deuterium, helium, and carbon, progress has been slower for equally important, albeit more challenging, materials like molecular crystals, polymers, and foams. Hydrocarbon based polymer foams are common materials and in particular they are used in designing shock- and inertial confinement fusion experiments. Depending on their initial density, foams shock to relatively higher pressure and temperature compared to shocked dense polymers/plastics. As foams and polymers are shocked, they exhibit both structural and chemical transitions. We will present experimental and theoretical results for shocked polymers in the Mbar regime. By shock impact of magnetically launched flyer plates on poly(4-methyl-1-pentene) foams, we create multi-Mbar pressures in a dense plasma mixture of hydrogen, carbon, at temperatures of several eV. Concurrently with executing experiments, we analyze the system by multi-scale simulations, from density functional theory to continuum magneto-hydrodynamics simulations. In particular, density functional theory (DFT) molecular dynamics (MD) and classical MD simulations of the principal shock Hugoniot will be presented in detail for two hydrocarbon polymers: polyethylene (PE) and poly(4-methyl-1-pentene) (PMP).
Hosseini, Seyed Ali; Shah, Nilay
2011-01-01
There is a large body of literature regarding the choice and optimization of different processes for converting feedstock to bioethanol and bio-commodities; moreover, there has been some reasonable technological development in bioconversion methods over the past decade. However, the eventual cost and other important metrics relating to sustainability of biofuel production will be determined not only by the performance of the conversion process, but also by the performance of the entire supply chain from feedstock production to consumption. Moreover, in order to ensure world-class biorefinery performance, both the network and the individual components must be designed appropriately, and allocation of resources over the resulting infrastructure must effectively be performed. The goal of this work is to describe the key challenges in bioenergy supply chain modelling and then to develop a framework and methodology to show how multi-scale modelling can pave the way to answer holistic supply chain questions, such as the prospects for second generation bioenergy crops. PMID:22482032
NASA Astrophysics Data System (ADS)
Kim, Hyun; Shim, Bong Sup
2014-08-01
Electrogenetic tissues in human body such as central and peripheral nerve systems, muscular and cardiomuscular systems are soft and stretchable materials. However, most of the artificial materials, interfacing with those conductive tissues, such as neural electrodes and cardiac pacemakers, have stiff mechanical properties. The rather contradictory properties between natural and artificial materials usually cause critical incompatibility problems in implanting bodymachine interfaces for wide ranges of biomedical devices. Thus, we developed a stretchable and electrically conductive material with complex hierarchical structures; multi-scale microstructures and nanostructural electrical pathways. For biomedical purposes, an implantable polycaprolactone (PCL) membrane was coated by molecularly controlled layer-bylayer (LBL) assembly of single-walled carbon nanotubes (SWNTs) or poly(3,4-ethylenedioxythiophene) (PEDOT). The soft PCL membrane with asymmetric micro- and nano-pores provides elastic properties, while conductive SWNT or PEDOT coating preserves stable electrical conductivity even in a fully stretched state. This electrical conductivity enhanced ionic cell transmission and cell-to-cell interactions as well as electrical cellular stimulation on the membrane. Our novel stretchable conducting materials will overcome long-lasting challenges for bioelectronic applications by significantly reducing mechanical property gaps between tissues and artificial materials and by providing 3D interconnected electro-active pathways which can be available even at a fully stretched state.
SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling
Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi
2013-01-01
Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster. PMID:24163721
A Unified Multi-Scale Model for Pore-Scale Flow Simulations in Soils
Yang, Xiaofan; Liu, Chongxuan; Shang, Jianying; Fang, Yilin; Bailey, Vanessa L.
2014-01-30
Pore-scale simulations have received increasing interest in subsurface sciences to provide mechanistic insights into the macroscopic phenomena of water flow and reactive transport processes. The application of the pore scale simulations to soils and sediments is, however, challenged because of the characterization limitation that often only allows partial resolution of pore structure and geometry. A significant proportion of the pore space in soils and sediments is below the spatial resolution, forming a mixed media of pore and porous domains. Here we reported a unified multi-scale model (UMSM) that can be used to simulate water flow and transport in mixed media of pore and porous domains under both saturated and unsaturated conditions. The approach modifies the classic Navier-Stokes equation by adding a Darcy term to describe fluid momentum and uses a generalized mass balance equation for saturated and unsaturated conditions. By properly defining physical parameters, the UMSM can be applied in both pore and porous domains. This paper describes the set of equations for the UMSM, a series of validation cases under saturated or unsaturated conditions, and a real soil case for the application of the approach.
Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model
NASA Astrophysics Data System (ADS)
Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.
2012-12-01
The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that
Multi-scale analysis and characterization of the ITER pre-compression rings
NASA Astrophysics Data System (ADS)
Foussat, A.; Park, B.; Rajainmaki, H.
2014-01-01
The toroidal field (TF) system of ITER Tokamak composed of 18 "D" shaped Toroidal Field (TF) coils during an operating scenario experiences out-of-plane forces caused by the interaction between the 68kA operating TF current and the poloidal magnetic fields. In order to keep the induced static and cyclic stress range in the intercoil shear keys between coils cases within the ITER allowable limits [1], centripetal preload is introduced by means of S2 fiber-glass/epoxy composite pre-compression rings (PCRs). Those PCRs consist in two sets of three rings, each 5 m in diameter and 337 × 288 mm in cross-section, and are installed at the top and bottom regions to apply a total resultant preload of 70 MN per TF coil equivalent to about 400 MPa hoop stress. Recent developments of composites in the aerospace industry have accelerated the use of advanced composites as primary structural materials. The PCRs represent one of the most challenging composite applications of large dimensions and highly stressed structures operating at 4 K over a long term life. Efficient design of those pre-compression composite structures requires a detailed understanding of both the failure behavior of the structure and the fracture behavior of the material. Due to the inherent difficulties to carry out real scale testing campaign, there is a need to develop simulation tools to predict the multiple complex failure mechanisms in pre-compression rings. A framework contract was placed by ITER Organization with SENER Ingenieria y Sistemas SA to develop multi-scale models representative of the composite structure of the Pre-compression rings based on experimental material data. The predictive modeling based on ABAQUS FEM provides the opportunity both to understand better how PCR composites behave in operating conditions and to support the development of materials by the supplier with enhanced performance to withstand the machine design lifetime of 30,000 cycles. The multi-scale stress analysis has
Multi-scale Hydroacoustic Remote Sensing of Sturgeon and Their Habitats in A Large, Turbid River
NASA Astrophysics Data System (ADS)
Jacobson, R. B.; Delonay, A.; Vishy, C.; Elliott, C. M.; Reuter, J. M.; Chojnacki, K. A.
2009-12-01
Restoration and management of the Lower Missouri River (LMOR) to support recovery of the endangered pallid sturgeon (Scaphirhynchus albus) requires quantifying habitats used during all life stages in order to isolate specific habitats (if any) that present bottlenecks to reproduction and survival. All life stages of the pallid sturgeon take place in deep, turbid rivers where direct observation of habitat selection, movement, and behavior are impossible. Female pallid sturgeon reproduce only once every 3-5 years, but during a reproductive season they may migrate 10’s to 100’s of kilometers to spawn in patches of only several 100’s of square meters over a period of several hours. The broad ranges of spatial and temporal scales involved in understanding how particular life stages relate to their environment, as well as the technical challenges of working in a large river, dictate application of a multi-scale, remote-sensing approach. At the scale of the entire LMOR (1300 km), extensive hydroacoustic mapping using single-beam bathymetry, acoustic Doppler current profiling (ADCP), and substrate classification has been used to quantify the fundamental biophysical capacity of river segments in terms of frequency distributions of hydraulic variables. Coordinated telemetric tracking of reproductive fish provides an understanding of home range and habitat selection at reach to segment scales, over timeframes commensurate with 3-5 year reproductive cycles. Intensive reach-scale hydroacoustic mapping using multibeam bathymetry, ADCP, and high-resolution sidescan sonar, combined with intensive telemetric tracking, provide coincident measures of habitat availability and selection for upstream-migrating and spawning fish during reproductive seasons. These assessments measure habitat variables at sub-meter to bedform scales, commensurate with the scale at which fish occupy their habitat. For example, dual-frequency identification sonar (DIDSON) imagery indicates that during
Quasi-3D Multi-scale Modeling Framework Development
NASA Astrophysics Data System (ADS)
Arakawa, A.; Jung, J.
2008-12-01
When models are truncated in or near an energetically active range of the spectrum, model physics must be changed as the resolution changes. The model physics of GCMs and that of CRMs are, however, quite different from each other and at present there is no unified formulation of model physics that automatically provides transition between these model physics. The Quasi-3D (Q3D) Multi-scale Modeling Framework (MMF) is an attempt to bridge this gap. Like the recently proposed Heterogeneous Multiscale Method (HMM) (E and Engquist 2003), MMF combines a macroscopic model, GCM, and a microscopic model, CRM. Unlike the traditional multiscale methods such as the multi-grid and adapted mesh refinement techniques, HMM and MMF are for solving multi-physics problems. They share the common objective "to design combined macroscopic-microscopic computational methods that are much more efficient than solving the full microscopic model and at the same time give the information we need" (E et al. 2008). The question is then how to meet this objective in practice, which can be highly problem dependent. In HHM, the efficiency is gained typically by localization of the microscale problem. Following the pioneering work by Grabowski and Smolarkiewicz (1999) and Grabowski (2001), MMF takes advantage of the fact that 2D CRMs are reasonably successful in simulating deep clouds. In this approach, the efficiency is gained by sacrificing the three-dimensionality of cloud-scale motion. It also "localizes" the algorithm through embedding a CRM in each GCM grid box using cyclic boundary condition. The Q3D MMF is an attempt to reduce the expense due to these constraints by partially including the cloud-scale 3D effects and extending the CRM beyond individual GCM grid boxes. As currently formulated, the Q3D MMF is a 4D estimation/prediction framework that combines a GCM with a 3D anelastic cloud-resolving vector vorticity equation model (VVM) applied to a network of horizontal grids. The network
Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation
Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan
2010-01-01
Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939
MULTI-SCALE CLEAN: A COMPARISON OF ITS PERFORMANCE AGAINST CLASSICAL CLEAN ON GALAXIES USING THINGS
Rich, J. W.; De Blok, W. J. G.; Cornwell, T. J.; Brinks, E.; Bagetakos, I.; Walter, F.; Kennicutt, R. C. Jr E-mail: edeblok@ast.uct.ac.za E-mail: E.Brinks@herts.ac.uk E-mail: walter@mpia.de
2008-12-15
A practical evaluation of the multi-scale CLEAN algorithm is presented. The data used in the comparisons are taken from The H I Nearby Galaxy Survey. The implementation of multi-scale CLEAN in the CASA software package is used, although comparisons are made against the very similar multi-resolution CLEAN algorithm implemented in AIPS. Both are compared against the classical CLEAN algorithm (as implemented in AIPS). The results of this comparison show that several of the well-known characteristics and issues of using classical CLEAN are significantly lessened (or eliminated completely) when using the multi-scale CLEAN algorithm. Importantly, multi-scale CLEAN significantly reduces the effects of the clean 'bowl' that is caused by missing short-spacings, and the 'pedestal' of low-level un-cleaned flux (which affects flux scales and resolution). Multi-scale CLEAN can clean down to the noise level without the divergence suffered by classical CLEAN. We discuss practical applications of the added contrast provided by multi-scale CLEAN using two selected astronomical examples: H I holes in the interstellar medium and anomalous gas structures outside the main galactic disk.
Koppes, Abigail N; Kamath, Megha; Pfluger, Courtney A; Burkey, Daniel D; Dokmeci, Mehmet; Wang, Lin; Carrier, Rebecca L
2016-01-01
Native small intestine possesses distinct multi-scale structures (e.g., crypts, villi) not included in traditional 2D intestinal culture models for drug delivery and regenerative medicine. The known impact of structure on cell function motivates exploration of the influence of intestinal topography on the phenotype of cultured epithelial cells, but the irregular, macro- to submicron-scale features of native intestine are challenging to precisely replicate in cellular growth substrates. Herein, we utilized chemical vapor deposition of Parylene C on decellularized porcine small intestine to create polymeric intestinal replicas containing biomimetic irregular, multi-scale structures. These replicas were used as molds for polydimethylsiloxane (PDMS) growth substrates with macro to submicron intestinal topographical features. Resultant PDMS replicas exhibit multiscale resolution including macro- to micro-scale folds, crypt and villus structures, and submicron-scale features of the underlying basement membrane. After 10 d of human epithelial colorectal cell culture on PDMS substrates, the inclusion of biomimetic topographical features enhanced alkaline phosphatase expression 2.3-fold compared to flat controls, suggesting biomimetic topography is important in induced epithelial differentiation. This work presents a facile, inexpensive method for precisely replicating complex hierarchal features of native tissue, towards a new model for regenerative medicine and drug delivery for intestinal disorders and diseases. PMID:27550930
Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.; Giuly, Richard J.; Ellisman, Mark; Pfister, Hanspeter; Tasdizen, Tolga
2011-10-01
Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output of each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.
NASA Astrophysics Data System (ADS)
Wang, Y. D.; Liu, K. Y.; Yang, Y. S.; Ren, Y. Q.; Hu, T.; Deng, B.; Xiao, T. Q.
2016-04-01
Three dimensional (3D) characterization of shales has recently attracted wide attentions in relation to the growing importance of shale oil and gas. Obtaining a complete 3D compositional distribution of shale has proven to be challenging due to its multi-scale characteristics. A combined multi-energy X-ray micro-CT technique and data-constrained modelling (DCM) approach has been used to quantitatively investigate the multi-scale mineral and porosity distributions of a heterogeneous shale from the Junger Basin, northwestern China by sub-sampling. The 3D sub-resolution structures of minerals and pores in the samples are quantitatively obtained as the partial volume fraction distributions, with colours representing compositions. The shale sub-samples from two areas have different physical structures for minerals and pores, with the dominant minerals being feldspar and dolomite, respectively. Significant heterogeneities have been observed in the analysis. The sub-voxel sized pores form large interconnected clusters with fractal structures. The fractal dimensions of the largest clusters for both sub-samples were quantitatively calculated and found to be 2.34 and 2.86, respectively. The results are relevant in quantitative modelling of gas transport in shale reservoirs.
Multi-scale texture-based level-set segmentation of breast B-mode images.
Lang, Itai; Sklair-Levy, Miri; Spitzer, Hedva
2016-05-01
Automatic segmentation of ultrasonographic breast lesions is very challenging, due to the lesions' spiculated nature and the variance in shape and texture of the B-mode ultrasound images. Many studies have tried to answer this challenge by applying a variety of computational methods including: Markov random field, artificial neural networks, and active contours and level-set techniques. These studies focused on creating an automatic contour, with maximal resemblance to a manual contour, delineated by a trained radiologist. In this study, we have developed an algorithm, designed to capture the spiculated boundary of the lesion by using the properties from the corresponding ultrasonic image. This is primarily achieved through a unique multi-scale texture identifier (inspired by visual system models) integrated in a level-set framework. The algorithm׳s performance has been evaluated quantitatively via contour-based and region-based error metrics. We compared the algorithm-generated contour to a manual contour delineated by an expert radiologist. In addition, we suggest here a new method for performance evaluation where corrections made by the radiologist replace the algorithm-generated (original) result in the correction zones. The resulting corrected contour is then compared to the original version. The evaluation showed: (1) Mean absolute error of 0.5 pixels between the original and the corrected contour; (2) Overlapping area of 99.2% between the lesion regions, obtained by the algorithm and the corrected contour. These results are significantly better than those previously reported. In addition, we have examined the potential of our segmentation results to contribute to the discrimination between malignant and benign lesions. PMID:27010737
NASA Astrophysics Data System (ADS)
Mizukami, Naoki; Clark, Martyn; Newman, Andrew; Wood, Andy
2016-04-01
Estimation of spatially distributed parameters is one of the biggest challenges in hydrologic modeling over a large spatial domain. This problem arises from methodological challenges such as the transfer of calibrated parameters to ungauged locations. Consequently, many current large scale hydrologic assessments rely on spatially inconsistent parameter fields showing patchwork patterns resulting from individual basin calibration or spatially constant parameters resulting from the adoption of default or a-priori estimates. In this study we apply the Multi-scale Parameter Regionalization (MPR) framework (Samaniego et al., 2010) to generate spatially continuous and optimized parameter fields for the Variable Infiltration Capacity (VIC) model over the contiguous United States(CONUS). The MPR method uses transfer functions that relate geophysical attributes (e.g., soil) to model parameters (e.g., parameters that describe the storage and transmission of water) at the native resolution of the geophysical attribute data and then scale to the model spatial resolution with several scaling functions, e.g., arithmetic mean, harmonic mean, and geometric mean. Model parameter adjustments are made by calibrating the parameters of the transfer function rather than the model parameters themselves. In this presentation, we first discuss conceptual challenges in a "model agnostic" continental-domain application of the MPR approach. We describe development of transfer functions for the soil parameters, and discuss challenges associated with extending MPR for VIC to multiple models. Next, we discuss the "computational shortcut" of headwater basin calibration where we estimate the parameters for only 500 headwater basins rather than conducting simulations for every grid box across the entire domain. We first performed individual basin calibration to obtain a benchmark of the maximum achievable performance in each basin, and examined their transferability to the other basins. We then
The effect of multi-scale laser textured surface on lubrication regime
NASA Astrophysics Data System (ADS)
Segu, Dawit Zenebe; Choi, Si Geun; Choi, Jae hyouk; Kim, Seock Sam
2013-04-01
Laser surface texturing (LST) is a surface engineering process used to improve tribological characteristics of materials by creating patterned microstructures on the mechanical contact surface. In LST technology, a pulsated laser beam is used to create arranged dimples on surface by a material ablation process, which can improve load capacity, wear resistances, lubrication lifetime, and reduce friction coefficients. In the present study, the effect of multi-scale LST on lubricant regime was investigated. A pulsed Nd:YAG laser was applied on steel (AISI 52100) to create arranged dimples. To optimize the surface texturing effect on friction, multi-scale texture dimples with some specific formula arrays were fabricated by laser ablation process by combining circles and ellipses. The tribological testing of multi-scale textured surface was performed by a flat-on-flat unidirectional tribometer under lubrication, and the results compared with that of untextured surface. Through an increase in sliding speed and dimple depth the beneficial effect of multi-scale LST performance was achieved. The multi-scale textured surface had lower friction coefficient performance than the untextured surface due to hydrodynamic lubrication effect.
Multi-scale Characterization of Improved Algae Strains
Dale, Taraka T.
2015-04-01
This report relays the important role biofuels such as algae could have in the energy market. The report cites that problem of crude oil becoming less abundant while the demand for energy continues to rise. There are many benefits of producing energy with biofuels such as fewer carbon emissions as well as less land area to produce the same amount of energy compared to other sources of renewable fuels. One challenge that faces biofuels right now is the cost to produce it is high.
Modelling catchment non-stationarity - multi-scale modelling and data assimilation
NASA Astrophysics Data System (ADS)
Wheater, H. S.; Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.
2012-12-01
Modelling environmental change is in many senses a 'Grand Challenge' for hydrology, but poses major methodological challenges for hydrological models. Conceptual models represent complex processes in a simplified and spatially aggregated manner; typically parameters have no direct relationship to measurable physical properties. Calibration using observed data results in parameter equifinality, unless highly parsimonious model structures are employed. Use of such models to simulate effects of catchment non-stationarity is essentially speculative, unless attention is given to the analysis of parameter temporal variability in a non-stationary observation record. Black-box models are similarly constrained by the information content of the observational data. In contrast, distributed physics-based models provide a stronger theoretical basis for the prediction of change. However, while such models have parameters that are in principle measurable, in practice, for catchment-scale application, the measurement scale is inconsistent with the scale of model representation, the costs associated with such an exercise are high, and key properties are spatially variable, often strongly non-linear, and highly uncertain. In this paper we present a framework for modelling catchment non-stationarity that integrates information (with uncertainty) from multiple models and data sources. The context is the need to model the effects of agricultural land use change at multiple scales. A detailed UK multi-scale and multi-site experimental programme has provided data to support high resolution physics-based models of runoff processes that can, for example, represent the effects of soil structural change (due to grazing densities or trafficking), localised tree planting and drainage. Such models necessarily have high spatial resolution (1m in the horizontal plane, 1 cm in the vertical in this case), and hence can be applied at the scale of a field or hillslope element, but would be
NASA Astrophysics Data System (ADS)
Hosni, I.; JaafriGhamki, M.; Bennaceur Farah, L.; Naceur, M. S.
2015-04-01
In this paper, a multi-layered multi-scale backscattering model for a lossy medium and a neural network inversion procedure has been presented. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. An adapted three layers 2D MLS small perturbations (SPM) model has been used to describe radar backscattering response of semiarid sub-surfaces. The total reflection coefficients of the natural soil are computed using the multilayer model, and volumetric scattering is approximated by the internal reflections between layers. The original multi-scale SPM model includes only the surface scattering of the natural bare soil, while the multilayer soil modified 2D MLS SPM model includes both the surface scattering and the volumetric scattering within the soil. This multi-layered model has been used to calculate the total surface reflection coefficients of a natural soil surface for both horizontal and vertical co-polarizations. A parametric analysis presents the dependence of the backscattering coefficient on multi scale roughness and soil. The overall objective of this work is to retrieve soil surfaces parameters namely roughness and soil moisture related to the dielectric constant by inverting the radar backscattered signal from natural soil surfaces. To perform the inversion of the modified three layers 2D MLS SPM model, we used a multilayer neural network (NN) architecture trained by a back-propagation learning rule.
Multi-scale predictive modeling of nano-material and realistic electron devices
NASA Astrophysics Data System (ADS)
Palaria, Amritanshu
Among the challenges faced in further miniaturization of electronic devices, heavy influence of the detailed atomic configuration of the material(s) involved, which often differs significantly from that of the bulk material(s), is prominent. Device design has therefore become highly interrelated with material engineering at the atomic level. This thesis aims at outlining, with examples, a multi-scale simulation procedure that allows one to integrate material and device aspects of nano-electronic design to predict behavior of novel devices with novel material. This is followed in four parts: (1) An approach that combines a higher time scale reactive force field analysis with density functional theory to predict structure of new material is demonstrated for the first time for nanowires. Novel stable structures for very small diameter silicon nanowires are predicted. (2) Density functional theory is used to show that the new nanowire structures derived in 1 above have properties different from diamond core wires even though the surface bonds in some may be similar to the surface of bulk silicon. (3) Electronic structure of relatively large-scale germanium sections of realistically strained Si/strained Ge/ strained Si nanowire heterostructures is computed using empirical tight binding and it is shown that the average non-homogeneous strain in these structures drives their interesting non-conventional electronic characteristics such as hole effective masses which decrease as the wire cross-section is reduced. (4) It is shown that tight binding, though empirical in nature, is not necessarily limited to the material and atomic structure for which the parameters have been empirically derived, but that simple changes may adapt the derived parameters to new bond environments. Si (100) surface electronic structure is obtained from bulk Si parameters.
The potential vorticity budget of the multi-scale models of the MJO
NASA Astrophysics Data System (ADS)
Remmel, M.; Biello, J. A.; Majda, A.
2012-12-01
Zhang and Ling (J.Atmos Sci. 2012) performed a comprehensive analysis of the potential vorticity budget of the MJO, distinguishing it from Rossby and Kelvin waves. Biello and Majda have used the IPESD multi-scale framework of tropical dynamics to create kinematic models of the MJO which distinguish an MJO forced by in-scale heating with ones forced by fluxes of momentum and temperature from synoptic to MJO scales. In this study we use the results of Zhang and Ling as a benchmark for comparing the different multi-scale models. In particular, a PV budget can be obtained in the multi-scale framework, and PV advection, in-scale generation, and upscale generation terms are compared.
NASA Astrophysics Data System (ADS)
Bao, Wenxing; Feng, Wei; Ma, Ruishi
2015-12-01
In this paper, we proposed a new classification method based on support vector machine (SVM) combined with multi-scale segmentation. The proposed method obtains satisfactory segmentation results which are based on both the spectral characteristics and the shape parameters of segments. SVM method is used to label all these regions after multiscale segmentation. It can effectively improve the classification results. Firstly, the homogeneity of the object spectra, texture and shape are calculated from the input image. Secondly, multi-scale segmentation method is applied to the RS image. Combining graph theory based optimization with the multi-scale image segmentations, the resulting segments are merged regarding the heterogeneity criteria. Finally, based on the segmentation result, the model of SVM combined with spectrum texture classification is constructed and applied. The results show that the proposed method can effectively improve the remote sensing image classification accuracy and classification efficiency.
Triad interactions in multi-scale ITG/TEM/ETG turbulence
NASA Astrophysics Data System (ADS)
Maeyama, Shinya; Watanabe, Tomohiko; Idomura, Yasuhiro; Nakata, Motoki; Ishizawa, Akihiro; Nunami, Masanori
2015-11-01
Most of turbulent transport studies assume scale separation between electron- and ion-scale turbulence. However, latest massively parallel simulations based on gyrokinetics reveal that multi-scale interactions between electron- and ion-scale turbulence can influence turbulent transport [S. Maeyama, Phys. Rev. Lett. 114, 255002 (2015)]. The physical mechanism is investigated by applying triad transfer analysis. It is revealed that short-wave-length ITG turbulent eddies stabilize electron-scale streamers. Additionally, it is found that electron-scale turbulence has a damping effect on zonal flows. As a result, turbulent transport spectrum obtained from the multi-scale turbulence simulation differs from the sum of ones obtained from single-scale simulations. We will discuss gyrokinetic triad transfer analysis and the applicability of its fluid approximation, and explain the physical mechanism of multi-scale interactions by means of triad transfer analysis.
Multi-scale surface texture to improve blue response of nanoporous black silicon solar cells
NASA Astrophysics Data System (ADS)
Toor, Fatima; Branz, Howard M.; Page, Matthew R.; Jones, Kim M.; Yuan, Hao-Chih
2011-09-01
We characterize the optical and carrier-collection physics of multi-scale textured p-type black Si solar cells with conversion efficiency of 17.1%. The multi-scale texture is achieved by combining density-graded nanoporous layer made by metal-assisted etching with micron-scale pyramid texture. We found that (1) reducing the thickness of nanostructured Si layer improves the short-wavelength spectral response and (2) multi-scale texture permits thinning of the nanostructured layer while maintaining low surface reflection. We have reduced the nanostructured layer thickness by 60% while retaining a solar-spectrum-averaged black Si reflectance of less than 2%. Spectral response at 450 nm has improved from 57% to 71%.
Multi-scale radiographic applications in microelectronic industry
NASA Astrophysics Data System (ADS)
Gluch, J.; Löffler, M.; Meyendorf, N.; Oppermann, M.; Röllig, M.; Sättler, P.; Wolter, K. J.; Zschech, E.
2016-02-01
New concepts in assembly technology boost our daily life in an unknown way. High end semiconductor industry today deals with functional structures down to a few nanometers. ITRS roadmap predicts an ongoing decrease of the "DRAM half pitch" over the next decade. Packaging of course is not intended to realize pitches at the nanometer scale, but has to face the challenges of integrating such semiconductor devices with smallest pitch and high pin counts into systems. System integration (SiP, SoP, Hetero System Integration etc.) into the third dimension is the only way to reduce the gap between semiconductor level and packaging level interconnection. The described development is mainly driven by communication technology but also other branches like power electronics benefit from the vast progress in integration and assembly technology. The challenge of advanced packaging requires new nondestructive evaluation (NDE) techniques for technology development and production control. In power electronics production the condition monitoring receives a lot of interest to avoid electrical shortcuts, dead solder joints and interface cracking. It is also desired to detect and characterize very small defects like transportation phenomenon or Kirkendall voids. For this purpose imaging technologies with resolutions in the sub-micron range are required. Our presentation discusses the potentials and the limits of X-ray NDE techniques, illustrated by crack observation in solder joints, evaluation of micro vias in PCBs and interposers and the investigation of solder material composition and other aftermaths of electro migration in solder joints. Applied radiographic methods are X-ray through transmission, multi-energy techniques, laminography, CT and nano-CT.
NASA Astrophysics Data System (ADS)
Wei, Y.; Liu, S.; Huntzinger, D. N.; Michalak, A. M.; Viovy, N.; Post, W. M.; Schwalm, C. R.; Schaefer, K.; Jacobson, A. R.; Lu, C.; Tian, H.; Ricciuto, D. M.; Cook, R. B.; Mao, J.; Shi, X.
2014-12-01
Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model-model and model-observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.
NASA Astrophysics Data System (ADS)
Wei, Y.; Liu, S.; Huntzinger, D. N.; Michalak, A. M.; Viovy, N.; Post, W. M.; Schwalm, C. R.; Schaefer, K.; Jacobson, A. R.; Lu, C.; Tian, H.; Ricciuto, D. M.; Cook, R. B.; Mao, J.; Shi, X.
2013-11-01
Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM model skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model-model and model-observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land-use and land-cover change (LULCC), C3/C4 grasses fractions, major crops, phenology, and soil data into a standard format for global (0.5° x 0.5° resolution) and regional (North American, 0.25° x 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by changing the quality, the spatial and temporal coverage, resolution, or a combination of these. The resulting standardized model driver data sets are being used by over 20 different models participating MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.
Wei, Yaxing; Liu, Shishi; Huntzinger, Deborah N.; Michalak, Anna M.; Viovy, Nicolas; Post, Wilfred M.; Schwalm, Christopher R.; Schaeffer, Kevin; Jacobson, Andrew R.; Lu, Chaoqun; Tian, Hanqin; Ricciuto, Daniel M.; Cook, Robert B.; Mao, Jiafu; Shi, Xiaoying
2014-12-05
Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model model and model observation comparisons. In this article, we describe the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO_{2} concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5⁰ x 0.5⁰ resolution) and regional (North American: 0.25⁰ x 0.25⁰ resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. Lastly, the data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.
Wei, Yaxing; Liu, Shishi; Huntzinger, Deborah N.; Michalak, Anna M.; Viovy, Nicolas; Post, Wilfred M.; Schwalm, Christopher R.; Schaeffer, Kevin; Jacobson, Andrew R.; Lu, Chaoqun; et al
2014-12-05
Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model model and model observation comparisons. Inmore » this article, we describe the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5⁰ x 0.5⁰ resolution) and regional (North American: 0.25⁰ x 0.25⁰ resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. Lastly, the data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.« less
Multi-scale modelling of rubber-like materials and soft tissues: an appraisal
Puglisi, G.
2016-01-01
We survey, in a partial way, multi-scale approaches for the modelling of rubber-like and soft tissues and compare them with classical macroscopic phenomenological models. Our aim is to show how it is possible to obtain practical mathematical models for the mechanical behaviour of these materials incorporating mesoscopic (network scale) information. Multi-scale approaches are crucial for the theoretical comprehension and prediction of the complex mechanical response of these materials. Moreover, such models are fundamental in the perspective of the design, through manipulation at the micro- and nano-scales, of new polymeric and bioinspired materials with exceptional macroscopic properties. PMID:27118927
NASA Astrophysics Data System (ADS)
Blomley, R.; Jutzi, B.; Weinmann, M.
2016-06-01
In this paper, we address the classification of airborne laser scanning data. We present a novel methodology relying on the use of complementary types of geometric features extracted from multiple local neighbourhoods of different scale and type. To demonstrate the performance of our methodology, we present results of a detailed evaluation on a standard benchmark dataset and we show that the consideration of multi-scale, multi-type neighbourhoods as the basis for feature extraction leads to improved classification results in comparison to single-scale neighbourhoods as well as in comparison to multi-scale neighbourhoods of the same type.
NASA Astrophysics Data System (ADS)
Hong, M.; Yuan, G. D.; Peng, Y.; Chen, H. Y.; Zhang, Y.; Liu, Z. Q.; Wang, J. X.; Cai, B.; Zhu, Y. M.; Chen, Y.; Liu, J. H.; Li, J. M.
2014-06-01
We report an enhanced performance of multi-scale textured black silicon solar cell with power conversion efficiency of 15.5% by using anisotropic tetramethylammonium hydroxide etching to control the recombination. The multi-scale texture can effectively reduce the surface reflectance in a wide wavelength range, and both the surface and Auger recombination can be effectively suppressed by etching the samples after the n++ emitter formed. Our result shows that the reformed solar cell has higher conversion efficiency than that of conventional pyramid textured cell (15.3%). This work presents an effective method for improving the performance of nanostructured silicon solar cells.
Human visual system-based multi-scale tools with biomedical and security applications
NASA Astrophysics Data System (ADS)
Nercessian, Shahan
Multi-scale transforms have been shown to be invaluable tools for image processing. The effectiveness of consequently formulated multi-scale algorithms have practically made them de facto standards for realizing solutions for a broad range of image processing problems. Multi-scale formulations of transforms and algorithms are motivated by the ability of the human visual system (HVS) to extract edge structures at their different scales. Image processing algorithms, consequently, have been developed which alter multi-transform coefficients of images for various means. However, the multi-scale contrasts as defined by these schemes generally not consistent with many other relevant HVS phenomena. Upon reviewing relevant HVS characteristics, new tools which are consistent with these features are presented. Accordingly, new image enhancement, image de-noising, and image fusion algorithms which make use of HVS-inspired multi-scale tools are presented as contributions to each of these fields. In this context, the aim of the presented algorithms is two-fold: The intention is to both consider new multi-scale solutions, as well as to formulate them using perceptually-driven mathematical constructs based on HVS characteristics. In the context of image enhancement, a new set of multi-scale image enhancement algorithms are presented which are able to simultaneously provide both local and global enhancements within a direct enhancement framework. For the purpose of image de-noising, a multi-scale formulation of the non-local-means de-noising algorithm is developed which is shown to both visually and quantitatively outperform existing de-noising approaches. Many algorithms to achieve image fusion based on the presented transforms are presented. One set of algorithms is based on a Parameterized Logarithmic Image Processing model, while another is based on an adaptive similarity-based weighting scheme. The interdependence between the different algorithms considered in this
Multi-scale/multi-physical modeling in head/disk interface of magnetic data storage
NASA Astrophysics Data System (ADS)
Chung, Pil Seung; Smith, Robert; Vemuri, Sesha Hari; Jhon, Young In; Tak, Kyungjae; Moon, Il; Biegler, Lorenz T.; Jhon, Myung S.
2012-04-01
The model integration of the head-disk interface (HDI) in the hard disk drive system, which includes the hierarchy of highly interactive layers (magnetic layer, carbon overcoat (COC), lubricant, and air bearing system (ABS)), has recently been focused upon to resolve technical barriers and enhance reliability. Heat-assisted magnetic recording especially demands that the model simultaneously incorporates thermal and mechanical phenomena by considering the enormous combinatorial cases of materials and multi-scale/multi-physical phenomena. In this paper, we explore multi-scale/multi-physical simulation methods for HDI, which will holistically integrate magnetic layers, COC, lubricants, and ABS in non-isothermal conditions.
Multi-scale modelling for HEDP experiments on Orion
NASA Astrophysics Data System (ADS)
Sircombe, N. J.; Ramsay, M. G.; Hughes, S. J.; Hoarty, D. J.
2016-05-01
The Orion laser at AWE couples high energy long-pulse lasers with high intensity short-pulses, allowing material to be compressed beyond solid density and heated isochorically. This experimental capability has been demonstrated as a platform for conducting High Energy Density Physics material properties experiments. A clear understanding of the physics in experiments at this scale, combined with a robust, flexible and predictive modelling capability, is an important step towards more complex experimental platforms and ICF schemes which rely on high power lasers to achieve ignition. These experiments present a significant modelling challenge, the system is characterised by hydrodynamic effects over nanoseconds, driven by long-pulse lasers or the pre-pulse of the petawatt beams, and fast electron generation, transport, and heating effects over picoseconds, driven by short-pulse high intensity lasers. We describe the approach taken at AWE; to integrate a number of codes which capture the detailed physics for each spatial and temporal scale. Simulations of the heating of buried aluminium microdot targets are discussed and we consider the role such tools can play in understanding the impact of changes to the laser parameters, such as frequency and pre-pulse, as well as understanding effects which are difficult to observe experimentally.
De Jesus, Aribet M; Aghvami, Maziar; Sander, Edward A
2016-01-01
Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical
2016-01-01
Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours), structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants) were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks) remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient-specific mechanical
Multi-scale gravity field modeling in space and time
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2016-04-01
The Earth constantly deforms as it undergoes dynamic phenomena, such as earthquakes, post-glacial rebound and water displacement in its fluid envelopes. These processes have different spatial and temporal scales and are accompanied by mass displacements, which create temporal variations of the gravity field. Since 2002, the GRACE satellite missions provide an unprecedented view of the gravity field spatial and temporal variations. Gravity models built from these satellite data are essential to study the Earth's dynamic processes (Tapley et al., 2004). Up to present, time variations of the gravity field are often modelled using spatial spherical harmonics functions averaged over a fixed period, as 10 days or 1 month. This approach is well suited for modeling global phenomena. To better estimate gravity related to local and/or transient processes, such as earthquakes or floods, and adapt the temporal resolution of the model to its spatial resolution, we propose to model the gravity field using localized functions in space and time. For that, we build a model of the gravity field in space and time with a four-dimensional wavelet basis, well localized in space and time. First we design the 4D basis, then, we study the inverse problem to model the gravity field from the potential differences between the twin GRACE satellites, and its regularization using prior knowledge on the water cycle. Our demonstration of surface water mass signals decomposition in time and space is based on the use of synthetic along-track gravitational potential data. We test the developed approach on one year of 4D gravity modeling and compare the reconstructed water heights to those of the input hydrological model. Perspectives of this work is to apply the approach on real GRACE data, addressing the challenge of a realistic noise, to better describe and understand physical processus with high temporal resolution/low spatial resolution or the contrary.
NASA Astrophysics Data System (ADS)
Liu, C.; Yang, X.; Bailey, V. L.; Bond-Lamberty, B. P.; Hinkle, C.
2013-12-01
Mathematical representations of hydrological and biogeochemical processes in soil, plant, aquatic, and atmospheric systems vary with scale. Process-rich models are typically used to describe hydrological and biogeochemical processes at the pore and small scales, while empirical, correlation approaches are often used at the watershed and regional scales. A major challenge for multi-scale modeling is that water flow, biogeochemical processes, and reactive transport are described using different physical laws and/or expressions at the different scales. For example, the flow is governed by the Navier-Stokes equations at the pore-scale in soils, by the Darcy law in soil columns and aquifer, and by the Navier-Stokes equations again in open water bodies (ponds, lake, river) and atmosphere surface layer. This research explores whether the physical laws at the different scales and in different physical domains can be unified to form a unified multi-scale model (UMSM) to systematically investigate the cross-scale, cross-domain behavior of fundamental processes at different scales. This presentation will discuss our research on the concept, mathematical equations, and numerical execution of the UMSM. Three-dimensional, multi-scale hydrological processes at the Disney Wilderness Preservation (DWP) site, Florida will be used as an example for demonstrating the application of the UMSM. In this research, the UMSM was used to simulate hydrological processes in rooting zones at the pore and small scales including water migration in soils under saturated and unsaturated conditions, root-induced hydrological redistribution, and role of rooting zone biogeochemical properties (e.g., root exudates and microbial mucilage) on water storage and wetting/draining. The small scale simulation results were used to estimate effective water retention properties in soil columns that were superimposed on the bulk soil water retention properties at the DWP site. The UMSM parameterized from smaller
Geoelectrical Measurement of Multi-Scale Mass Transfer Parameters
Day-Lewis, Frederick David; Singha, Kamini; Johnson, Timothy C.; Haggerty, Roy; Binley, Andrew; Lane, John W.
2014-11-25
Mass transfer affects contaminant transport and is thought to control the efficiency of aquifer remediation at a number of sites within the Department of Energy (DOE) complex. An improved understanding of mass transfer is critical to meeting the enormous scientific and engineering challenges currently facing DOE. Informed design of site remedies and long-term stewardship of radionuclide-contaminated sites will require new cost-effective laboratory and field techniques to measure the parameters controlling mass transfer spatially and across a range of scales. In this project, we sought to capitalize on the geophysical signatures of mass transfer. Previous numerical modeling and pilot-scale field experiments suggested that mass transfer produces a geoelectrical signature—a hysteretic relation between sampled (mobile-domain) fluid conductivity and bulk (mobile + immobile) conductivity—over a range of scales relevant to aquifer remediation. In this work, we investigated the geoelectrical signature of mass transfer during tracer transport in a series of controlled experiments to determine the operation of controlling parameters, and also investigated the use of complex-resistivity (CR) as a means of quantifying mass transfer parameters in situ without tracer experiments. In an add-on component to our grant, we additionally considered nuclear magnetic resonance (NMR) to help parse mobile from immobile porosities. Including the NMR component, our revised study objectives were to: 1. Develop and demonstrate geophysical approaches to measure mass-transfer parameters spatially and over a range of scales, including the combination of electrical resistivity monitoring, tracer tests, complex resistivity, nuclear magnetic resonance, and materials characterization; and 2. Provide mass-transfer estimates for improved understanding of contaminant fate and transport at DOE sites, such as uranium transport at the Hanford 300 Area. To achieve our objectives, we implemented a 3
GPS Navigation for the Magnetospheric Multi-Scale Mission
NASA Technical Reports Server (NTRS)
Bamford, William; Mitchell, Jason; Southward, Michael; Baldwin, Philip; Winternitz, Luke; Heckler, Gregory; Kurichh, Rishi; Sirotzky, Steve
2009-01-01
In 2014. NASA is scheduled to launch the Magnetospheric Multiscale Mission (MMS), a four-satellite formation designed to monitor fluctuations in the Earth's magnetosphere. This mission has two planned phases with different orbits (1? x 12Re and 1.2 x 25Re) to allow for varying science regions of interest. To minimize ground resources and to mitigate the probability of collisions between formation members, an on-board orbit determination system consisting of a Global Positioning System (GPS) receiver and crosslink transceiver was desired. Candidate sensors would be required to acquire GPS signals both below and above the constellation while spinning at three revolutions-per-minute (RPM) and exchanging state and science information among the constellation. The Intersatellite Ranging and Alarm System (IRAS), developed by Goddard Space Flight Center (GSFC) was selected to meet this challenge. IRAS leverages the eight years of development GSFC has invested in the Navigator GPS receiver and its spacecraft communication expertise, culminating in a sensor capable of absolute and relative navigation as well as intersatellite communication. The Navigator is a state-of-the-art receiver designed to acquire and track weak GPS signals down to -147dBm. This innovation allows the receiver to track both the main lobe and the much weaker side lobe signals. The Navigator's four antenna inputs and 24 tracking channels, together with customized hardware and software, allow it to seamlessly maintain visibility while rotating. Additionally, an extended Kalman filter provides autonomous, near real-time, absolute state and time estimates. The Navigator made its maiden voyage on the Space Shuttle during the Hubble Servicing Mission, and is scheduled to fly on MMS as well as the Global Precipitation Measurement Mission (GPM). Additionally, Navigator's acquisition engine will be featured in the receiver being developed for the Orion vehicle. The crosslink transceiver is a 1/4 Watt transmitter
Multi-scale gas flow in Bazhen formation shales
NASA Astrophysics Data System (ADS)
Vasilyev, R.; Gerke, K.; Korost, D. V.; Karsanina, M.; Balushkina, N. S.; Kalmikov, G. A.; Mallants, D.
2013-12-01
scans (1 μm resolution). High resolution SEM images (with resolution up to 10 nm) are used to reconstruct the 3D structure of kerogen nanoporosity. Pore-networks are extracted directly from 3D images using the maximal ball extraction algorithm, or pore-network parameters were combined (pore and throat size distributions and connection number statistics) to merge macro and nanoscale porosities using a previously developed concept of under-resolution porosity (Korost and Gerke, 2012). Using analytical relationships between conductance and pressure for nanopores (Mehmani et al., 2013), the gas permeability was solved iteratively. For samples with dominant kerogen type nanoporosity we obtained satisfactory predictions of gas permeability. Finally, we also discuss current problems and future challenges (e.g., oil flow). This work was partially supported by RFBR grants 12-05-33089, 12-04-32264, 13-04-00409, 13-05-01176 and 12-05-01130.
Multi-Scale Multi-Species Modeling for Plasma Devices
NASA Astrophysics Data System (ADS)
Araki, Samuel Jun
This dissertation describes three computational models developed to simulate important aspects of low-temperature plasma devices, most notably ring-cusp ion discharges and thrusters. The main findings of this dissertation are related to (1) the mechanisms of cusp confinement for micro-scale plasmas, (2) the implementation and merits of magnetic field aligned meshes, and (3) an improved method for describing heavy species interactions. The Single Cusp (SC) model focuses on the near-cusp region of the discharge chamber to investigate the near surface cusp confinement of a micro-scale plasma. The model employs the multi-species iterative Monte Carlo method and uses various advanced methods such as electric field calculation and particle weighting algorithm that are compatible with a non-uniform mesh in cylindrical coordinates. Three different plasma conditions are simulated with the SC model, including an electron plasma, a sparse plasma, and a weakly ionized plasma. It is found that the scaling of plasma loss to the cusp for a sparse plasma can be similar to that for a weakly ionized plasma, while the loss mechanism is significantly different; the primary electrons strongly influence the loss structure of the sparse plasma. The model is also used, along with experimental results, to describe the importance of the local magnetic field on the primary electron loss behavior at the cusp. Many components of the 2D/3D hybrid fluid/particle model (DC-ION) are improved from the original version. The DC-ION code looks at the macroscopic structure of the discharge plasma and can be used to address the design and optimization challenges of miniature to micro discharges on the order of 3 cm to 1 cm in diameter. Among the work done for DC-ION, detailed steps for the magnetic field aligned (MFA) mesh are provided. Solving the plasma diffusion equation in the ring-cusp configuration, the benefit of the MFA mesh has been fully investigated by comparing the solution with a uniform
A real-time multi-scale 2D Gaussian filter based on FPGA
NASA Astrophysics Data System (ADS)
Luo, Haibo; Gai, Xingqin; Chang, Zheng; Hui, Bin
2014-11-01
Multi-scale 2-D Gaussian filter has been widely used in feature extraction (e.g. SIFT, edge etc.), image segmentation, image enhancement, image noise removing, multi-scale shape description etc. However, their computational complexity remains an issue for real-time image processing systems. Aimed at this problem, we propose a framework of multi-scale 2-D Gaussian filter based on FPGA in this paper. Firstly, a full-hardware architecture based on parallel pipeline was designed to achieve high throughput rate. Secondly, in order to save some multiplier, the 2-D convolution is separated into two 1-D convolutions. Thirdly, a dedicate first in first out memory named as CAFIFO (Column Addressing FIFO) was designed to avoid the error propagating induced by spark on clock. Finally, a shared memory framework was designed to reduce memory costs. As a demonstration, we realized a 3 scales 2-D Gaussian filter on a single ALTERA Cyclone III FPGA chip. Experimental results show that, the proposed framework can computing a Multi-scales 2-D Gaussian filtering within one pixel clock period, is further suitable for real-time image processing. Moreover, the main principle can be popularized to the other operators based on convolution, such as Gabor filter, Sobel operator and so on.
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper discusses a multi-scale remote sensing modeling system that fuses flux assessments generated with TIR imagery collected by multiple satellite platforms to estimate daily surface fluxes from field to global scales. The Landsat series of polar orbiting systems has collected TIR imagery at 6...
Boundary-constrained multi-scale segmentation method for remote sensing images
NASA Astrophysics Data System (ADS)
Zhang, Xueliang; Xiao, Pengfeng; Song, Xiaoqun; She, Jiangfeng
2013-04-01
Image segmentation is the key step of Object-Based Image Analysis (OBIA) in remote sensing. This paper proposes a Boundary-Constrained Multi-Scale Segmentation (BCMS) method. Firstly, adjacent pixels are aggregated to generate initial segmentation according to the local best region growing strategy. Then, the Region Adjacency Graph (RAG) is built based on initial segmentation. Finally, the local mutual best region merging strategy is applied on RAG to produce multi-scale segmentation results. During the region merging process, a Step-Wise Scale Parameter (SWSP) strategy is proposed to produce boundary-constrained multi-scale segmentation results. Moreover, in order to improve the accuracy of object boundaries, the property of edge strength is introduced as a merging criterion. A set of high spatial resolution remote sensing images is used in the experiment, e.g., QuickBird, WorldView, and aerial image, to evaluate the effectiveness of the proposed method. The segmentation results of BCMS are compared with those of the commercial image analysis software eCognition. The experiment shows that BCMS can produce nested multi-scale segmentations with accurate and smooth boundaries, which proves the robustness of the proposed method.
Using Multi-scale Modeling Systems to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2007-01-01
Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented.
A multi-scale non-local means algorithm for image de-noising
NASA Astrophysics Data System (ADS)
Nercessian, Shahan; Panetta, Karen A.; Agaian, Sos S.
2012-06-01
A highly studied problem in image processing and the field of electrical engineering in general is the recovery of a true signal from its noisy version. Images can be corrupted by noise during their acquisition or transmission stages. As noisy images are visually very poor in quality, and complicate further processing stages of computer vision systems, it is imperative to develop algorithms which effectively remove noise in images. In practice, it is a difficult task to effectively remove the noise while simultaneously retaining the edge structures within the image. Accordingly, many de-noising algorithms have been considered attempt to intelligent smooth the image while still preserving its details. Recently, a non-local means (NLM) de-noising algorithm was introduced, which exploited the redundant nature of images to achieve image de-noising. The algorithm was shown to outperform current de-noising standards, including Gaussian filtering, anisotropic diffusion, total variation minimization, and multi-scale transform coefficient thresholding. However, the NLM algorithm was developed in the spatial domain, and therefore, does not leverage the benefit that multi-scale transforms provide a framework in which signals can be better distinguished by noise. Accordingly, in this paper, a multi-scale NLM (MS-NLM) algorithm is proposed, which combines the advantage of the NLM algorithm and multi-scale image processing techniques. Experimental results via computer simulations illustrate that the MS-NLM algorithm outperforms the NLM, both visually and quantitatively.
Multi-scale methods for the solution of the radiative transfer equation
NASA Astrophysics Data System (ADS)
Coelho, Pedro J.; Crouseilles, Nicolas; Pereira, Pedro; Roger, Maxime
2016-03-01
Various methods have been developed and tested over the years to solve the radiative transfer equation (RTE) with different results and trade-offs. Although the RTE is extensively used, the approximate diffusion equation is sometimes preferred, particularly in optically thick media, due to the lower computational requirements. Recently, multi-scale models, namely the domain decomposition methods, the micro-macro model and the hybrid transport-diffusion model, have been proposed as an alternative to the RTE. In domain decomposition methods, the domain is split into two subdomains, namely a mesoscopic subdomain where the RTE is solved and a macroscopic subdomain where the diffusion equation is solved. In the micro-macro and hybrid transport-diffusion models, the radiation intensity is decomposed into a macroscopic component and a mesoscopic one. In both cases, the aim is to reduce the computational requirements, while maintaining the accuracy, or to improve the accuracy for similar computational requirements. In this paper, these multi-scale methods are described, and the application of the micro-macro and hybrid transport-diffusion models to three-dimensional transient problems is reported. It is shown that when the diffusion approximation is accurate, but not over the entire domain, the multi-scale methods may improve the solution accuracy in comparison with the solution of the RTE. The order of accuracy of the numerical schemes and the radiative properties of the medium play a key role in the performance of the multi-scale methods.
Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility
NASA Astrophysics Data System (ADS)
Kou, Jisheng; Sun, Shuyu
2016-08-01
In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests
Multi-Scale Scratch Analysis in Qinghai-Tibet Plateau and its Geological Implications
NASA Astrophysics Data System (ADS)
Sun, Yanyun; Yang, Wencai; Yu, Changqing
2016-04-01
Multi-scale scratch analysis on a regional gravity field is a new data processing system for depicting three-dimensional density structures and tectonic features. It comprises four modules including the spectral analysis of potential fields, multi-scale wavelet analysis, density distribution inversion, and scratch analysis. The multi-scale scratch analysis method was applied to regional gravity data to extract information about the deformation belts in the Qinghai-Tibet Plateau, which can help reveal variations of the deformation belts and plane distribution features from the upper crust to the lower crust, provide evidence for the study of three-dimensional crustal structures, and define distribution of deformation belts and mass movement. Results show the variation of deformation belts from the upper crust to the lower crust. The deformation belts vary from dense and thin in the upper crust to coarse and thick in the lower crust, demonstrating that vertical distribution of deformation belts resembles a tree with a coarse and thick trunk in the lower part and dense and thin branches at the top. The dense and thin deformation areas in the upper crust correspond to crustal shortening areas, while the thick and continuous deformation belts in the lower crust indicate the structural framework of the plateau. Additionally, the lower crustal deformation belts recognized by the multi-scale scratch analysis coincide approximately with the crustal deformation belts recognized using single-scale scratch analysis. However, deformation belts recognized by the latter are somewhat rough while multi-scale scratch analysis can provide more detailed and accurate results.
Using Multi-Scale Modeling Systems to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2010-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2010-01-01
In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.
Microphysics in the Multi-Scale Modeling Systems with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.
Multi-Scale Change Detection Research of Remotely Sensed Big Data in CyberGIS
NASA Astrophysics Data System (ADS)
Xing, J.; Sieber, R.
2015-12-01
Big remotely sensed data, the heterogeneity of satellite platforms and file formats along with increasing volumes and velocities, offers new types of analyses. This makes big remotely sensed data a good candidate for CyberGIS, the aim of which is to enable knowledge discovery of big data in the cloud. We apply CyberGIS to feature-based multi-scale land use/cover change (LUCC) detection. There have been attempts to do multi-scale LUCC. However, studies were done with small data and could not consider the mismatch between multi-scale analysis and computational scale. They have yet to consider the possibilities for scalar research across numerous temporal and spatial scales afforded by big data, especially if we want to advance beyond pixel-based analysis and also reduce preprocessing requirements. We create a geospatial cyberinfrastructure (GCI) to handle multi-spatio-temporal scale change detection. We first clarify different meanings of scale in CyberGIS and LUCC to derive a feature scope layer in the GCI based on Stommel modelling. Our analysis layer contains a multi-scale segmentation-based method based on normalized cut image segmentation and wavelet-based image scaling algorithms. Our computer resource utilization layer uses Wang and Armstrong's (2009) method for mainly for memory, I/O and CPU time. Our case is urban-rural change detection in the Greater Montreal Area (5 time periods, 2006-2012, 100 virtual machines), 36,000km2 and varying from 0.6m to 38m resolution. We present a ground truthed accuracy assessment of a change matrix that is composed of 6 feature classes at 12 different spatio-temporal scales, and the performance of the change detection GCI for multi-scale LUCC study. The GCI allows us to extract and coordinate different types of changes by varying spatio-temporal scales from the big imagery datasets.
Transferring Multi-Scale Approaches from 3d City Modeling to Ifc-Based Tunnel Modeling
NASA Astrophysics Data System (ADS)
Borrmann, A.; Kolbe, T. H.; Donaubauer, A.; Steuer, H.; Jubierre, J. R.
2013-09-01
A multi-scale representation of the built environment is required to provide information with the adequate level of detail (LoD) for different use cases and objectives. This applies not only to the visualization of city and building models, but in particular to their use in the context of planning and analysis tasks. While in the field of Geographic Information Systems, the handling of multi-scale representations is well established and understood, no formal approaches for incorporating multi-scale methods exist in the field of Building Information Modeling (BIM) so far. However, these concepts are much needed to better support highly dynamic planning processes that make use of very rough information about the facility under design in the early stages and provide increasingly detailed and fine-grained information in later stages. To meet these demands, this paper presents a comprehensive concept for incorporating multi-scale representations with infrastructural building information models, with a particular focus on the representation of shield tunnels. Based on a detailed analysis of the data modeling methods used in CityGML for capturing multiscale representations and the requirements present in the context of infrastructure planning projects, we discuss potential extensions to the BIM data model Industry Foundation Classes (IFC). Particular emphasis is put on providing means for preserving the consistency of the representation across the different Levels-of-Detail (LoD). To this end we make use of a procedural geometry description which makes it possible to define explicit dependencies between geometric entities on different LoDs. The modification of an object on a coarse level consequently results in an automated update of all dependent objects on the finer levels. Finally we discuss the transformation of the IFC-based multi-scale tunnel model into a CityGML compliant tunnel representation.
This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...
NASA Astrophysics Data System (ADS)
Hein, H.; Mai, S.; Mayer, B.; Pohlmann, T.; Barjenbruch, U.
2012-04-01
The interactions of tides, external surges, storm surges and waves with an additional role of the coastal bathymetry define the probability of extreme water levels at the coast. Probabilistic analysis and also process based numerical models allow the estimation of future states. From the physical point of view both, deterministic processes and stochastic residuals are the fundamentals of high water statistics. This study uses a so called model chain to reproduce historic statistics of tidal high water levels (Thw) as well as the prediction of future statistics high water levels. The results of the numerical models are post-processed by a stochastic analysis. Recent studies show, that for future extrapolation of extreme Thw nonstationary parametric approaches are required. With the presented methods a better prediction of time depended parameter sets seems possible. The investigation region of this study is the southern German Bright. The model-chain is the representation of a downscaling process, which starts with an emissions scenario. Regional atmospheric and ocean models refine the results of global climate models. The concept of downscaling was chosen to resolve coastal topography sufficiently. The North Sea and estuaries are modeled with the three-dimensional model HAMburg Shelf Ocean Model. The running time includes 150 years (1950 - 2100). Results of four different hindcast runs and also of one future prediction run are validated. Based on multi-scale analysis and the theory of entropy we analyze whether any significant periodicities are represented numerically. Results show that also hindcasting the climate of Thw with a model chain for the last 60 years is a challenging task. For example, an additional modeling activity must be the inclusion of tides into regional climate ocean models. It is found that the statistics of climate variables derived from model results differs from the statistics derived from measurements. E.g. there are considerable shifts in
NASA Astrophysics Data System (ADS)
Bhanumurthy, V.; Venugopala Rao, K.; Srinivasa Rao, S.; Ram Mohan Rao, K.; Chandra, P. Satya; Vidhyasagar, J.; Diwakar, P. G.; Dadhwal, V. K.
2014-11-01
emergency database systems. These include aspects such as i) data integration procedures namely standard coding scheme, schema, meta data format, spatial format ii) database organisation mechanism covering data management, catalogues, data models iii) database dissemination through a suitable environment, as a standard service for effective service dissemination. National Database for Emergency Management (NDEM) is such a comprehensive database for addressing disasters in India at the national level. This paper explains standards for integrating, organising the multi-scale and multi-source data with effective emergency response using customized user interfaces for NDEM. It presents standard procedure for building comprehensive emergency information systems for enabling emergency specific functions through geospatial technologies.
A multi-scale micromechanics framework for shale using the nano-tools
NASA Astrophysics Data System (ADS)
Ortega, J.; Ulm, F.; Abousleiman, Y.
2009-12-01
The successful prediction of poroelastic properties of fine-grained rocks such as shale continues to be a formidable challenge for the geophysics community. The highly heterogeneous nature of shale in terms of its compositional and microstructural features translates into a complex anisotropic behavior observed at macroscopic length scales. The recent application of instrumented indentation for the mechanical characterization of shale has revealed the granular response and intrinsic anisotropy of its porous clay phase at nanometer length scales [1-2]. This discovered mechanical behavior at the grain scale has been incorporated into the development of a multi-scale, micromechanics model for shale poroelasticity [3]. The only inputs to the model are two volumetric parameters synthesizing the mineralogy and porosity information of a shale sample. The model is meticulously calibrated and validated, as displayed in Fig. 1, with independent data sets of anisotropic elasticity obtained from nanoindentation experiments and standard laboratory acoustic measurements for shale specimens with and without organic content. The treatment of the elastic anisotropy corresponding to the porous clay fabric, as sensed by nanoindentation, delineates the contribution of the intrinsic anisotropy in shale to its overall anisotropy observed at macroscales. Furthermore, the proposed poroelastic formulation provides access to intrinsic rock parameters such as Biot pore pressure coefficients that are of importance for problems of flow in porous media. In addition, the model becomes a useful tool in geophysics applications for the prediction of shale acoustic properties from material-specific information such as porosity, mineralogy, and density measurements. References: [1] Ulm, F.-J., Abousleiman, Y. (2006) ‘The nanogranular nature of shale.’ Acta Geot. 1(2), 77-88. [2] Bobko, C., Ulm, F.-J. (2008) ‘The nano-mechanical morphology of shale.’ Mech. Mat. 40(4-5), 318-337. [3] Ortega, J
NASA Astrophysics Data System (ADS)
Chen, Dehui; Xue Xuesheng Yang, Jishan; Zhang, Hongliang; Hu, Jianglin; Jin, Zhiyan; Huang, Liping; Wu, Xiangjun
With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will become more and more complicated, and more and more "huge". The costs for improvement and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally; (4) variable or uniform resolution in option; (5) possibility to run in regional or global mode; (6) finite difference in the vertical discretization in option; (7) semi-implicit and semi - Lagrangian scheme; (8) height terrain-following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993). Key Words: numerical weather prediction, grid point model, non-hydrostatic, variable resolution, vertical spectral formulation
Multi-scale study of soil structure from different genetic horizons: from meter to nanometer
NASA Astrophysics Data System (ADS)
Karsanina, Marina; Skvortsova, Elena; Abrosimov, Konstantin; Sizonenko, Timofey; Romanenko, Konstantin; Belokhin, Vasily; Yudina, Anna; Gilyazetdinova, Dina; Korost, Dmitry; Gerke, Kirill
2016-04-01
Soil structure is extremely diverse, has numerous relevant scales, e.g., important pore hierarchical levels, such as intra and inter aggregate porosity, cracks and others. None of the existing imaging techniques is capable of catching all scales within one single image due to sample size/resolution limitations. The only way to experimentally obtain soil structural information from all important scales is to utilize multi-scale scanning using different imaging approaches. In this study we use macro X-ray tomography (with resolution of 100 um), micro X-ray tomography (with resolution range of 3-16 um) and SEM with nanoscale resolutions to obtain a vast multi-scale structural data from meter to nanometer. Two one meter long undisturbed soil columns extracted from soddy-podzolic and grey forest soils were used as objects of our multi-scale study. At first macrotomography was used to make the coarsest 3D image of the whole column. Afterwards, the column was carefully sliced to obtain smaller undisturbed samples for microtomography scanning. Some undisturbed soil pieces were also imaged using SEM to obtain sub-micron images of the soil structure. All resulting 2/3D images were segmented using up-to-date image processing and segmentation techniques to obtain solid material and pore space binary phases. Directional correlation functions were utilized to characterize multi-scale soil structures and compare/differentiate them from each other. We extensively show how such powerful structural descriptors as correlation functions can results in better soil structure characterization and classification. Combined with multi-scale image fusion and/or pore-scale modelling techniques 3D multi-scale images can used to assess scale dependant flow and transport properties. This work was partially supported by RFBR grant 15-34-20989 (field studies, X-ray tomography and SEM imaging) and RSF grant 14-17-00658 (directional correlation functions). References: 1. Karsanina, M.V., Gerke, K
NASA Astrophysics Data System (ADS)
Wilkinson, Mark; Owen, Gareth; Geris, Josie; Soulsby, Chris; Quinn, Paul
2015-04-01
Many communities across the world face the increasing challenge of balancing water quantity and quality issues with accommodating new growth and urban development. Urbanisation is typically associated with detrimental changes in water quality, sediment delivery, and effects on water storage and flow pathways (e.g. increases in flooding). In particular for mixed rural and urban catchments where the spatio-temporal variability of hydrological responses is high, there remains a key research challenge in evaluating the timing and magnitude of storage and flow pathways at multiple scales. This is of crucial importance for appropriate catchment management, for example to aid the design of Green Infrastructure (GI) to mitigate the risk of flooding, among other multiple benefits. The aim of this work was to (i) explore spatio-temporal storm runoff generation characteristics in multi-scale catchment experiments that contain rural and urban land use zones, and (ii) assess the (preliminary) impact of Sustainable Drainage (SuDs) as GI on high flow and flood characteristics. Our key research catchment, the Ouseburn in Northern England (55km2), has rural headwaters (15%) and an urban zone (45%) concentrated in the lower catchment area. There is an intermediate and increasingly expanding peri-urban zone (currently 40%), which is defined here as areas where rural and urban features coexist, alongside GIs. Such a structure is typical for most catchments with urban developments. We monitored spatial precipitation and multiscale nested (five gauges) runoff response, in addition to the storage dynamics in GIs for a period of 6 years (2007-2013). For a range of events, we examined the multiscale nested runoff characteristics (lag time and magnitude) of the rural and urban flow components, assessed how these integrated with changing land use and increasing scale, and discussed the implications for flood management in the catchment. The analyses indicated three distinctly different
On incremental non-linearity in granular media: phenomenological and multi-scale views
NASA Astrophysics Data System (ADS)
Darve, Félix; Nicot, François
2005-12-01
On the basis of fundamental constitutive laws such as elasticity, perfect plasticity, and pure viscosity, many elasto-viscoplastic constitutive relations have been developed since the 1970s through phenomenological approaches. In addition, a few more recent micro-mechanical models based on multi-scale approaches are now able to describe the main macroscopic features of the mechanical behaviour of granular media. The purpose of this paper is to compare a phenomenological constitutive relation and a micro-mechanical model with respect to a basic issue regularly raised about granular assemblies: the incrementally non-linear character of their behaviour. It is shown that both phenomenological and micro-mechanical models exhibit an incremental non-linearity. In addition, the multi-scale approach reveals that the macroscopic incremental non-linearity could stem from the change in the regime of local contacts between particles (from plastic regime to elastic regime) in terms of the incremental macroscopic loading direction. Copyright
Multi-scale periodic homogenization of ionic transfer in cementitious materials
NASA Astrophysics Data System (ADS)
Bourbatache, K.; Millet, O.; Aït-Mokhtar, A.
2016-08-01
A multi-scale periodic homogenization procedure of the ionic transfers in saturated porous media is proposed. An application on a multi-scale porous material was achieved for establishing models describing a ionic transfer from Nernst-Planck-Poisson-Boltzmann system. The first one is obtained by homogenization from the scale of Debye length to the capillary porosity scale, by taking into account the electrical double layer phenomenon. The second one results from another homogenization procedure from the capillary porosity scale to the scale of the material, where the electrical double layer effects are naturally negligible. A numerical parametric study is conducted on three dimensional elementary cells in order to highlight the effects of the electrical double layer on the ionic transfer parameters. Comparisons with existing experimental data are also presented and discussed. The double homogenization procedure gives homogenized diffusion coefficients very close to those obtained experimentally for chlorides ions from electrodiffusion tests carried out in laboratory.
NASA Astrophysics Data System (ADS)
Lee, Sangmin; Sastry, Ann Marie; Park, Jonghyun
2016-05-01
Performance and degradation of a Li-ion battery reflect the transport and kinetics of related species within the battery's electrode microstructures. The variational multi-scale principle is adapted to a Li-ion battery system in order to improve the predictions of battery performance by including multi-scale and multiphysics phenomena among the particle aggregates in the electrode; this physics cannot be addressed by conventional homogenized approaches. The developed model is verified through the direct numerical solutions and compared with the conventional pseudo-2D (P2D) model method. The developed model has revealed more dynamic battery behaviors related to the variation of the microstructure-such as particle shape, tortuosity, and material composition-while the corresponding result from P2D shows a monotonous change within different structures.
Multi-Scale Modeling of a Graphite-Epoxy-Nanotube System
NASA Technical Reports Server (NTRS)
Frankland, S. J. V.; Riddick, J. C.; Gates, T. S.
2005-01-01
A multi-scale method is utilized to determine some of the constitutive properties of a three component graphite-epoxy-nanotube system. This system is of interest because carbon nanotubes have been proposed as stiffening and toughening agents in the interlaminar regions of carbon fiber/epoxy laminates. The multi-scale method uses molecular dynamics simulation and equivalent-continuum modeling to compute three of the elastic constants of the graphite-epoxy-nanotube system: C11, C22, and C33. The 1-direction is along the nanotube axis, and the graphene sheets lie in the 1-2 plane. It was found that the C11 is only 4% larger than the C22. The nanotube therefore does have a small, but positive effect on the constitutive properties in the interlaminar region.
A Multi-Scale Algorithm for Graffito Advertisement Detection from Images of Real Estate
NASA Astrophysics Data System (ADS)
Yang, Jun; Zhu, Shi-Jiao
There is a significant need to detect and extract the graffito advertisement embedded in the housing images automatically. However, it is a hard job to separate the advertisement region well since housing images generally have complex background. In this paper, a detecting algorithm which uses multi-scale Gabor filters to identify graffito regions is proposed. Firstly, multi-scale Gabor filters with different directions are applied to housing images, then the approach uses these frequency data to find likely graffito regions using the relationship of different channels, it exploits the ability of different filters technique to solve the detection problem with low computational efforts. Lastly, the method is tested on several real estate images which are embedded graffito advertisement to verify its robustness and efficiency. The experiments demonstrate graffito regions can be detected quite well.
Sen, Oishik; Davis, Sean; Jacobs, Gustaaf; Udaykumar, H.S.
2015-08-01
The effectiveness of several metamodeling techniques, viz. the Polynomial Stochastic Collocation method, Adaptive Stochastic Collocation method, a Radial Basis Function Neural Network, a Kriging Method and a Dynamic Kriging Method is evaluated. This is done with the express purpose of using metamodels to bridge scales between micro- and macro-scale models in a multi-scale multimaterial simulation. The rate of convergence of the error when used to reconstruct hypersurfaces of known functions is studied. For sufficiently large number of training points, Stochastic Collocation methods generally converge faster than the other metamodeling techniques, while the DKG method converges faster when the number of input points is less than 100 in a two-dimensional parameter space. Because the input points correspond to computationally expensive micro/meso-scale computations, the DKG is favored for bridging scales in a multi-scale solver.
A multi-scale modeling framework for instabilities of film/substrate systems
NASA Astrophysics Data System (ADS)
Xu, Fan; Potier-Ferry, Michel
2016-01-01
Spatial pattern formation in stiff thin films on soft substrates is investigated from a multi-scale point of view based on a technique of slowly varying Fourier coefficients. A general macroscopic modeling framework is developed and then a simplified macroscopic model is derived. The model incorporates Asymptotic Numerical Method (ANM) as a robust path-following technique to trace the post-buckling evolution path and to predict secondary bifurcations. The proposed multi-scale finite element framework allows sinusoidal and square checkerboard patterns as well as their bifurcation portraits to be described from a quantitative standpoint. Moreover, it provides an efficient way to compute large-scale instability problems with a significant reduction of computational cost compared to full models.
Multi-class and multi-scale models of complex biological phenomena.
Yu, Jessica S; Bagheri, Neda
2016-06-01
Computational modeling has significantly impacted our ability to analyze vast (and exponentially increasing) quantities of experimental data for a variety of applications, such as drug discovery and disease forecasting. Single-scale, single-class models persist as the most common group of models, but biological complexity often demands more sophisticated approaches. This review surveys modeling approaches that are multi-class (incorporating multiple model types) and/or multi-scale (accounting for multiple spatial or temporal scales) and describes how these models, and combinations thereof, should be used within the context of the problem statement. We end by highlighting agent-based models as an intuitive, modular, and flexible framework within which multi-scale and multi-class models can be implemented. PMID:27115496
An Investigation of Wavelet Bases for Grid-Based Multi-Scale Simulations Final Report
Baty, R.S.; Burns, S.P.; Christon, M.A.; Roach, D.W.; Trucano, T.G.; Voth, T.E.; Weatherby, J.R.; Womble, D.E.
1998-11-01
The research summarized in this report is the result of a two-year effort that has focused on evaluating the viability of wavelet bases for the solution of partial differential equations. The primary objective for this work has been to establish a foundation for hierarchical/wavelet simulation methods based upon numerical performance, computational efficiency, and the ability to exploit the hierarchical adaptive nature of wavelets. This work has demonstrated that hierarchical bases can be effective for problems with a dominant elliptic character. However, the strict enforcement of orthogonality was found to be less desirable than weaker semi-orthogonality or bi-orthogonality for solving partial differential equations. This conclusion has led to the development of a multi-scale linear finite element based on a hierarchical change of basis. The reproducing kernel particle method has been found to yield extremely accurate phase characteristics for hyperbolic problems while providing a convenient framework for multi-scale analyses.
NASA Astrophysics Data System (ADS)
Guo, Li; Guo, XiaoMing; Mi, ChangWen
2012-09-01
In this paper, we propose a concurrent multi-scale finite element (FE) model coupling equations of the degree of freedoms of meso-scale model of ITZs and macroscopic model of bulk pastes. The multi-scale model is subsequently implemented and integrated into ABAQUS resulting in easy application to complex concrete structures. A few benchmark numerical examples are performed to test both the accuracy and efficiency of the developed model in analyzing chloride diffusion in concrete. These examples clearly demonstrate that high diffusivity of ITZs, primarily because of its porous microstructure, tends to accelerate chloride penetration along concentration gradient. The proposed model provides new guidelines for the durability analysis of concrete structures under adverse operating conditions.
Application of multi-scale feature extraction to surface defect classification of hot-rolled steels
NASA Astrophysics Data System (ADS)
Xu, Ke; Ai, Yong-hao; Wu, Xiu-yong
2013-01-01
Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis (MGA) were employed to decompose the image into several directional subbands at several scales. Then, the statistical features of each subband were calculated to produce a high-dimensional feature vector, which was reduced to a lower-dimensional vector by graph embedding algorithms. Finally, support vector machine (SVM) was used for defect classification. The multi-scale feature extraction method was implemented via curvelet transform and kernel locality preserving projections (KLPP). Experiment results show that the proposed method is effective for classifying the surface defects of hot-rolled steels and the total classification rate is up to 97.33%.
Urban air quality simulation with community multi-scale air quality (CMAQ) modeling system
Byun, D.; Young, J.; Gipson, G.; Schere, K.; Godowitch, J.
1998-11-01
In an effort to provide a state-of-the-science air quality modeling capability, US EPA has developed a new comprehensive and flexible Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. The authors demonstrate CMAQ simulations for a high ozone episode in the northeastern US during 12-15 July 1995 and discuss meteorological issues important for modeling of urban air quality.
Multi-scale Modeling and Analysis of Nano-RFID Systems on HPC Setup
NASA Astrophysics Data System (ADS)
Pathak, Rohit; Joshi, Satyadhar
In this paper we have worked out on some the complex modeling aspects such as Multi Scale modeling, MATLAB Sugar based modeling and have shown the complexities involved in the analysis of Nano RFID (Radio Frequency Identification) systems. We have shown the modeling and simulation and demonstrated some novel ideas and library development for Nano RFID. Multi scale modeling plays a very important role in nanotech enabled devices properties of which cannot be explained sometimes by abstraction level theories. Reliability and packaging still remains one the major hindrances in practical implementation of Nano RFID based devices. And to work on them modeling and simulation will play a very important role. CNTs is the future low power material that will replace CMOS and its integration with CMOS, MEMS circuitry will play an important role in realizing the true power in Nano RFID systems. RFID based on innovations in nanotechnology has been shown. MEMS modeling of Antenna, sensors and its integration in the circuitry has been shown. Thus incorporating this we can design a Nano-RFID which can be used in areas like human implantation and complex banking applications. We have proposed modeling of RFID using the concept of multi scale modeling to accurately predict its properties. Also we give the modeling of MEMS devices that are proposed recently that can see possible application in RFID. We have also covered the applications and the advantages of Nano RFID in various areas. RF MEMS has been matured and its devices are being successfully commercialized but taking it to limits of nano domains and integration with singly chip RFID needs a novel approach which is being proposed. We have modeled MEMS based transponder and shown the distribution for multi scale modeling for Nano RFID.
NASA Astrophysics Data System (ADS)
Howard, N. T.; Holland, C.; White, A. E.; Greenwald, M.; Candy, J.
2015-06-01
The first study using multi-scale (coupled ITG/TEM/ETG) gyrokinetic simulations at both reduced and realistic electron mass ratios, μ = (mD/me).5 = 20.0, 40.0 and 60.0, has been performed on a standard, Alcator C-Mod, L-mode discharge. Ion-scale (kθρs ∼ 1.0) and multi-scale (up to kθρe ∼ 0.8) gyrokinetic simulations are compared at different simulated mass ratios to investigate the fidelity of reduced electron mass ratio, multi-scale simulation through direct comparison with realistic mass ratio, multi-scale simulation. Detailed description of both the numerical setup and the turbulent scales required to obtain meaningful coupled ITG/TEM/ETG simulation is presented. Significant high-k driven (TEM/ETG) heat flux is found to exist at scales of approximately kθρe ∼ 0.1 at all mass ratios but can only be obtained by simulation capturing turbulence up to kθρe ∼ 1.0. At slightly reduced mass ratio, μ = 40.0, qualitative agreement with realistic mass simulation can be obtained in the studied discharge, consistent with intuition obtained from linear stability analysis. However, realistic electron mass is required for any robust quantitative comparison with experimental heat fluxes for the condition studied, as significant differences are observed at even slightly reduced electron mass ratio. The details of this numerical study are presented to provide a basis for future studies utilizing coupled ITG/TEM/ETG gyrokinetic simulation.
Low-carbon building assessment and multi-scale input-output analysis
NASA Astrophysics Data System (ADS)
Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.
2011-01-01
Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.
Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks
Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik
2009-01-01
Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569
Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation
NASA Astrophysics Data System (ADS)
Sakamoto, M.; Honda, Y.; Kondo, A.
2016-06-01
From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.
NASA Astrophysics Data System (ADS)
Nedic, Jovan; Vassilicos, J. Christos
2014-11-01
An experimental investigation was conducted into the aerodynamic performance and nature of the vortex shedding generated by truncated and non-flat serrated trailing edges of a NACA 0012 wing section. The truncated trailing edge generates a significant amount of vortex shedding, whilst increasing both the maximum lift and drag coefficients, resulting in an overall reduction in the maximum lift-to-drag ratio (L/D) compared to a plain NACA0012 wing section. By decreasing the chevron angle (ϕ) of the non-flat trailing edge serrations (i.e. by making them sharper), the energy of the vortex shedding significantly decreases and L/D increase compared to a plain NACA0012 wing section. Fractal/multi-scale patterns were also investigated with a view to further improve performance. It was found that the energy of the vortex shedding increases with increasing fractal iteration if the chevron is broad (ϕ ~65°), but decreases for sharper chevrons (ϕ =45°). It is believed that if ϕ is too big, the multi-scale trailing edges are too far away from each other to interact and break down the vortex shedding mechanism. Fractal/multi-scale trailing edges are also able to improve aerodynamic performance compared to the NACA 0012 wing section.
Flow around new wind fence with multi-scale fractal structure in an atmospheric boundary layer
NASA Astrophysics Data System (ADS)
McClure, Sarah; Lee, Sang-Joon; Zhang, Wei
2015-11-01
Understanding and controlling atmospheric boundary-layer flows with engineered structures, such as porous wind fences or windbreaks, has been of great interest to the fluid mechanics and wind engineering community. Previous studies found that the regular mono-scale grid fence of 50% porosity and a bottom gap of 10% of the fence height are considered to be optimal over a flat surface. Significant differences in turbulent flow structure have recently been noted behind multi-scale fractal wind fences, even with the same porosity. In this study, wind-tunnel tests on the turbulent flow and the turbulence kinetic energy transport of 1D and 2D multi-scale fractal fences under atmospheric boundary-layer were conducted. Velocity fields around the fractal fences were systematically measured using Particle Image Velocimetry to uncover effects of key parameters on turbulent flows around the fences at a Reynolds number of approximately 3.6x104 based on the free-stream speed and fence height. The turbulent flow structures induced by specific 1D/2D multi-scale fractal wind fences were compared to those of a conventional grid fence. The present results would contribute to the design of new-generation wind fences to reduce snow/sand deposition on critical infrastructure such as roads and bridges.
Multi-scale numerical simulations of thermal expansion properties of CNT-reinforced nanocomposites
2013-01-01
In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc. PMID:23294669
A multi-scale urban atmospheric dispersion model for emergency management
NASA Astrophysics Data System (ADS)
Miao, Yucong; Liu, Shuhua; Zheng, Hui; Zheng, Yijia; Chen, Bicheng; Wang, Shu
2014-11-01
To assist emergency management planning and prevention in case of hazardous chemical release into the atmosphere, especially in densely built-up regions with large populations, a multi-scale urban atmospheric dispersion model was established. Three numerical dispersion experiments, at horizontal resolutions of 10 m, 50 m and 3000 m, were performed to estimate the adverse effects of toxic chemical release in densely built-up areas. The multi-scale atmospheric dispersion model is composed of the Weather Forecasting and Research (WRF) model, the Open Source Field Operation and Manipulation software package, and a Lagrangian dispersion model. Quantification of the adverse health effects of these chemical release events are given by referring to the U.S. Environmental Protection Agency's Acute Exposure Guideline Levels. The wind fields of the urban-scale case, with 3 km horizontal resolution, were simulated by the Beijing Rapid Update Cycle system, which were utilized by the WRF model. The sub-domain-scale cases took advantage of the computational fluid dynamics method to explicitly consider the effects of buildings. It was found that the multi-scale atmospheric dispersion model is capable of simulating the flow pattern and concentration distribution on different scales, ranging from several meters to kilometers, and can therefore be used to improve the planning of prevention and response programs.
Control of Thermo-Acoustics Instabilities: The Multi-Scale Extended Kalman Approach
NASA Technical Reports Server (NTRS)
Le, Dzu K.; DeLaat, John C.; Chang, Clarence T.
2003-01-01
"Multi-Scale Extended Kalman" (MSEK) is a novel model-based control approach recently found to be effective for suppressing combustion instabilities in gas turbines. A control law formulated in this approach for fuel modulation demonstrated steady suppression of a high-frequency combustion instability (less than 500Hz) in a liquid-fuel combustion test rig under engine-realistic conditions. To make-up for severe transport-delays on control effect, the MSEK controller combines a wavelet -like Multi-Scale analysis and an Extended Kalman Observer to predict the thermo-acoustic states of combustion pressure perturbations. The commanded fuel modulation is composed of a damper action based on the predicted states, and a tones suppression action based on the Multi-Scale estimation of thermal excitations and other transient disturbances. The controller performs automatic adjustments of the gain and phase of these actions to minimize the Time-Scale Averaged Variances of the pressures inside the combustion zone and upstream of the injector. The successful demonstration of Active Combustion Control with this MSEK controller completed an important NASA milestone for the current research in advanced combustion technologies.
NASA Astrophysics Data System (ADS)
Piersanti, Mirko; Materassi, Massimo; Spogli, Luca; Cicone, Antonio; Alberti, Tommaso
2016-04-01
Highly irregular fluctuations of the power of trans-ionospheric GNSS signals, namely radio power scintillation, are, at least to a large extent, the effect of ionospheric plasma turbulence, a by-product of the non-linear and non-stationary evolution of the plasma fields defining the Earth's upper atmosphere. One could expect the ionospheric turbulence characteristics of inter-scale coupling, local randomness and high time variability to be inherited by the scintillation on radio signals crossing the medium. On this basis, the remote sensing of local features of the turbulent plasma could be expected as feasible by studying radio scintillation. The dependence of the statistical properties of the medium fluctuations on the space- and time-scale is the distinctive character of intermittent turbulent media. In this paper, a multi-scale statistical analysis of some samples of GPS radio scintillation is presented: the idea is that assessing how the statistics of signal fluctuations vary with time scale under different Helio-Geophysical conditions will be of help in understanding the corresponding multi-scale statistics of the turbulent medium causing that scintillation. In particular, two techniques are tested as multi-scale decomposition schemes of the signals: the discrete wavelet analysis and the Empirical Mode Decomposition. The discussion of the results of the one analysis versus the other will be presented, trying to highlight benefits and limits of each scheme, also under suitably different helio-geophysical conditions.
[Pattern recognition of surface electromyography signal based on multi-scale fuzzy entropy].
Zou, Xiaoyang; Lei, Min
2012-12-01
Action surface electromyography (SEMG) signals can be acquired from human skin surface. Its pattern recognition plays a very important role in practical applications such as human prosthesis and human-computer interface systems. For the purpose of increasing the recognition accuracy, we proposed a new recognition method combining fuzzy entropy (FuzzyEn) with multi-scale analysis. Considering the nonlinear and non-stationary characteristics of the SEMG, a multi-scale fuzzy entropy (MSFuzzyEn) feature was introduced and applied to the pattern recognition of six type action SEMG signals of the forearm. Firstly, multi-scale decomposition was applied to original signal using wavelet decomposition. Then MSFuzzyEn of the decomposed signals were calculated and inputted to support vector machine (SVM) for classification as feature vectors. The mean recognition accuracy reached 97%, which was 3% greater than that when FuzzyEn of original signal is applied to the classification of SEMG signals. The results have proved that the MSFuzzyEn is effective and precise in the classification of action SEMG signals. PMID:23469553
Multi-scale characterization of surface blistering morphology of helium irradiated W thin films
NASA Astrophysics Data System (ADS)
Yang, J. J.; Zhu, H. L.; Wan, Q.; Peng, M. J.; Ran, G.; Tang, J.; Yang, Y. Y.; Liao, J. L.; Liu, N.
2015-09-01
Surface blistering morphologies of W thin films irradiated by 30 keV He ion beam were studied quantitatively. It was found that the blistering morphology strongly depends on He fluence. For lower He fluence, the accumulation and growth of He bubbles induce the intrinsic surface blisters with mono-modal size distribution feature. When the He fluence is higher, the film surface morphology exhibits a multi-scale property, including two kinds of surface blisters with different characteristic sizes. In addition to the intrinsic He blisters, film/substrate interface delamination also induces large-sized surface blisters. A strategy based on wavelet transform approach was proposed to distinguish and extract the multi-scale surface blistering morphologies. Then the density, the lateral size and the height of these different blisters were estimated quantitatively, and the effect of He fluence on these geometrical parameters was investigated. Our method could provide a potential tool to describe the irradiation induced surface damage morphology with a multi-scale property.
NASA Astrophysics Data System (ADS)
Chen, Shuang-Quan; Zeng, Lian-Bo; Huang, Ping; Sun, Shao-Han; Zhang, Wan-Lu; Li, Xiang-Yang
2016-03-01
In this paper, we implement three scales of fracture integrated prediction study by classifying it to macro- (> 1/4 λ), meso- (> 1/100 λ and < 1/4 λ) and micro- (< 1/100 λ) scales. Based on the multi-scales rock physics modelling technique, the seismic azimuthal anisotropy characteristic is analyzed for distinguishing the fractures of meso-scale. Furthermore, by integrating geological core fracture description, image well-logging fracture interpretation, seismic attributes macro-scale fracture prediction and core slice micro-scale fracture characterization, an comprehensive multi-scale fracture prediction methodology and technique workflow are proposed by using geology, well-logging and seismic multi-attributes. Firstly, utilizing the geology core slice observation (Fractures description) and image well-logging data interpretation results, the main governing factors of fracture development are obtained, and then the control factors of the development of regional macro-scale fractures are carried out via modelling of the tectonic stress field. For the meso-scale fracture description, the poststack geometric attributes are used to describe the macro-scale fracture as well, the prestack attenuation seismic attribute is used to predict the meso-scale fracture. Finally, by combining lithological statistic inversion with superposed results of faults, the relationship of the meso-scale fractures, lithology and faults can be reasonably interpreted and the cause of meso-scale fractures can be verified. The micro-scale fracture description is mainly implemented by using the electron microscope scanning of cores. Therefore, the development of fractures in reservoirs is assessed by valuating three classes of fracture prediction results. An integrated fracture prediction application to a real field in Sichuan basin, where limestone reservoir fractures developed, is implemented. The application results in the study area indicates that the proposed multi-scales integrated
Voluntary EMG-to-force estimation with a multi-scale physiological muscle model
2013-01-01
Background EMG-to-force estimation based on muscle models, for voluntary contraction has many applications in human motion analysis. The so-called Hill model is recognized as a standard model for this practical use. However, it is a phenomenological model whereby muscle activation, force-length and force-velocity properties are considered independently. Perreault reported Hill modeling errors were large for different firing frequencies, level of activation and speed of contraction. It may be due to the lack of coupling between activation and force-velocity properties. In this paper, we discuss EMG-force estimation with a multi-scale physiology based model, which has a link to underlying crossbridge dynamics. Differently from the Hill model, the proposed method provides dual dynamics of recruitment and calcium activation. Methods The ankle torque was measured for the plantar flexion along with EMG measurements of the medial gastrocnemius (GAS) and soleus (SOL). In addition to Hill representation of the passive elements, three models of the contractile parts have been compared. Using common EMG signals during isometric contraction in four able-bodied subjects, torque was estimated by the linear Hill model, the nonlinear Hill model and the multi-scale physiological model that refers to Huxley theory. The comparison was made in normalized scale versus the case in maximum voluntary contraction. Results The estimation results obtained with the multi-scale model showed the best performances both in fast-short and slow-long term contraction in randomized tests for all the four subjects. The RMS errors were improved with the nonlinear Hill model compared to linear Hill, however it showed limitations to account for the different speed of contractions. Average error was 16.9% with the linear Hill model, 9.3% with the modified Hill model. In contrast, the error in the multi-scale model was 6.1% while maintaining a uniform estimation performance in both fast and slow
Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to
ERIC Educational Resources Information Center
Allday, Jonathan
2002-01-01
The events that led to the spectacular destruction of the Space Shuttle "Challenger" in 1986 are detailed here. They show how NASA should have heeded engineers' worries over materials problems resulting from a launch in cold weather. Suggestions are made of how pupils could also learn from this tragedy. (Contains 4 figures and 2 footnotes.)
NASA Astrophysics Data System (ADS)
Allday, Jonathan
2002-09-01
The events that led to the spectacular destruction of the Space Shuttle Challenger in 1986 are detailed here. They show how NASA should have heeded engineers' worries over materials problems resulting from a launch in cold weather. Suggestions are made of how pupils could also learn from this tragedy.
ERIC Educational Resources Information Center
Moore, Thomas R.
1975-01-01
Domestic and international challenges facing the National Society for the Prevention of Blindness are discussed; and U.S. and Russian programs in testing and correcting children's vision, developing eye safety programs in agriculture and industry, and disseminating information concerning the detection and treatment of cataracts are compared. (SB)
Utrilla, Jose; O'Brien, Edward J; Chen, Ke; McCloskey, Douglas; Cheung, Jacky; Wang, Harris; Armenta-Medina, Dagoberto; Feist, Adam M; Palsson, Bernhard O
2016-04-27
Pleiotropic regulatory mutations affect diverse cellular processes, posing a challenge to our understanding of genotype-phenotype relationships across multiple biological scales. Adaptive laboratory evolution (ALE) allows for such mutations to be found and characterized in the context of clear selection pressures. Here, several ALE-selected single-mutation variants in RNA polymerase (RNAP) of Escherichia coli are detailed using an integrated multi-scale experimental and computational approach. While these mutations increase cellular growth rates in steady environments, they reduce tolerance to stress and environmental fluctuations. We detail structural changes in the RNAP that rewire the transcriptional machinery to rebalance proteome and energy allocation toward growth and away from several hedging and stress functions. We find that while these mutations occur in diverse locations in the RNAP, they share a common adaptive mechanism. In turn, these findings highlight the resource allocation trade-offs organisms face and suggest how the structure of the regulatory network enhances evolvability. PMID:27135538
NASA Astrophysics Data System (ADS)
Yuan, Liang (Leon); Herman, Peter R.
2016-02-01
Three-dimensional (3D) periodic nanostructures underpin a promising research direction on the frontiers of nanoscience and technology to generate advanced materials for exploiting novel photonic crystal (PC) and nanofluidic functionalities. However, formation of uniform and defect-free 3D periodic structures over large areas that can further integrate into multifunctional devices has remained a major challenge. Here, we introduce a laser scanning holographic method for 3D exposure in thick photoresist that combines the unique advantages of large area 3D holographic interference lithography (HIL) with the flexible patterning of laser direct writing to form both micro- and nano-structures in a single exposure step. Phase mask interference patterns accumulated over multiple overlapping scans are shown to stitch seamlessly and form uniform 3D nanostructure with beam size scaled to small 200 μm diameter. In this way, laser scanning is presented as a facile means to embed 3D PC structure within microfluidic channels for integration into an optofluidic lab-on-chip, demonstrating a new laser HIL writing approach for creating multi-scale integrated microsystems.
Yuan, Liang (Leon); Herman, Peter R.
2016-01-01
Three-dimensional (3D) periodic nanostructures underpin a promising research direction on the frontiers of nanoscience and technology to generate advanced materials for exploiting novel photonic crystal (PC) and nanofluidic functionalities. However, formation of uniform and defect-free 3D periodic structures over large areas that can further integrate into multifunctional devices has remained a major challenge. Here, we introduce a laser scanning holographic method for 3D exposure in thick photoresist that combines the unique advantages of large area 3D holographic interference lithography (HIL) with the flexible patterning of laser direct writing to form both micro- and nano-structures in a single exposure step. Phase mask interference patterns accumulated over multiple overlapping scans are shown to stitch seamlessly and form uniform 3D nanostructure with beam size scaled to small 200 μm diameter. In this way, laser scanning is presented as a facile means to embed 3D PC structure within microfluidic channels for integration into an optofluidic lab-on-chip, demonstrating a new laser HIL writing approach for creating multi-scale integrated microsystems. PMID:26922872
Yuan, Liang Leon; Herman, Peter R
2016-01-01
Three-dimensional (3D) periodic nanostructures underpin a promising research direction on the frontiers of nanoscience and technology to generate advanced materials for exploiting novel photonic crystal (PC) and nanofluidic functionalities. However, formation of uniform and defect-free 3D periodic structures over large areas that can further integrate into multifunctional devices has remained a major challenge. Here, we introduce a laser scanning holographic method for 3D exposure in thick photoresist that combines the unique advantages of large area 3D holographic interference lithography (HIL) with the flexible patterning of laser direct writing to form both micro- and nano-structures in a single exposure step. Phase mask interference patterns accumulated over multiple overlapping scans are shown to stitch seamlessly and form uniform 3D nanostructure with beam size scaled to small 200 μm diameter. In this way, laser scanning is presented as a facile means to embed 3D PC structure within microfluidic channels for integration into an optofluidic lab-on-chip, demonstrating a new laser HIL writing approach for creating multi-scale integrated microsystems. PMID:26922872
NASA Technical Reports Server (NTRS)
Chai, Dean; Queen, Steve; Placanica, Sam
2015-01-01
NASA's Magnetospheric Multi-Scale (MMS) mission successfully launched on March 13, 2015 (UTC) consists of four identically instrumented spin-stabilized observatories that function as a constellation to study magnetic reconnection in space. The need to maintain sufficiently accurate spatial and temporal formation resolution of the observatories must be balanced against the logistical constraints of executing overly-frequent maneuvers on a small fleet of spacecraft. These two considerations make for an extremely challenging maneuver design problem. This paper focuses on the design elements of a 6-DOF spacecraft attitude control and maneuvering system capable of delivering the high-precision adjustments required by the constellation designers---specifically, the design, implementation, and on-orbit performance of the closed-loop formation-class maneuvers that include initialization, maintenance, and re-sizing. The maneuvering control system flown on MMS utilizes a micro-gravity resolution accelerometer sampled at a high rate in order to achieve closed-loop velocity tracking of an inertial target with arc-minute directional and millimeter-per-second magnitude accuracy. This paper summarizes the techniques used for correcting bias drift, sensor-head offsets, and centripetal aliasing in the acceleration measurements. It also discusses the on-board pre-maneuver calibration and compensation algorithms as well as the implementation of the post-maneuver attitude adjustments.
Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis
2015-01-01
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893
Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C; Shen, Dinggang
2015-02-01
improve the label fusion results. In particular, a coarse-to-fine iterative label fusion approach is used that gradually reduces the patch size. To evaluate the accuracy of our label fusion approach, the proposed method was used to segment the hippocampus in the ADNI dataset and 7.0 T MR images, sub-cortical regions in LONI LBPA40 dataset, mid-brain regions in SATA dataset from MICCAI 2013 segmentation challenge, and a set of key internal gray matter structures in IXI dataset. In all experiments, the segmentation results of the proposed hierarchical label fusion method with multi-scale feature representations and label-specific atlas patches are more accurate than several well-known state-of-the-art label fusion methods. PMID:25463474
NASA Astrophysics Data System (ADS)
Hill, T. C.; Stoy, P. C.; Baxter, R.; Clement, R.; Disney, M.; Evans, J.; Fletcher, B.; Gornall, J.; Harding, R.; Hartley, I. P.; Ineson, P.; Moncrieff, J.; Phoenix, G.; Sloan, V.; Poyatos, R.; Prieto-Blanco, A.; Subke, J.; Street, L.; Wade, T. J.; Wayolle, A.; Wookey, P.; Williams, M. D.
2009-12-01
The Arctic has already warmed significantly, and warming of 4-7 °C is expected over the next century. However, linkages between climate, the carbon cycle, the energy balance, and hydrology mean that the response of arctic ecosystems to these changes remains poorly understood. The release by warming of considerable but poorly quantified carbon stores from high latitude soils could accelerate the build-up of atmospheric CO2. The Arctic Biosphere Atmosphere Coupling at Multiple Scales (ABACUS) project, part of International Polar Year, was designed to improve predictions of the response of the Arctic terrestrial biosphere to climate change. The project operated at two sites (Abisko, Sweden and Kevo, Finland) over multiple years, utilising roving flux chambers (CO2/CH4), five flux towers (CO2/CH4/H2O) and a research aircraft equipped for fluxes (CO2/H2O) to directly measure multi-scale exchanges in-conjunction with other observations (both plot level and satellite). We show how these data can be combined using data assimilation approaches to address the question “what controls the temporal and spatial variability of carbon exchange by sub-Arctic ecosystems?” Eddy covariance measurements of mire methane exchanges agreed with chamber estimates, indicating that mires were strong summer sources, while birch woodland was a weak sink. However, remote sensing of mire extent was limited at resolutions > 30 m, and variations in sink/source activity suggested that upscaling CH4 exchanges (from chamber, to tower, to landscape) required higher resolution (ideally <10 m) landcover data in heterogeneous Arctic landscapes. Chamber and eddy covariance measurements of CO2 exchange recorded similar seasonal timing over a range of vegetation types. Birch woodlands had the greatest range of CO2 exchanges compared to tundra and mires. The challenge of measuring continuous fluxes across the full annual cycle, and inherent uncertainties in the methods, complicates the determination of
An integrated multi-scale risk analysis procedure for pluvial flooding
NASA Astrophysics Data System (ADS)
Tader, Andreas; Mergili, Martin; Jäger, Stefan; Glade, Thomas; Neuhold, Clemens; Stiefelmeyer, Heinz
2016-04-01
Mitigation of or adaptation to the negative impacts of natural processes on society requires a better understanding of the spatio-temporal distribution not only of the processes themselves, but also of the elements at risk. Information on their values, exposures and vulnerabilities towards the expected impact magnitudes/intensities of the relevant processes is needed. GIS-supported methods are particularly useful for integrated spatio-temporal analyses of natural processes and their potential consequences. Hereby, pluvial floods are of particular concern for many parts of Austria. The overall aim of the present study is to calculate the hazards emanating from pluvial floods, to determine the exposure of given elements at risk, to determine their vulnerabilities towards given pluvial flood hazards and to analyze potential consequences in terms of monetary losses. The whole approach builds on data available on a national scale. We introduce an integrated, multi-scale risk analysis procedure with regard to pluvial flooding. Focusing on the risk to buildings, we firstly exemplify this procedure with a well-documented event in the city of Graz (Austria), in order to highlight the associated potentials and limitations. Secondly, we attempt to predict the possible consequences of pluvial flooding triggered by rainfall events with recurrence intervals of 30, 100 and 300 years. (i) We compute spatially distributed inundation depths using the software FloodArea. Infiltration capacity and surface roughness are estimated from the land cover units given by the official cadastre. Various assumptions are tested with regard to the inflow to the urban sewer system. (ii) Based on the inundation depths and the official building register, we employ a set of rules and functions to deduce the exposure, vulnerability and risk for each building. A risk indicator for each building, expressed as the expected damage associated to a given event, is derived by combining the building value and
NASA Astrophysics Data System (ADS)
Harvey, J. W.; Packman, A. I.
2010-12-01
Surface water and groundwater flow interact with the channel geomorphology and sediments in ways that determine how material is transported, stored, and transformed in stream corridors. Solute and sediment transport affect important ecological processes such as carbon and nutrient dynamics and stream metabolism, processes that are fundamental to stream health and function. Many individual mechanisms of transport and storage of solute and sediment have been studied, including surface water exchange between the main channel and side pools, hyporheic flow through shallow and deep subsurface flow paths, and sediment transport during both baseflow and floods. A significant challenge arises from non-linear and scale-dependent transport resulting from natural, fractal fluvial topography and associated broad, multi-scale hydrologic interactions. Connections between processes and linkages across scales are not well understood, imposing significant limitations on system predictability. The whole-stream tracer experimental approach is popular because of the spatial averaging of heterogeneous processes; however the tracer results, implemented alone and analyzed using typical models, cannot usually predict transport beyond the very specific conditions of the experiment. Furthermore, the results of whole stream tracer experiments tend to be biased due to unavoidable limitations associated with sampling frequency, measurement sensitivity, and experiment duration. We recommend that whole-stream tracer additions be augmented with hydraulic and topographic measurements and also with additional tracer measurements made directly in storage zones. We present examples of measurements that encompass interactions across spatial and temporal scales and models that are transferable to a wide range of flow and geomorphic conditions. These results show how the competitive effects between the different forces driving hyporheic flow, operating at different spatial scales, creates a situation
Using CellML with OpenCMISS to Simulate Multi-Scale Physiology
Nickerson, David P.; Ladd, David; Hussan, Jagir R.; Safaei, Soroush; Suresh, Vinod; Hunter, Peter J.; Bradley, Christopher P.
2014-01-01
OpenCMISS is an open-source modeling environment aimed, in particular, at the solution of bioengineering problems. OpenCMISS consists of two main parts: a computational library (OpenCMISS-Iron) and a field manipulation and visualization library (OpenCMISS-Zinc). OpenCMISS is designed for the solution of coupled multi-scale, multi-physics problems in a general-purpose parallel environment. CellML is an XML format designed to encode biophysically based systems of ordinary differential equations and both linear and non-linear algebraic equations. A primary design goal of CellML is to allow mathematical models to be encoded in a modular and reusable format to aid reproducibility and interoperability of modeling studies. In OpenCMISS, we make use of CellML models to enable users to configure various aspects of their multi-scale physiological models. This avoids the need for users to be familiar with the OpenCMISS internal code in order to perform customized computational experiments. Examples of this are: cellular electrophysiology models embedded in tissue electrical propagation models; material constitutive relationships for mechanical growth and deformation simulations; time-varying boundary conditions for various problem domains; and fluid constitutive relationships and lumped-parameter models. In this paper, we provide implementation details describing how CellML models are integrated into multi-scale physiological models in OpenCMISS. The external interface OpenCMISS presents to users is also described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modeling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use of other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (graphical processing unit and field programmable gate array) generated from CellML models is also
Multi-scale gyrokinetic simulation of Alcator C-Mod tokamak discharges
NASA Astrophysics Data System (ADS)
Howard, N. T.; White, A. E.; Greenwald, M.; Holland, C.; Candy, J.
2014-03-01
Alcator C-Mod tokamak discharges have been studied with nonlinear gyrokinetic simulation simultaneously spanning both ion and electron spatiotemporal scales. These multi-scale simulations utilized the gyrokinetic model implemented by GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and the approximation of reduced electron mass (μ = (mD/me).5 = 20.0) to qualitatively study a pair of Alcator C-Mod discharges: a low-power discharge, previously demonstrated (using realistic mass, ion-scale simulation) to display an under-prediction of the electron heat flux and a high-power discharge displaying agreement with both ion and electron heat flux channels [N. T. Howard et al., Nucl. Fusion 53, 123011 (2013)]. These multi-scale simulations demonstrate the importance of electron-scale turbulence in the core of conventional tokamak discharges and suggest it is a viable candidate for explaining the observed under-prediction of electron heat flux. In this paper, we investigate the coupling of turbulence at the ion (kθρs˜O(1.0)) and electron (kθρe˜O(1.0)) scales for experimental plasma conditions both exhibiting strong (high-power) and marginally stable (low-power) low-k (kθρs < 1.0) turbulence. It is found that reduced mass simulation of the plasma exhibiting marginally stable low-k turbulence fails to provide even qualitative insight into the turbulence present in the realistic plasma conditions. In contrast, multi-scale simulation of the plasma condition exhibiting strong turbulence provides valuable insight into the coupling of the ion and electron scales.
Multi-scale gyrokinetic simulation of Alcator C-Mod tokamak discharges
Howard, N. T. White, A. E.; Greenwald, M.; Holland, C.; Candy, J.
2014-03-15
Alcator C-Mod tokamak discharges have been studied with nonlinear gyrokinetic simulation simultaneously spanning both ion and electron spatiotemporal scales. These multi-scale simulations utilized the gyrokinetic model implemented by GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and the approximation of reduced electron mass (μ = (m{sub D}/m{sub e}){sup .5} = 20.0) to qualitatively study a pair of Alcator C-Mod discharges: a low-power discharge, previously demonstrated (using realistic mass, ion-scale simulation) to display an under-prediction of the electron heat flux and a high-power discharge displaying agreement with both ion and electron heat flux channels [N. T. Howard et al., Nucl. Fusion 53, 123011 (2013)]. These multi-scale simulations demonstrate the importance of electron-scale turbulence in the core of conventional tokamak discharges and suggest it is a viable candidate for explaining the observed under-prediction of electron heat flux. In this paper, we investigate the coupling of turbulence at the ion (k{sub θ}ρ{sub s}∼O(1.0)) and electron (k{sub θ}ρ{sub e}∼O(1.0)) scales for experimental plasma conditions both exhibiting strong (high-power) and marginally stable (low-power) low-k (k{sub θ}ρ{sub s} < 1.0) turbulence. It is found that reduced mass simulation of the plasma exhibiting marginally stable low-k turbulence fails to provide even qualitative insight into the turbulence present in the realistic plasma conditions. In contrast, multi-scale simulation of the plasma condition exhibiting strong turbulence provides valuable insight into the coupling of the ion and electron scales.