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 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.
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.
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.
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.
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.
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.
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.
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
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.
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 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
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.
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
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
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.
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
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
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
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.
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
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.
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,
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.
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.
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
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 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 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 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
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
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.
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.
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.
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 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.
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.
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.
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.
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 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.
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
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 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
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 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.
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.
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
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
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.
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
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.
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.
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.
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
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).
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.
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.
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.
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.
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.
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.
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.
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.
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%.
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
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.
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.
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 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)
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 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.
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
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
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
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.
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...
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.
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.
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.
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
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.
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.
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
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.
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.
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%.
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.
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
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
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.
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.
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.
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.
[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)
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.
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
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
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)
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.
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.
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
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.
Turbulent Flow Structure Inside a Canopy with Complex Multi-Scale Elements
NASA Astrophysics Data System (ADS)
Bai, Kunlun; Katz, Joseph; Meneveau, Charles
2015-06-01
Particle image velocimetry laboratory measurements are carried out to study mean flow distributions and turbulent statistics inside a canopy with complex geometry and multiple scales consisting of fractal, tree-like objects. Matching the optical refractive indices of the tree elements with those of the working fluid provides unobstructed optical paths for both illuminations and image acquisition. As a result, the flow fields between tree branches can be resolved in great detail, without optical interference. Statistical distributions of mean velocity, turbulence stresses, and components of dispersive fluxes are documented and discussed. The results show that the trees leave their signatures in the flow by imprinting wake structures with shapes similar to the trees. The velocities in both wake and non-wake regions significantly deviate from the spatially-averaged values. These local deviations result in strong dispersive fluxes, which are important to account for in canopy-flow modelling. In fact, we find that the streamwise normal dispersive flux inside the canopy has a larger magnitude (by up to four times) than the corresponding Reynolds normal stress. Turbulent transport in horizontal planes is studied in the framework of the eddy viscosity model. Scatter plots comparing the Reynolds shear stress and mean velocity gradient are indicative of a linear trend, from which one can calculate the eddy viscosity and mixing length. Similar to earlier results from the wake of a single tree, here we find that inside the canopy the mean mixing length decreases with increasing elevation. This trend cannot be scaled based on a single length scale, but can be described well by a model, which considers the coexistence of multi-scale branches. This agreement indicates that the multi-scale information and the clustering properties of the fractal objects should be taken into consideration in flows inside multi-scale canopies.
NASA Astrophysics Data System (ADS)
Fouofula-Georgiou, E.; Ebtehaj, A. M.
2012-04-01
Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction Efi Foufoula-Georgiou and Ardeshir Mohammad Ebtehaj Department of Civil Engineering and National Center for Earth-surface Dynamics University of Minnesota, Minneapolis, MN 55414 Many geophysical processes exhibit variability over a wide range of scales. Yet, in numerical modeling or remote sensing observations not all of this variability is explicitly resolved due to limitations in computational resources or sensor configurations. As a result, sub-grid scale parameterizations and downscaling/upscaling representations are essential. Such representations take advantage of scale invariance which has been theoretically or empirically documented in a wide range of geophysical processes, including precipitation, soil moisture, and topography. Here we present a new direction in the field of multi-scale analysis and reconstruction. It capitalizes on the fact that most geophysical signals are naturally redundant, due to spatial dependence and coherence over a range of scales, and thus when projected onto an appropriate space (e.g, Fourier or wavelet) only a few representation coefficients are non-zero -- this property is called sparsity. The sparsity can serve as a priori knowledge to properly regularize the otherwise ill-posed inverse problem of creating information at scales smaller than resolved, which is at the heart of sub-grid scale and downscaling parameterizations. The same property of sparsity is also shown to play a revolutionary role in revisiting the problem of optimal estimation of non-Gaussian processes. Theoretical concepts are borrowed from the new field of compressive sampling and super-resolution and the merits of the methodology are demonstrated using examples from precipitation downscaling, multi-scale data fusion and data assimilation.
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 path planning for reduced environmental impact of aviation
NASA Astrophysics Data System (ADS)
Campbell, Scot Edward
A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.
An Improved Multi-Scale Modeling Framework for WRF over Complex Terrain
NASA Astrophysics Data System (ADS)
Wiersema, D. J.; Lundquist, K. A.; Chow, F. K.
2014-12-01
Atmospheric modelers continue to push towards higher resolution simulations of the planetary boundary layer. As resolution is refined, the resolved terrain slopes increase. Atmospheric models using terrain-following coordinates, such as the Weather Research and Forecasting (WRF) model, suffer from numerical errors since steep terrain slopes lead to grid skewness, resulting in model failure. One solution to this problem is the use of an immersed boundary method, which uses a non-conforming grid, for simulations over complex terrain. Our implementation of an immersed boundary method in WRF, known as WRF-IBM, was developed for use at the micro-scale and has been shown to accurately simulate flow around complex topography, such as urban environments or mountainous terrain. The research presented here describes our newly developed framework to enable concurrently run multi-scale simulations using the WRF model at the meso-scale and the WRF-IBM model at the micro-scale. WRF and WRF-IBM use different vertical coordinates therefore it is not possible to use the existing nesting framework to pass lateral boundary conditions from a WRF parent domain to a WRF-IBM nested domain. Nesting between WRF and WRF-IBM requires "vertical grid nesting", meaning the ability to pass information between domains with different vertical levels. Our newly implemented method for vertical grid nesting, available in the public release of WRFv3.6.1, allows nested domains to utilize different vertical levels. Using our vertical grid nesting code, we are currently developing the ability to nest a domain using IBM within a domain using terrain-following coordinates. Here we present results from idealized cases displaying the functionality of the multi-scale nesting framework and the advancement towards multi-scale meteorological simulations over complex terrain.
Fast randomized Hough transformation track initiation algorithm based on multi-scale clustering
NASA Astrophysics Data System (ADS)
Wan, Minjie; Gu, Guohua; Chen, Qian; Qian, Weixian; Wang, Pengcheng
2015-10-01
A fast randomized Hough transformation track initiation algorithm based on multi-scale clustering is proposed to overcome existing problems in traditional infrared search and track system(IRST) which cannot provide movement information of the initial target and select the threshold value of correlation automatically by a two-dimensional track association algorithm based on bearing-only information . Movements of all the targets are presumed to be uniform rectilinear motion throughout this new algorithm. Concepts of space random sampling, parameter space dynamic linking table and convergent mapping of image to parameter space are developed on the basis of fast randomized Hough transformation. Considering the phenomenon of peak value clustering due to shortcomings of peak detection itself which is built on threshold value method, accuracy can only be ensured on condition that parameter space has an obvious peak value. A multi-scale idea is added to the above-mentioned algorithm. Firstly, a primary association is conducted to select several alternative tracks by a low-threshold .Then, alternative tracks are processed by multi-scale clustering methods , through which accurate numbers and parameters of tracks are figured out automatically by means of transforming scale parameters. The first three frames are processed by this algorithm in order to get the first three targets of the track , and then two slightly different gate radius are worked out , mean value of which is used to be the global threshold value of correlation. Moreover, a new model for curvilinear equation correction is applied to the above-mentioned track initiation algorithm for purpose of solving the problem of shape distortion when a space three-dimensional curve is mapped to a two-dimensional bearing-only space. Using sideways-flying, launch and landing as examples to build models and simulate, the application of the proposed approach in simulation proves its effectiveness , accuracy , and adaptivity
Linking Multi-Scale Observations to Determine Hyporheic Nitrate Removal in a Stream
NASA Astrophysics Data System (ADS)
Zarnetske, J. P.; Haggerty, R.; Wondzell, S. M.
2014-12-01
Surplus nitrate (NO3-) in streams is a persistent problem for many aquatic ecosystems and denitrification represents the primary removal process for NO3- in streams. Hyporheic zones can have high denitrification potentials, but the role of the hyporheic denitrification on reach and network scale NO3- removal is unknown because it is difficult to estimate using current methods. Here, we develop a new approach that links existing independent and complementary multi-scale measurements of denitrification and total NO3- uptake. This approach is then used to quantify the role of hyporheic NO3- removal in a 303m reach of a third-order agricultural stream in western Oregon, USA. The reach scale NO3- dynamics were characterized with steady-state 15N-NO3- tracer addition experiments and solute transport modeling, while the hyporheic conditions were measured via in situ biogeochemical and groundwater modeling. Our linking of multi-scale approaches revealed that the hyporheic NO3- removal (rate coefficient λHZ = 0.007 h-1) accounted for 17% of the observed total reach NO3- uptake, and 32% of the reach denitrification estimated from the 15N experiments. The primary limitations of hyporheic denitrification at the reach scale were labile dissolved organic carbon availability (low hyporheic SUVA254) and the restricted size of the hyporheic zone due to anthropogenic channelization (sediment thickness ≤ 1.5 m). Linking multi-scale methods enabled us to make one of the first ever reach-scale estimates of hyporheic influence on stream NO3- and denitrification dynamics. Further, this study also demonstrates that the traditional reach scale tracer experimental designs and subsequent transport modeling cannot be used alone to directly investigate the role of the hyporheic zone on reach scale water and solute dynamics.
Multi-scale groundwater modelling for the assessment of sustainable borehole yields under drought
NASA Astrophysics Data System (ADS)
Upton, Kirsty; Butler, Adrian; Jackson, Chris; Jones, Mike
2014-05-01
A new multi-scale groundwater modelling methodology is presented for simulating abstraction boreholes in regional groundwater models. This provides a robust tool for assessing the sustainable yield of supply boreholes, thus improving our understanding of groundwater availability during droughts. The yield of an abstraction well is dependent on a number of factors. These include antecedent recharge and groundwater conditions; the properties of a regional aquifer system; requirements on a groundwater system to maintain river flows or sites of ecological significance; the properties of an individual abstraction borehole; small-scale aquifer heterogeneity around a borehole; the rate of abstraction; and the way in which neighboring abstraction boreholes interact. These factors can all be represented in the multi-scale model, which couples a small-scale radial flow model of an abstraction borehole with a regional-scale groundwater model. The regional groundwater model, ZOOMQ3D, represents the large-scale groundwater system, including lateral and vertical aquifer heterogeneity, rivers, and spatially varying recharge. The 3D radial flow model, SPIDERR, represents linear and non-linear flow to a borehole, local vertical heterogeneity, well storage and pump location. The multi-scale model is applied to a supply borehole (operated by Thames Water) located in the Chalk aquifer within the catchment of the River Thames in southern England. Groundwater abstraction from the Chalk aquifer accounts for 40-70% of the total public water supply in this region. Drought is a recurring feature of the UK climate, and in particular the south and east of England. Since 1850, nine major groundwater droughts have occurred, all of which lasted longer than one year. The most recent occurred in 2010-2012, during which seven water supply companies introduced water usage restrictions, affecting over 20 million people. The radial flow model is initially calibrated against pumping test data from the
Multi-scale modeling for dynamics of structure-soil-structure interactions
NASA Astrophysics Data System (ADS)
Boutin, Claude; Soubestre, Jean; Schwan, Logan; Dietz, Matt
2014-10-01
This paper presents two cases of multi-scale modeling in the context of dynamic structure soil-structure interaction. The first case concerns the behaviour of reinforced soils. It is shown that such system may involve both shear and bending effect at the leading order, which corresponds to a second gradient material. The second case addresses the seismic response of soils in presence of a densely urbanized city. It appears that the effect of resonance of the whole buildings in interaction actually modify the seismic response. In both cases the theoretical approach is completed by a validation through analogous samples tested on a shaking table.
Ho, Hsin Shen; Bigerelle, Maxence; Vincent, Renald; Deltomb, Raphael
2016-05-01
In the present study, the influence of sandblasting condition (working pressure) on surface texture is modeled, relying on a multi-scale approach and statistical analysis. To improve the correlation modeling between the process condition and surface texture, special effort is made to identification of an optimal parameter set, including 3D roughness parameters, cut-off lengths, filter types and model types. A power law relationship is identified between the pressure and Sdq computed with a cut-off length of 120 µm using a low-pass filter. Experimental and theoretical arguments are provided for justification. SCANNING 38:191-201, 2016. © 2015 Wiley Periodicals, Inc. PMID:26249107
Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach.
Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah
2009-01-01
Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated. PMID:22389617
Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach
Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah
2009-01-01
Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated. PMID:22389617
A unified double-loop multi-scale control strategy for NMP integrating-unstable systems
NASA Astrophysics Data System (ADS)
Seer, Qiu Han; Nandong, Jobrun
2016-03-01
This paper presents a new control strategy which unifies the direct and indirect multi-scale control schemes via a double-loop control structure. This unified control strategy is proposed for controlling a class of highly nonminimum-phase processes having both integrating and unstable modes. This type of systems is often encountered in fed-batch fermentation processes which are very difficult to stabilize via most of the existing well-established control strategies. A systematic design procedure is provided where its applicability is demonstrated via a numerical example.
Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework
Ackerman, Thomas P.
2015-03-01
The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained
Sengupta, Jayasree; Ghosh, Debabrata
2014-01-01
Implantation is a complex process which results in fixation of zona pellucida free blastocyst to the maternal uterine endometrium. In the human, it involves progesterone mediated preparation of endometrium, age- and stage-matched development of pre-implantation embryo, and interaction between embryo and endometrium. In the present essay, we present the case to explain why there is a necessity of undertaking multi-level, multi-scale integrative approach to deconstruct the succession process of endometrial development to the climax of implantation. PMID:24342377
NASA Astrophysics Data System (ADS)
Liao, Miao; Zhao, Yu-qian; Wang, Xiao-hong; Dai, Pei-shan
2014-06-01
Retinal vessels play an important role in the diagnostic procedure of retinopathy. A new retinal vessel enhancement method is proposed in this paper. Firstly, the optimal bright and dim image features of an original retinal image are extracted by a multi-scale top-hat transformation. Then, the retinal image is enhanced preliminarily by adding the optimal bright image features and removing the optimal dim image features. Finally, the preliminarily enhanced image is further processed by linear stretching with histogram Gaussian curve fitting. The experiments results on the DRIVE and STARE databases show that the proposed method improves the contrast and enhances the details of the retinal vessels effectively.
Replication of Non-Trivial Directional Motion in Multi-Scales Observed by the Runs Test
NASA Astrophysics Data System (ADS)
Yura, Yoshihiro; Ohnishi, Takaaki; Yamada, Kenta; Takayasu, Hideki; Takayasu, Misako
Non-trivial autocorrelation in up-down statistics in financial market price fluctuation is revealed by a multi-scale runs test(Wald-Wolfowitz test). We apply two models, a stochastic price model and dealer model to understand this property. In both approaches we successfully reproduce the non-stationary directional price motions consistent with the runs test by tuning parameters in the models. We find that two types of dealers exist in the markets, a short-time-scale trend-follower and an extended-time-scale contrarian who are active in different time periods.
Continuum Level Formulation and Implementation of a Multi-scale Model for Vanadium
Lawrence Livermore National Laboratory
2009-08-17
A multi-scale approach is used to construct a continuum strength model for vanadium. The model is formulated assuming plastic deformation by dislocation motion and strain hardening due to dislocation interactions. Dislocation density is adopted as the state variable in the model. Information from molecular statics, molecular dynamics and dislocation dynamics simulations is combined to create kinetic relations for dislocation motion, strain hardening relations and evolution equations for the dislocation density. Implicit time integration of the constitutive equations is described in the context of implementation in a finite element code. Results are provided illustrating the strain, strain rate, temperature and pressure dependence of the constitutive model.
A multi-scale registration of urban aerial image with airborne lidar data
NASA Astrophysics Data System (ADS)
Huang, Shuo; Chen, Siying; Zhang, Yinchao; Guo, Pan; Chen, He
2015-11-01
This paper presented a multi-scale progressive registration method of airborne LiDAR data with aerial image. The cores of the proposed method lie in the coarse registration with road networks and the fine registration method using regularized building corners. During the two-stage registration, the exterior orientation parameters (EOP) are continually refined. By validation of the actual flight data of Dunhuang, the experimental result shows that the proposed method can obtain accurate results with low-precision initial EOP, also improve the automatic degree of registration.
NASA Astrophysics Data System (ADS)
Wildhaber, M. L.; Wikle, C. K.; Anderson, C. J.; Franz, K. J.; Moran, E. H.
2010-12-01
Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by course-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and hierarchical Bayesian modeling frameworks to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global change.
Fix, N. J.
2008-01-31
The purpose of the project is to conduct research at an Integrated Field-Scale Research Challenge Site in the Hanford Site 300 Area, CERCLA OU 300-FF-5 (Figure 1), to investigate multi-scale mass transfer processes associated with a subsurface uranium plume impacting both the vadose zone and groundwater. The project will investigate a series of science questions posed for research related to the effect of spatial heterogeneities, the importance of scale, coupled interactions between biogeochemical, hydrologic, and mass transfer processes, and measurements/approaches needed to characterize a mass-transfer dominated system. The research will be conducted by evaluating three (3) different hypotheses focused on multi-scale mass transfer processes in the vadose zone and groundwater, their influence on field-scale U(VI) biogeochemistry and transport, and their implications to natural systems and remediation. The project also includes goals to 1) provide relevant materials and field experimental opportunities for other ERSD researchers and 2) generate a lasting, accessible, and high-quality field experimental database that can be used by the scientific community for testing and validation of new conceptual and numerical models of subsurface reactive transport.
Kuramae, Hiroyuki; Okada, Kenji; Uetsuji, Yasutomo; Nakamachi, Eiji; Tam, Nguyen Ngoc; Nakamura, Yasunori
2005-08-05
Since the multi-scale finite element analysis (FEA) requires large computation time, development of the parallel computing technique for the multi-scale analysis is inevitable. A parallel elastic/crystalline viscoplastic FEA code based on a crystallographic homogenization method has been developed using PC cluster. The homogenization scheme is introduced to compute macro-continuum plastic deformations and material properties by considering a polycrystal texture. Since the dynamic explicit method is applied to this method, the analysis using micro crystal structures computes the homogenized stresses in parallel based on domain partitioning of macro-continuum without solving simultaneous linear equations. The micro-structure is defined by the Scanning Electron Microscope (SEM) and the Electron Back Scan Diffraction (EBSD) measurement based crystal orientations. In order to improve parallel performance of elastoplasticity analysis, which dynamically and partially increases computational costs during the analysis, a dynamic workload balancing technique is introduced to the parallel analysis. The technique, which is an automatic task distribution method, is realized by adaptation of subdomain size for macro-continuum to maintain the computational load balancing among cluster nodes. The analysis code is applied to estimate the polycrystalline sheet metal formability.
Application of multi-scale (cross-) sample entropy for structural health monitoring
NASA Astrophysics Data System (ADS)
Lin, Tzu-Kang; Liang, Jui-Chang
2015-08-01
This study proposes an information-theoretic structural health monitoring (SHM) system based on multi-scale entropy (MSE) and multi-scale cross-sample entropy (MSCE). By measuring the ambient vibration signal from a structure, the damage condition can be rapidly evaluated via MSE analysis. The damage location can then be detected by analyzing the signals of different floors under the same damage condition via MSCE analysis. Moreover, a damage index is proposed to efficiently quantify the SHM process. Unlike some existing SHM methods, no experimental database or numerical model is required. Instead, a reference measurement of the current stage can initiate and launch the SHM system. A numerical simulation of a four-story steel structure is used to verify that the damage location and condition can be detected by the proposed SHM algorithm, and the location can be efficiently quantified by the damage index. A seven-story scaled-down benchmark structure is then employed for experimental verification. Based on the results, the damage condition can be correctly assessed, and average accuracy rates of 63.4 and 86.6% for the damage location can be achieved using the MSCE and damage index methods, respectively. As only the ambient vibration signal is required with a set of initial reference measurements, the proposed SHM system can be implemented practically with low cost.
Retrieving the intracellular topology from multi-scale protein mobility mapping in living cells
Baum, Michael; Erdel, Fabian; Wachsmuth, Malte; Rippe, Karsten
2014-01-01
In living cells, most proteins diffuse over distances of micrometres within seconds. Protein translocation is constrained due to the cellular organization into subcompartments that impose diffusion barriers and guide enzymatic activities to their targets. Here, we introduce an approach to retrieve structural features from the scale-dependent mobility of green fluorescent protein monomer and multimers in human cells. We measure protein transport simultaneously between hundreds of positions by multi-scale fluorescence cross-correlation spectroscopy using a line-illuminating confocal microscope. From these data we derive a quantitative model of the intracellular architecture that resembles a random obstacle network for diffusing proteins. This topology partitions the cellular content and increases the dwell time of proteins in their local environment. The accessibility of obstacle surfaces depends on protein size. Our method links multi-scale mobility measurements with a quantitative description of intracellular structure that can be applied to evaluate how drug-induced perturbations affect protein transport and interactions. PMID:25058002
Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI.
Zhuang, Xiahai; Shen, Juan
2016-07-01
A whole heart segmentation (WHS) method is presented for cardiac MRI. This segmentation method employs multi-modality atlases from MRI and CT and adopts a new label fusion algorithm which is based on the proposed multi-scale patch (MSP) strategy and a new global atlas ranking scheme. MSP, developed from the scale-space theory, uses the information of multi-scale images and provides different levels of the structural information of images for multi-level local atlas ranking. Both the local and global atlas ranking steps use the information theoretic measures to compute the similarity between the target image and the atlases from multiple modalities. The proposed segmentation scheme was evaluated on a set of data involving 20 cardiac MRI and 20 CT images. Our proposed algorithm demonstrated a promising performance, yielding a mean WHS Dice score of 0.899 ± 0.0340, Jaccard index of 0.818 ± 0.0549, and surface distance error of 1.09 ± 1.11 mm for the 20 MRI data. The average runtime for the proposed label fusion was 12.58 min. PMID:26999615
The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence
NASA Astrophysics Data System (ADS)
Staebler, G. M.; Candy, J.; Howard, N. T.; Holland, C.
2016-06-01
The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.
Multi-scale analysis of Proterozoic shear zones: An integrated structural and geophysical study
NASA Astrophysics Data System (ADS)
Stewart, John R.; Betts, Peter G.; Collins, Alan S.; Schaefer, Bruce F.
2009-11-01
Structural mapping of poorly exposed shear zone outcrops is integrated with the analysis of aeromagnetic and Bouguer gravity data to develop a multi-scale kinematic and relative overprinting chronology for the Palaeoproterozoic Tallacootra Shear Zone, Australia. D 2 mylonitic fabrics at outcrop record Kimban-aged (ca. 1730-1690 Ma) N-S shortening and correlate with SZ 1 movements. Overprinting D 3 sinistral shear zones record the partitioning of near-ideal simple shear and initiated Riedel to regional-scale SZ 2 strike-slip on the Tallacootra Shear Zone (SZ 2). Previously undocumented NE-SW extension led to the emplacement of aplite dykes into the shear zone and can be correlated to the (ca. 1595-1575 Ma) Hiltaba magmatic event. D 4 dextral transpression during the (ca. 1470-1450 Ma) Coorabie Orogeny reactivated the Tallacootra Shear Zone (SZ 2-R4) exhuming lower crust of the northwestern Fowler Domain within a positive flower structure. This latest shear zone movement is related to a system of west-dipping shear zones that penetrate the crust and sole into a lithospheric detachment indicating wholesale crustal shortening. These methods demonstrate the value of integrating multi-scale structural analyses for the study of shear zones with limited exposure.
Space-scale unfolding mechanism in canonical multi-scale flows
NASA Astrophysics Data System (ADS)
Baj, Pawel; Bruce, Paul J. K.; Buxton, Oliver R. H.
2015-11-01
Some recent studies on fractal generated turbulence revealed a highly increased transverse turbulent scalar flux downstream of fractal grids compared to regular grids. The complexity of these flows makes it impossible to track the origins of this phenomenon, often referred to as the space-scale unfolding mechanism (SSU). Thus research on flows past canonical examples of single and multi-scale obstacles, which are arrays of bars of the same and different thicknesses, was undertaken in order to investigate the SSU's roots. The velocity field and the scalar concentration field were measured simultaneously downstream of the obstacles by means of particle image velocimetry and laser induced fluorescence techniques. It is observed that the concentration field behind the multi-scale obstacle undergoes intense quasi-periodic transverse scalar bursts, which are believed to be the manifestation of the SSU, whereas such events are either weak or absent in the single scale configuration. Investigation of the velocity field reveals a phase locking between wakes of different scale objects in terms of the phase-conditioned transverse integral length scale. Both phenomena are observed to be triggered at the downstream position corresponding to the wakes' intersection point. The authors acknowledge support form the EU through the FP7 Marie Curie MULTISOLVE project (grant agreement No. 317269).
The Numerical Performance of Wavelets for PDEs: The Multi-Scale Finite Element
Christon, M.A.; Roach, D.W.
1998-12-23
The research summarized in this paper is part of a multiyear effort 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 in the usual L 2 sense is less desirable than orthogonality in the energy norm. This conclusion has led to the development of a multi-scale lineax finite element based on a hierarchical change-of-basis. This work considers the numerical and computational performance of the hierarchical Schauder basis in a Galerkin context. A unique row-column lumping procedure is developed with multi-scale solution strategies for 1-D and 2-D elliptic partial differential equations.
Noori, Hamid Reza
2012-09-01
The phenomena related to brain function occur as the interplay of various modules at different spatial and temporal scales. Particularly, the integration of the dynamical behavior of cells within the complex brain topology reveals a heterogeneous multi-scale problem, which has, to date, mainly been addressed by methods of statistical physics such as mean-field approximations. In contrast, the present study introduces an abstract mathematical model of a deterministic nature that provides a robust integral transformation of the microscopic activities into macroscopic spatiotemporal patterns. The existence of the transformation operator is guaranteed by the convergence of a repetitive patching of the network domain with its fundamental domains that express the local topologies of the tissue. Depending on the choice of the local connectivity function, this framework represents a computationally efficient generalization of the classical Kirchhoff's, Hebbian, and Hopfield's approaches. The capabilities of this multi-scale method have been evaluated within the structure of the dorsal striatum of rats, a brain region with major involvement in motor and cognitive information processing. Numerical simulations suggest the formation of characteristic spatiotemporal patterns due to the activation of cholinergic interneurons. PMID:24615222
Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion
NASA Astrophysics Data System (ADS)
Feng, Wenqing; Sui, Haigang; Tu, Jihui
2016-06-01
In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.
Multi-scale image fusion for x-ray grating-based mammography
NASA Astrophysics Data System (ADS)
Jiang, Xiaolei; Zhang, Li; Wang, Zhentian; Stampanoni, Marco
2012-10-01
X-ray phase contrast imaging (PCI) can provide high sensitivity of weakly absorbing low-Z objects in medical and biological fields, especially in mammography. Grating-based differential phase contrast (DPC) method is the most potential PCI method for clinic applications because it can works well with conventional X-ray tube and it can retrieve attenuation, DPC and dark-field information of the samples in a single scanning. Three kinds of information have different details and contrast which represent different physical characteristics of X-rays with matters. Hence, image fusion can show the most desirable characteristics of each image. In this paper, we proposed a multi-scale image fusion for X-ray grating-based DPC mammography. Firstly, non-local means method is adopted for denoising due to the strong noise, especially for DPC and dark-field images. Then, Laplacian pyramid is used for multi-scale image fusion. The principal component analysis (PCA) method is used on the high frequency part and the spatial frequency method is used on the low frequency part. Finally, the fused image is obtained by inverse Laplacian pyramid transform. Our algorithm is validated by experiments. The experiments were performed on mammoDPC instrumentation at the Paul Scherrer Institut in Villigen, Switzerland. The results show that our algorithm can significantly show the advantages of three kinds of information in the fused image, which is very helpful for the breast cancer diagnosis.
Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method
NASA Technical Reports Server (NTRS)
Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.
2014-01-01
A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.
Multi-Scale Fusion for Improved Localization of Malicious Tampering in Digital Images.
Korus, Paweł; Huang, Jiwu
2016-03-01
A sliding window-based analysis is a prevailing mechanism for tampering localization in passive image authentication. It uses existing forensic detectors, originally designed for a full-frame analysis, to obtain the detection scores for individual image regions. One of the main problems with a window-based analysis is its impractically low localization resolution stemming from the need to use relatively large analysis windows. While decreasing the window size can improve the localization resolution, the classification results tend to become unreliable due to insufficient statistics about the relevant forensic features. In this paper, we investigate a multi-scale analysis approach that fuses multiple candidate tampering maps, resulting from the analysis with different windows, to obtain a single, more reliable tampering map with better localization resolution. We propose three different techniques for multi-scale fusion, and verify their feasibility against various reference strategies. We consider a popular tampering scenario with mode-based first digit features to distinguish between singly and doubly compressed regions. Our results clearly indicate that the proposed fusion strategies can successfully combine the benefits of small-scale and large-scale analyses and improve the tampering localization performance. PMID:26800540
A multi-scale Q1/P0 approach to langrangian shock hydrodynamics.
Shashkov, Mikhail (Los Alamos National Laboratory, Los Alamos, NM.); Love, Edward; Scovazzi, Guglielmo
2006-03-01
A new multi-scale, stabilized method for Q1/P0 finite element computations of Lagrangian shock hydrodynamics is presented. Instabilities (of hourglass type) are controlled by a stabilizing operator derived using the variational multi-scale analysis paradigm. The resulting stabilizing term takes the form of a pressure correction. With respect to currently implemented hourglass control approaches, the novelty of the method resides in its residual-based character. The stabilizing residual has a definite physical meaning, since it embeds a discrete form of the Clausius-Duhem inequality. Effectively, the proposed stabilization samples and acts to counter the production of entropy due to numerical instabilities. The proposed technique is applicable to materials with no shear strength, for which there exists a caloric equation of state. The stabilization operator is incorporated into a mid-point, predictor/multi-corrector time integration algorithm, which conserves mass, momentum and total energy. Encouraging numerical results in the context of compressible gas dynamics confirm the potential of the method.
Zhang, Yanhang; Barocas, Victor H; Berceli, Scott A; Clancy, Colleen E; Eckmann, David M; Garbey, Marc; Kassab, Ghassan S; Lochner, Donna R; McCulloch, Andrew D; Tran-Son-Tay, Roger; Trayanova, Natalia A
2016-09-01
Cardiovascular diseases (CVDs) are the leading cause of death in the western world. With the current development of clinical diagnostics to more accurately measure the extent and specifics of CVDs, a laudable goal is a better understanding of the structure-function relation in the cardiovascular system. Much of this fundamental understanding comes from the development and study of models that integrate biology, medicine, imaging, and biomechanics. Information from these models provides guidance for developing diagnostics, and implementation of these diagnostics to the clinical setting, in turn, provides data for refining the models. In this review, we introduce multi-scale and multi-physical models for understanding disease development, progression, and designing clinical interventions. We begin with multi-scale models of cardiac electrophysiology and mechanics for diagnosis, clinical decision support, personalized and precision medicine in cardiology with examples in arrhythmia and heart failure. We then introduce computational models of vasculature mechanics and associated mechanical forces for understanding vascular disease progression, designing clinical interventions, and elucidating mechanisms that underlie diverse vascular conditions. We conclude with a discussion of barriers that must be overcome to provide enhanced insights, predictions, and decisions in pre-clinical and clinical applications. PMID:27138523
Predicting the roughness length of turbulent flows over landscapes with multi-scale microtopography
NASA Astrophysics Data System (ADS)
Pelletier, Jon D.; Field, Jason P.
2016-05-01
The fully rough form of the law of the wall is commonly used to quantify velocity profiles and associated bed shear stresses in fluvial, aeolian, and coastal environments. A key parameter in this law is the roughness length, z0. Here we propose a predictive formula for z0 that uses the amplitude and slope of each wavelength of microtopography within a discrete-Fourier-transform-based approach. Computational fluid dynamics (CFD) modeling is used to quantify the effective z0 value of sinusoidal microtopography as a function of the amplitude and slope. The effective z0 value of landscapes with multi-scale roughness is then given by the sum of contributions from each Fourier mode of the microtopography. Predictions of the equation are tested against z0 values measured in ˜ 105 wind-velocity profiles from southwestern US playa surfaces. Our equation is capable of predicting z0 values to 50 % accuracy, on average, across a 4 order of magnitude range. We also use our results to provide an alternative formula that, while somewhat less accurate than the one obtained from a full multi-scale analysis, has an advantage of being simpler and easier to apply.
NASA Astrophysics Data System (ADS)
Li, Chuan; Liang, Ming; Zhang, Yi; Hou, Shumin
2012-08-01
Fault features of rolling element bearings can be reflected by geometrical structures of the bearing vibration signals. These symptoms, however, often spread over various morphological scales without a known pattern. For this reason, we propose a multi-scale autocorrelation via morphological wavelet slices (MAMWS) approach to detect bearing fault signatures. The vibration measurement of a bearing is decomposed using morphological stationary wavelet with different resolutions of structuring elements. The extracted temporal components are then transformed to form a frequency-domain view of morphological slices by the Fourier transform. Although this three-dimensional representation is more intuitive in terms of fault diagnosis, the existence of the noise may reduce its readability. Hence the autocorrelation function is exploited to produce a multi-scale autocorrelation spectrogram from which the maximal autocorrelation values of all frequencies are aggregated into an ichnographical spectral representation. Accordingly the fault signature is highlighted for easy diagnosis of bearing faults. The effectiveness of the proposed approach has been demonstrated by both the simulation and experimental signal analyses.
Diagnosing Disaster Resilience of Communities as Multi-scale Complex Socio-ecological Systems
NASA Astrophysics Data System (ADS)
Liu, Wei; Mochizuki, Junko; Keating, Adriana; Mechler, Reinhard; Williges, Keith; Hochrainer, Stefan
2014-05-01
Global environmental change, growing anthropogenic influence, and increasing globalisation of society have made it clear that disaster vulnerability and resilience of communities cannot be understood without knowledge on the broader social-ecological system in which they are embedded. We propose a framework for diagnosing community resilience to disasters, as a form of disturbance to social-ecological systems, with feedbacks from the local to the global scale. Inspired by iterative multi-scale analysis employed by Resilience Alliance, the related socio-ecological systems framework of Ostrom, and the sustainable livelihood framework, we developed a multi-tier framework for thinking of communities as multi-scale social-ecological systems and analyzing communities' disaster resilience and also general resilience. We highlight the cross-scale influences and feedbacks on communities that exist from lower (e.g., household) to higher (e.g., regional, national) scales. The conceptual framework is then applied to a real-world resilience assessment situation, to illustrate how key components of socio-ecological systems, including natural hazards, natural and man-made environment, and community capacities can be delineated and analyzed.
A multi-scale model for correlation in B cell VDJ usage of zebrafish
Pan, Keyao; Deem, Michael W
2015-01-01
The zebrafish (Danio rerio) is one of the model animals for study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a “microscopic” random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principles calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment. PMID:21832808
On the formalization of multi-scale and multi-science processes for integrative biology
Díaz-Zuccarini, Vanessa; Pichardo-Almarza, César
2011-01-01
The aim of this work is to introduce the general concept of ‘Bond Graph’ (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the ‘elements’ of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The ‘effort’ and ‘flow’ variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view. PMID:22670211
Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression
Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong
2016-01-01
In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms. PMID:27525734
Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.
Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong
2016-01-01
In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms. PMID:27525734
Shamekhi, Sina; Miran Baygi, Mohammad Hossein; Azarian, Bahareh; Gooya, Ali
2015-11-01
Two dimensional gel electrophoresis (2DGE) is a useful method for studying proteins in a wide variety of applications including identifying post-translation modification (PTM), biomarker discovery, and protein purification. Computerized segmentation and detection of the proteins are the two main processes that are carried out on the scanned image of the gel. Due to the complexities of 2DGE images and the presence of artifacts, the segmentation and detection of protein spots in these images are non-trivial, and involve supervised and time consuming processes. This paper introduces a new spot filter for enhancing, and separating the closely overlapping spots of protein in 2DGE images based on the multi-scale eigenvalue analysis of the image Hessian. Using a Gaussian spot model, we have derived closed form equations to compute the eigen components of the image Hessian of two overlapping spots in a multi-scale fashion. Based on this analysis, we have proposed a novel filter that suppresses the overlapping area and results in a better spot separation. The performance of the proposed filter has been evaluated on the synthetic and real 2DGE images. The comparison with three conventional techniques and a commercial software package reveals the superiority and effectiveness of the proposed filter. PMID:26409228
Follicular lymphoma grading using cell-graphs and multi-scale feature analysis
NASA Astrophysics Data System (ADS)
Oztan, Basak; Kong, Hui; Gürcan, Metin N.; Yener, Bülent
2012-03-01
We present a method for the computer-aided histopathological grading of follicular lymphoma (FL) images based on a multi-scale feature analysis. We analyze FL images using cell-graphs to characterize the structural organization of the cells in tissues. Cell-graphs represent histopathological images with undirected and unweighted graphs wherein the cytological components constitute the graph nodes and the approximate adjacencies of the components are represented with edges. Using the features extracted from nuclei- and cytoplasm-based cell-graphs, a classifier defines the grading of the follicular lymphoma images. The performance of this system is comparable to that of our recently developed system that characterizes higher-level semantic description of tissues using model-based intermediate representation (MBIR) and color-textural analysis. When tested with three different classifiers, the combination of cell-graph based features with the MBIR and color-textural features followed by a multi-scale feature selection is shown to achieve considerably higher classification accuracies than any set of these feature sets can achieve separately.
NASA Astrophysics Data System (ADS)
Meneveau, Charles; Graham, Jason; Bai, Kunlun; Katz, Joseph
2010-05-01
In many regions the atmospheric surface layer is affected substantially by vegetation canopies. Most previous work has focused on effects of vegetated terrain characterized by a single length scale, e.g. a single obstruction of a particular size, or canopies consisting of plants, often modeled using a prescribed leaf-area density distribution with a characteristic dominant scale. It is well known, however, that typical flow obstructions such as canopies are characterized by a wide range of length scales, branches, sub-branches, etc.. Yet, it is not known how to parameterize the effects of such multi-scale objects on the lower atmospheric dynamics. This work aims to study boundary layer flow over fractal, tree-like shapes. Fractals provide convenient idealizations of the inherently multi-scale character of vegetation geometries, within certain ranges of scales. We report on Large Eddy Simulations whose results are compared with a ongoing experiments that also aim at understanding drag forces acting on fractal trees. The experiments are performed in a water tunnel facility that uses optically index-matched fluid. This enables to access the full 3-D flow volume with Particle-Image-Velocimetry. The measurements complement computer simulations using LES, and the aim is to use the results to develop downscaling parameterizations for unresolved branch drag forces with a technique called Renormalized Numerical Simulation (RNS). This research is supported by the National Science Foundation (IGERT Project # 0801471 and ATM grant # 0621396).
Strong, Multi-Scale Heterogeneity in Earth’s Lowermost Mantle
NASA Astrophysics Data System (ADS)
Tkalčić, Hrvoje; Young, Mallory; Muir, Jack B.; Davies, D. Rhodri; Mattesini, Maurizio
2015-12-01
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.
Multi-scale numerical simulations on piezoresistivity of CNT/polymer nanocomposites
2012-01-01
In this work, we propose a comprehensive multi-scale three-dimensional (3D) resistor network numerical model to predict the piezoresistivity behavior of a nanocomposite material composed of an insulating polymer matrix and conductive carbon nanotubes (CNTs). This material is expected to be used as highly sensitive resistance-type strain sensors due to its high piezoresistivity defined as the resistance change ratio divided by the mechanical strain. In this multi-scale 3D numerical model, three main working mechanisms, which are well known to induce the piezoresistivity of strain sensors fabricated from nanocomposites, are for the first time considered systematically. They are (a) the change of the internal conductive network formed by the CNTs, (b) the tunneling effect among neighboring CNTs, and (c) the CNTs’ piezoresistivity. Comparisons between the present numerical results and our previous experimental ones were also performed to validate the present numerical model. The influence of the CNTs’ piezoresistivity on the total piezoresistivity of nanocomposite strain sensors is explored in detail and further compared with that of the other two mechanisms. It is found that the first two working mechanisms (i.e., the change of the internal conductive network and the tunneling effect) play a major role on the piezoresistivity of the nanocomposite strain sensors, whereas the contribution from the CNTs’ piezoresistivity is quite small. The present numerical results can provide valuable information for designing highly sensitive resistance-type strain sensors made from various nanocomposites composed of an insulating polymer matrix and conductive nanofillers. PMID:22804919
Multi-scale numerical simulations on piezoresistivity of CNT/polymer nanocomposites.
Hu, Bin; Hu, Ning; Li, Yuan; Akagi, Kentaro; Yuan, Weifeng; Watanabe, Tomonori; Cai, Yong
2012-01-01
In this work, we propose a comprehensive multi-scale three-dimensional (3D) resistor network numerical model to predict the piezoresistivity behavior of a nanocomposite material composed of an insulating polymer matrix and conductive carbon nanotubes (CNTs). This material is expected to be used as highly sensitive resistance-type strain sensors due to its high piezoresistivity defined as the resistance change ratio divided by the mechanical strain. In this multi-scale 3D numerical model, three main working mechanisms, which are well known to induce the piezoresistivity of strain sensors fabricated from nanocomposites, are for the first time considered systematically. They are (a) the change of the internal conductive network formed by the CNTs, (b) the tunneling effect among neighboring CNTs, and (c) the CNTs' piezoresistivity. Comparisons between the present numerical results and our previous experimental ones were also performed to validate the present numerical model. The influence of the CNTs' piezoresistivity on the total piezoresistivity of nanocomposite strain sensors is explored in detail and further compared with that of the other two mechanisms. It is found that the first two working mechanisms (i.e., the change of the internal conductive network and the tunneling effect) play a major role on the piezoresistivity of the nanocomposite strain sensors, whereas the contribution from the CNTs' piezoresistivity is quite small. The present numerical results can provide valuable information for designing highly sensitive resistance-type strain sensors made from various nanocomposites composed of an insulating polymer matrix and conductive nanofillers. PMID:22804919
Intrinsic multi-scale analysis: a multi-variate empirical mode decomposition framework
Looney, David; Hemakom, Apit; Mandic, Danilo P.
2015-01-01
A novel multi-scale approach for quantifying both inter- and intra-component dependence of a complex system is introduced. This is achieved using empirical mode decomposition (EMD), which, unlike conventional scale-estimation methods, obtains a set of scales reflecting the underlying oscillations at the intrinsic scale level. This enables the data-driven operation of several standard data-association measures (intrinsic correlation, intrinsic sample entropy (SE), intrinsic phase synchrony) and, at the same time, preserves the physical meaning of the analysis. The utility of multi-variate extensions of EMD is highlighted, both in terms of robust scale alignment between system components, a pre-requisite for inter-component measures, and in the estimation of feature relevance. We also illuminate that the properties of EMD scales can be used to decouple amplitude and phase information, a necessary step in order to accurately quantify signal dynamics through correlation and SE analysis which are otherwise not possible. Finally, the proposed multi-scale framework is applied to detect directionality, and higher order features such as coupling and regularity, in both synthetic and biological systems. PMID:25568621
Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur
NASA Astrophysics Data System (ADS)
Ascenzi, Maria-Grazia; Kawas, Neal P.; Lutz, Andre; Kardas, Dieter; Nackenhorst, Udo; Keyak, Joyce H.
2013-07-01
We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual's (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structure varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method's development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications - varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient's femur, that strains computed at the multi-scale model's micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.
Infrared/laser multi-sensor fusion and tracking based on the multi-scale model
NASA Astrophysics Data System (ADS)
Wang, Bingjian; Hao, Jingya; Yi, Xiang; Wu, Feihong; Li, Min; Qin, Hanlin; Huang, Hanqiao
2016-03-01
The state estimation problem of targets detected by infrared/laser composite detection system with different sampling rates was studied in this paper. An effective state estimation algorithm based on data fusion is presented. Because sampling rate of infrared detection system is much higher than that of the laser detection system, the theory of multi-scale analysis is used to establish multi-scale model in this algorithm. At the fine scale, angle information provided by infrared detection system is used to estimate the target state through the unscented Kalman filter. It makes full use of the high frequency characteristic of infrared detection system to improve target state estimation accuracy. At the coarse scale, due to the sampling ratio of infrared and laser detection systems is an integer multiple, the angle information can be fused directly with the distance information of laser detection system to determine the target location. The fused information is served as observation, while the converted measurement Kalman filter (CMKF) is used to estimate the target state, which greatly reduces the complexity of filtering process and gets the optimal fusion estimation. The simulation results of tracking a target in 3-D space by infrared and laser detection systems demonstrate that the proposed algorithm in this paper is efficient and can obtain better performance than traditional algorithm.
Jiang, Ching-Fen; Lin, Yu-Ching; Yu, Nan-Ying
2013-01-01
To solve the limitations in using the conventional parametric measures to define myofascial pain, a 3-D multi-scale wavelet energy variation graph is proposed as a way to inspect the pattern of surface electromyography (SEMG) variation between the dominant and nondominant sides at different frequency scales during a muscle contraction cycle and the associated changes with the upper-back myofascial pain. The model was developed based on the property of the wavelet energy of the SEMG signal revealing the degree of correspondence between the shape of the motor unit action potential and the wavelet waveform at a certain scale in terms of the frequency band. The characteristic pattern of the graph for each group (30 normal and 26 patient subjects) was first derived and revealed the dominant-hand effect and the changes with myofascial pain. Through comparison of individual graphs across subjects, we found that the graph pattern reveals a sensitivity of 53.85% at a specificity of 83.33% in the identification of myofascial pain. The changes in these patterns provide insight into the transformation between different fiber recruitment, which cannot be explored using conventional SEMG features. Therefore, this multi-scale analysis model could provide a reliable SEMG features to identify myofascial pain. PMID:23070369
Improved convergence of gradient-based reconstruction using multi-scale models
Cunningham, G.S.; Hanson, K.M.; Koyfman, I.
1996-05-01
Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component.
A multi-scale model for correlation in B cell VDJ usage of zebrafish
NASA Astrophysics Data System (ADS)
Pan, Keyao; Deem, Michael W.
2011-10-01
The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.
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
Multi-scale theoretical investigation of hydrogen storage in covalent organic frameworks
NASA Astrophysics Data System (ADS)
Tylianakis, Emmanuel; Klontzas, Emmanouel; Froudakis, George E.
2011-03-01
The quest for efficient hydrogen storage materials has been the limiting step towards the commercialization of hydrogen as an energy carrier and has attracted a lot of attention from the scientific community. Sophisticated multi-scale theoretical techniques have been considered as a valuable tool for the prediction of materials storage properties. Such techniques have also been used for the investigation of hydrogen storage in a novel category of porous materials known as Covalent Organic Frameworks (COFs). These framework materials are consisted of light elements and are characterized by exceptional physicochemical properties such as large surface areas and pore volumes. Combinations of ab initio, Molecular Dynamics (MD) and Grand Canonical Monte-Carlo (GCMC) calculations have been performed to investigate the hydrogen adsorption in these ultra-light materials. The purpose of the present review is to summarize the theoretical hydrogen storage studies that have been published after the discovery of COFs. Experimental and theoretical studies have proven that COFs have comparable or better hydrogen storage abilities than other competitive materials such as MOF. The key factors that can lead to the improvement of the hydrogen storage properties of COFs are highlighted, accompanied with some recently presented theoretical multi-scale studies concerning these factors.
Toor, F.; Page, M. R.; Branz, H. M.; Yuan, H. C.
2011-07-01
In this work we present 17.1%-efficient p-type single crystal Si solar cells with a multi-scale-textured surface and no dielectric antireflection coating. Multi-scale texturing is achieved by a gold-nanoparticle-assisted nanoporous etch after conventional micron scale KOH-based pyramid texturing (pyramid black etching). By incorporating geometric enhancement of antireflection, this multi-scale texturing reduces the nanoporosity depth required to make silicon 'black' compared to nanoporous planar surfaces. As a result, it improves short-wavelength spectral response (blue response), previously one of the major limiting factors in 'black-Si' solar cells. With multi-scale texturing, the spectrum-weighted average reflectance from 350- to 1000-nm wavelength is below 2% with a 100-nm deep nanoporous layer. In comparison, roughly 250-nm deep nanopores are needed to achieve similar reflectance on planar surface. Here, we characterize surface morphology, reflectivity and solar cell performance of the multi-scale textured solar cells.
Chen, Li; He, Ya-Ling; Kang, Qinjun; Tao, Wen-Quan
2013-12-15
A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of which obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.
Multi-modality registration via multi-scale textural and spectral embedding representations
NASA Astrophysics Data System (ADS)
Li, Lin; Rusu, Mirabela; Viswanath, Satish; Penzias, Gregory; Pahwa, Shivani; Gollamudi, Jay; Madabhushi, Anant
2016-03-01
Intensity-based similarity measures assume that the original signal intensity of different modality images can provide statistically consistent information regarding the two modalities to be co-registered. In multi-modal registration problems, however, intensity-based similarity measures are often inadequate to identify an optimal transformation. Texture features can improve the performance of the multi-modal co-registration by providing more similar appearance representations of the two images to be co-registered, compared to the signal intensity representations. Furthermore, texture features extracted at different length scales (neighborhood sizes) can reveal similar underlying structural attributes between the images to be co-registered similarities that may not be discernible on the signal intensity representation alone. However one limitation of using texture features is that a number of them may be redundant and dependent and hence there is a need to identify non-redundant representations. Additionally it is not clear which features at which specific scales reveal similar attributes across the images to be co-registered. To address this problem, we introduced a novel approach for multimodal co-registration that employs new multi-scale image representations. Our approach comprises 4 distinct steps: (1) texure feature extraction at each length scale within both the target and template images, (2) independent component analysis (ICA) at each texture feature length scale, and (3) spectrally embedding (SE) the ICA components (ICs) obtained for the texture features at each length scale, and finally (4) identifying and combining the optimal length scales at which to perform the co-registration. To combine and co-register across different length scales, -mutual information (-MI) was applied in the high dimensional space of spectral embedding vectors to facilitate co-registration. To validate our multi-scale co-registration approach, we aligned 45 pairs of prostate
Zhuang, Kai H; Herrgård, Markus J
2015-09-01
In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli and Saccharomyces cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions). We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales. PMID:26116515
NASA Astrophysics Data System (ADS)
Li, Ke; Chen, Jianping; Sofia, Giulia; Tarolli, Paolo
2014-05-01
Moon surface features have great significance in understanding and reconstructing the lunar geological evolution. Linear structures like rilles and ridges are closely related to the internal forced tectonic movement. The craters widely distributed on the moon are also the key research targets for external forced geological evolution. The extremely rare availability of samples and the difficulty for field works make remote sensing the most important approach for planetary studies. New and advanced lunar probes launched by China, U.S., Japan and India provide nowadays a lot of high-quality data, especially in the form of high-resolution Digital Terrain Models (DTMs), bringing new opportunities and challenges for feature extraction on the moon. The aim of this study is to recognize and extract lunar features using geomorphometric analysis based on multi-scale parameters and multi-resolution DTMs. The considered digital datasets include CE1-LAM (Chang'E One, Laser AltiMeter) data with resolution of 500m/pix, LRO-WAC (Lunar Reconnaissance Orbiter, Wide Angle Camera) data with resolution of 100m/pix, LRO-LOLA (Lunar Reconnaissance Orbiter, Lunar Orbiter Laser Altimeter) data with resolution of 60m/pix, and LRO-NAC (Lunar Reconnaissance Orbiter, Narrow Angle Camera) data with resolution of 2-5m/pix. We considered surface derivatives to recognize the linear structures including Rilles and Ridges. Different window scales and thresholds for are considered for feature extraction. We also calculated the roughness index to identify the erosion/deposits area within craters. The results underline the suitability of the adopted methods for feature recognition on the moon surface. The roughness index is found to be a useful tool to distinguish new craters, with higher roughness, from the old craters, which present a smooth and less rough surface.
A multi-scale hybrid neural network retrieval model for dust storm detection, a study in Asia
NASA Astrophysics Data System (ADS)
Wong, Man Sing; Xiao, Fei; Nichol, Janet; Fung, Jimmy; Kim, Jhoon; Campbell, James; Chan, P. W.
2015-05-01
Dust storms are known to have adverse effects on human health and significant impact on weather, air quality, hydrological cycle, and ecosystem. Atmospheric dust loading is also one of the large uncertainties in global climate modeling, due to its significant impact on the radiation budget and atmospheric stability. Observations of dust storms in humid tropical south China (e.g. Hong Kong), are challenging due to high industrial pollution from the nearby Pearl River Delta region. This study develops a method for dust storm detection by combining ground station observations (PM10 concentration, AERONET data), geostationary satellite images (MTSAT), and numerical weather and climatic forecasting products (WRF/Chem). The method is based on a hybrid neural network (NN) retrieval model for two scales: (i) a NN model for near real-time detection of dust storms at broader regional scale; (ii) a NN model for detailed dust storm mapping for Hong Kong and Taiwan. A feed-forward multilayer perceptron (MLP) NN, trained using back propagation (BP) algorithm, was developed and validated by the k-fold cross validation approach. The accuracy of the near real-time detection MLP-BP network is 96.6%, and the accuracies for the detailed MLP-BP neural network for Hong Kong and Taiwan is 74.8%. This newly automated multi-scale hybrid method can be used to give advance near real-time mapping of dust storms for environmental authorities and the public. It is also beneficial for identifying spatial locations of adverse air quality conditions, and estimates of low visibility associated with dust events for port and airport authorities.
From seconds to months: an overview of multi-scale dynamics of mobile telephone calls
NASA Astrophysics Data System (ADS)
Saramäki, Jari; Moro, Esteban
2015-06-01
Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.
NASA Astrophysics Data System (ADS)
Chen, Q.; Rice, A. F.
2005-03-01
Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).
Roger, Stéphane; Sang, Yan Yip Cheung; Bee, Agnès; Perzynski, Régine; Di Meglio, Jean Marc; Ponton, Alain
2015-08-01
We present a structural and a multi-scale rheophysical investigation of magneto-sensitive materials based on biopolymers, namely aqueous solutions of sodium alginate incorporating magnetic maghemite nanoparticles, functionalized with adsorbed negative citrate ions. The large alginate ionic strength impacts the structure and the rheology of these nanocomposites in zero magnetic field. In given physico-chemical conditions, the system is fluid and homogeneous on macroscopic scales while it is diphasic on microscopic ones, containing micro-droplets coming from the demixion of the system. These micro-droplets are liquid and deformable under magnetic field. Their under-field elongation and their zero-field relaxation are directly observed by optical microscopy to determine their interfacial tension, their magnetic susceptibility and their internal viscosity. A structural analysis of the solutions of alginate chains and of the phase-separated mixtures of alginate and nanoparticles by Small Angle Scattering completes the local description of the system. PMID:26264396
Multi-scale mechanical characterization of scaffolds for heart valve tissue engineering.
Argento, G; Simonet, M; Oomens, C W J; Baaijens, F P T
2012-11-15
Electrospinning is a promising technology to produce scaffolds for cardiovascular tissue engineering. Each electrospun scaffold is characterized by a complex micro-scale structure that is responsible for its macroscopic mechanical behavior. In this study, we focus on the development and the validation of a computational micro-scale model that takes into account the structural features of the electrospun material, and is suitable for studying the multi-scale scaffold mechanics. We show that the computational tool developed is able to describe and predict the mechanical behavior of electrospun scaffolds characterized by different microstructures. Moreover, we explore the global mechanical properties of valve-shaped scaffolds with different microstructural features, and compare the deformation of these scaffolds when submitted to diastolic pressures with a tissue engineered and a native valve. It is shown that a pronounced degree of anisotropy is necessary to reproduce the deformation patterns observed in the native heart valve. PMID:22999107
An improved fusion algorithm for infrared and visible images based on multi-scale transform
NASA Astrophysics Data System (ADS)
Li, He; Liu, Lei; Huang, Wei; Yue, Chao
2016-01-01
In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.
Results from Navigator GPS Flight Testing for the Magnetospheric MultiScale Mission
NASA Technical Reports Server (NTRS)
Lulich, Tyler D.; Bamford, William A.; Wintermitz, Luke M. B.; Price, Samuel R.
2012-01-01
The recent delivery of the first Goddard Space Flight Center (GSFC) Navigator Global Positioning System (GPS) receivers to the Magnetospheric MultiScale (MMS) mission spacecraft is a high water mark crowning a decade of research and development in high-altitude space-based GPS. Preceding MMS delivery, the engineering team had developed receivers to support multiple missions and mission studies, such as Low Earth Orbit (LEO) navigation for the Global Precipitation Mission (GPM), above the constellation navigation for the Geostationary Operational Environmental Satellite (GOES) proof-of-concept studies, cis-Lunar navigation with rapid re-acquisition during re-entry for the Orion Project and an orbital demonstration on the Space Shuttle during the Hubble Servicing Mission (HSM-4).
Multi-Scale Analysis of the European Airspace Using Network Community Detection
Gurtner, Gérald; Vitali, Stefania; Cipolla, Marco; Lillo, Fabrizio; Mantegna, Rosario Nunzio; Miccichè, Salvatore; Pozzi, Simone
2014-01-01
We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace. PMID:24809991
Multi-scale modeling of the phase diagram of Human Immunoglobulin
NASA Astrophysics Data System (ADS)
Tuchman, Mark; Buldyrev, Sergey; Wang, Ying; Lomakin, Aleksey; Benedek, George B.
2014-03-01
Human Immunoglobulin antibodies IGg is a Y-shape trimer consisting of three folded protein globules, connected by two polypeptide hinges in random conformations linked by disulfide bonds. The solubility and crystallization phase diagrams of immunoglobulin are crucial in understanding various pathological conditions. It is experimentally known that the critical volume fraction of immunoglobulin is three times smaller than for typical globular proteins. In order to explain this phenomenon, we perform a multi-scale molecular dynamic (MD) simulations. First we produce all atom simulations of the hinges and compute the distribution of their end-to-end distances. Using these results we construct a simple effective bond potential and study a phase diagram of a system of three sticky hard-spheres linked by these bonds by discrete MD simulations. The results are in good agreement with the experiment.
Multi-scale modeling of the iron bcc arrow hcp martensitic phase transformation
NASA Astrophysics Data System (ADS)
Caspersen, Kyle; Carter, Emily; Lew, Adrian; Ortiz, Michael
2004-03-01
Pressures exceeding 10 GPa induce a martensitic phase transformation in iron, where ferro-magnetic bcc transforms into non-magnetic hcp. The transition pressure is not known precisely, but is thought to depend strongly on shear. To investigate the properties of this transformation and the role of shear, we have developed a multi-scale iron model. This model contains a free energy derived from an ab-initio based non-linear elastic expansion, a kinematically compatible spinodal decomposition of phases, ab-initio based interfacial energies, and a dependence on the bcc rightarrow hcp transformation path(s). The model shows spinodal decomposition behavior (with a slight expected deviation) as well as predicting 10 GPa to be the transformation pressure. Additionally, the model predicted that the inclusion of shear facilitates the transformation, causing transformation pressure to decrease.
Multi-scale crystal growth computations via an approximate block Newton method
NASA Astrophysics Data System (ADS)
Yeckel, Andrew; Lun, Lisa; Derby, Jeffrey J.
2010-04-01
Multi-scale and multi-physics simulations, such as the computational modeling of crystal growth processes, will benefit from the modular coupling of existing codes rather than the development of monolithic, single-application software. An effective coupling approach, the approximate block Newton approach (ABN), is developed and applied to the steady-state computation of crystal growth in an electrodynamic gradient freeze system. Specifically, the code CrysMAS is employed for furnace-scale heat transfer computations and is coupled with the code Cats2D to calculate melt fluid dynamics and phase-change phenomena. The ABN coupling strategy proves to be vastly more reliable and cost efficient than simpler coupling methods for this problem and is a promising approach for future crystal growth models.
Numerical methods for simulating blood flow at macro, micro, and multi scales.
Imai, Yohsuke; Omori, Toshihiro; Shimogonya, Yuji; Yamaguchi, Takami; Ishikawa, Takuji
2016-07-26
In the past decade, numerical methods for the computational biomechanics of blood flow have progressed to overcome difficulties in diverse applications from cellular to organ scales. Such numerical methods may be classified by the type of computational mesh used for the fluid domain, into fixed mesh methods, moving mesh (boundary-fitted mesh) methods, and mesh-free methods. The type of computational mesh used is closely related to the characteristics of each method. We herein provide an overview of numerical methods recently used to simulate blood flow at macro and micro scales, with a focus on computational meshes. We also discuss recent progress in the multi-scale modeling of blood flow. PMID:26705108
Lian, Xiaojuan Cartoixà, Xavier; Miranda, Enrique; Suñé, Jordi; Perniola, Luca; Rurali, Riccardo; Long, Shibing; Liu, Ming
2014-06-28
We depart from first-principle simulations of electron transport along paths of oxygen vacancies in HfO{sub 2} to reformulate the Quantum Point Contact (QPC) model in terms of a bundle of such vacancy paths. By doing this, the number of model parameters is reduced and a much clearer link between the microscopic structure of the conductive filament (CF) and its electrical properties can be provided. The new multi-scale QPC model is applied to two different HfO{sub 2}-based devices operated in the unipolar and bipolar resistive switching (RS) modes. Extraction of the QPC model parameters from a statistically significant number of CFs allows revealing significant structural differences in the CF of these two types of devices and RS modes.
On the mass-coupling relation of multi-scale quantum integrable models
NASA Astrophysics Data System (ADS)
Bajnok, Zoltán; Balog, János; Ito, Katsushi; Satoh, Yuji; Tóth, Gábor Zsolt
2016-06-01
We determine exactly the mass-coupling relation for the simplest multi-scale quantum integrable model, the homogenous sine-Gordon model with two independent mass-scales. We first reformulate its perturbed coset CFT description in terms of the perturbation of a projected product of minimal models. This representation enables us to identify conserved tensor currents on the UV side. These UV operators are then mapped via form factor perturbation theory to operators on the IR side, which are characterized by their form factors. The relation between the UV and IR operators is given in terms of the sought-for mass-coupling relation. By generalizing the Θ sum rule Ward identity we are able to derive differential equations for the mass-coupling relation, which we solve in terms of hypergeometric functions. We check these results against the data obtained by numerically solving the thermodynamic Bethe Ansatz equations, and find a complete agreement.
Advances in multi-scale modeling of solidification and casting processes
NASA Astrophysics Data System (ADS)
Liu, Baicheng; Xu, Qingyan; Jing, Tao; Shen, Houfa; Han, Zhiqiang
2011-04-01
The development of the aviation, energy and automobile industries requires an advanced integrated product/process R&D systems which could optimize the product and the process design as well. Integrated computational materials engineering (ICME) is a promising approach to fulfill this requirement and make the product and process development efficient, economic, and environmentally friendly. Advances in multi-scale modeling of solidification and casting processes, including mathematical models as well as engineering applications are presented in the paper. Dendrite morphology of magnesium and aluminum alloy of solidification process by using phase field and cellular automaton methods, mathematical models of segregation of large steel ingot, and microstructure models of unidirectionally solidified turbine blade casting are studied and discussed. In addition, some engineering case studies, including microstructure simulation of aluminum casting for automobile industry, segregation of large steel ingot for energy industry, and microstructure simulation of unidirectionally solidified turbine blade castings for aviation industry are discussed.
Multi-scale computation methods: Their applications in lithium-ion battery research and development
NASA Astrophysics Data System (ADS)
Siqi, Shi; Jian, Gao; Yue, Liu; Yan, Zhao; Qu, Wu; Wangwei, Ju; Chuying, Ouyang; Ruijuan, Xiao
2016-01-01
Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. Project supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900).
Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis
NASA Technical Reports Server (NTRS)
Olevsky, Eugene; German, Randall M.
2012-01-01
A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.
Shape reconstruction of the multi-scale rough surface from multi-frequency phaseless data
NASA Astrophysics Data System (ADS)
Bao, Gang; Zhang, Lei
2016-08-01
We consider the problem of reconstructing the shape of multi-scale sound-soft large rough surfaces from phases measurements of the scattered field generated by tapered waves with multiple frequencies impinging on a rough surface. To overcome both the ill-posedness and nonlinearity of this problem for a single frequency, the Landweber regularization method based on the adjoint of the nonlinear objective functional is used. When the multi-frequency data is available, an approximation method is introduced to estimate the large-scale structure of the rough surface using the data measurements at the lowest frequency. The obtained estimate serves as an initial guess for a recursive linearization algorithm in frequency, which is used to capture the small scale structure of the rough surface. Numerical experiments are presented to illustrate the effectiveness of the method.
NASA Astrophysics Data System (ADS)
Casadei, F.; Ruzzene, M.
2011-04-01
This work illustrates the possibility to extend the field of application of the Multi-Scale Finite Element Method (MsFEM) to structural mechanics problems that involve localized geometrical discontinuities like cracks or notches. The main idea is to construct finite elements with an arbitrary number of edge nodes that describe the actual geometry of the damage with shape functions that are defined as local solutions of the differential operator of the specific problem according to the MsFEM approach. The small scale information are then brought to the large scale model through the coupling of the global system matrices that are assembled using classical finite element procedures. The efficiency of the method is demonstrated through selected numerical examples that constitute classical problems of great interest to the structural health monitoring community.
Objective fluxes in a multi-scale continuum description of sparse medium dynamics
NASA Astrophysics Data System (ADS)
Capriz, Gianfranco; Mariano, Paolo Maria
2014-12-01
We discuss reasons justifying a multi-scale continuum description of sparse media, which do not admit a choice of a representative volume element remaining permanent in time with constant mass. We suggest the choice of objective derivatives for time-varying terms in the balance equations pertinent to the scheme that we analyze, to avoid some problems connected with SO(3)-based changes in observers, which emerge within the setting of the standard theory of gases when we start from it to get continuum models. The scheme discussed here can be reduced to versions of the averaged regularizations of the Navier-Stokes equations. In our approach we have primarily in mind the continuum description of bodies like macro-molecular fluids or granular ones, even if what we propose can be significant in a broader setting.
Understanding Prairie Fen Hydrology - a Hierarchical Multi-Scale Groundwater Modeling Approach
NASA Astrophysics Data System (ADS)
Sampath, P.; Liao, H.; Abbas, H.; Ma, L.; Li, S.
2012-12-01
Prairie fens provide critical habitat to more than 50 rare species and significantly contribute to the biodiversity of the upper Great Lakes region. The sustainability of these globally unique ecosystems, however, requires that they be fed by a steady supply of pristine, calcareous groundwater. Understanding the hydrology that supports the existence of such fens is essential in preserving these valuable habitats. This research uses process-based multi-scale groundwater modeling for this purpose. Two fen-sites, MacCready Fen and Ives Road Fen, in Southern Michigan were systematically studied. A hierarchy of nested steady-state models was built for each fen-site to capture the system's dynamics at spatial scales ranging from the regional groundwater-shed to the local fens. The models utilize high-resolution Digital Elevation Models (DEM), National Hydrologic Datasets (NHD), a recently-assembled water-well database, and results from a state-wide groundwater mapping project to represent the complex hydro-geological and stress framework. The modeling system simulates both shallow glacial and deep bedrock aquifers as well as the interaction between surface water and groundwater. Aquifer heterogeneities were explicitly simulated with multi-scale transition probability geo-statistics. A two-way hydraulic head feedback mechanism was set up between the nested models, such that the parent models provided boundary conditions to the child models, and in turn the child models provided local information to the parent models. A hierarchical mass budget analysis was performed to estimate the seepage fluxes at the surface water/groundwater interfaces and to assess the relative importance of the processes at multiple scales that contribute water to the fens. The models were calibrated using observed base-flows at stream gauging stations and/or static water levels at wells. Three-dimensional particle tracking was used to predict the sources of water to the fens. We observed from the
Mechanisms for multi-scale structures in dense degenerate astrophysical plasmas
NASA Astrophysics Data System (ADS)
Shatashvili, N. L.; Mahajan, S. M.; Berezhiani, V. I.
2016-02-01
Two distinct routes lead to the creation of multi-scale equilibrium structures in dense degenerate plasmas, often met in astrophysical conditions. By analyzing an e-p-i plasma consisting of degenerate electrons and positrons with a small contamination of mobile classical ions, we show the creation of a new macro scale L_{macro} (controlled by ion concentration). The temperature and degeneracy enhancement effective inertia of bulk e-p components also makes the effective skin depths larger (much larger) than the standard skin depth. The emergence of these intermediate and macro scales lends immense richness to the process of structure formation, and vastly increases the channels for energy transformations. The possible role played by this mechanism in explaining the existence of large-scale structures in astrophysical objects with degenerate plasmas, is examined.
NASA Astrophysics Data System (ADS)
Beckers, J.-M.; Barth, A.; Tomazic, I.; Alvera-Azcárate, A.
2014-03-01
We present a method in which the optimal interpolation of multi-scale processes can be untangled into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well controlled test case. The clear guidelines deduced from this experiment are then applied in a real situation in which we combine large-scale analysis of hourly SEVIRI satellite images using DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.
Multi-scale Godunov-type method for cell-centered discrete Lagrangian hydrodynamics
NASA Astrophysics Data System (ADS)
Maire, Pierre-Henri; Nkonga, Boniface
2009-02-01
This work presents a multi-dimensional cell-centered unstructured finite volume scheme for the solution of multimaterial compressible fluid flows written in the Lagrangian formalism. This formulation is considered in the Arbitrary-Lagrangian-Eulerian (ALE) framework with the constraint that the mesh velocity and the fluid velocity coincide. The link between the vertex velocity and the fluid motion is obtained by a formulation of the momentum conservation on a class of multi-scale encased volumes around mesh vertices. The vertex velocity is derived with a nodal Riemann solver constructed in such a way that the mesh motion and the face fluxes are compatible. Finally, the resulting scheme conserves both momentum and total energy and, it satisfies a semi-discrete entropy inequality. The numerical results obtained for some classical 2D and 3D hydrodynamic test cases show the robustness and the accuracy of the proposed algorithm.
Multi-scale model for the hierarchical architecture of native cellulose hydrogels.
Martínez-Sanz, Marta; Mikkelsen, Deirdre; Flanagan, Bernadine; Gidley, Michael J; Gilbert, Elliot P
2016-08-20
The structure of protiated and deuterated cellulose hydrogels has been investigated using a multi-technique approach combining small-angle scattering with diffraction, spectroscopy and microscopy. A model for the multi-scale structure of native cellulose hydrogels is proposed which highlights the essential role of water at different structural levels characterised by: (i) the existence of cellulose microfibrils containing an impermeable crystalline core surrounded by a partially hydrated paracrystalline shell, (ii) the creation of a strong network of cellulose microfibrils held together by hydrogen bonding to form cellulose ribbons and (iii) the differential behaviour of tightly bound water held within the ribbons compared to bulk solvent. Deuterium labelling provides an effective platform on which to further investigate the role of different plant cell wall polysaccharides in cellulose composite formation through the production of selectively deuterated cellulose composite hydrogels. PMID:27178962
NASA Astrophysics Data System (ADS)
Deng, Yan; Chen, Xiuhua; Wang, Hai
2015-12-01
This paper investigates the elastic and failure behavior of textile composite laminates by using an analytical multi-scale correlating approach. The analyses are performed under the four scale levels, i.e. the laminate scale, representative unit cell (RUC) scale, tow architecture scale and fiber/matrix scale levels. The correlation between different scales is derived based on the continuum mechanics and homogenization method from which the stress and strain fields in multiple scales can be obtained concurrently. Effective modulus and ultimate failure strengths of different textile composite (plain weave, twill weave and satin weave) laminates are predicted solely from the corresponding constituent properties, braid geometrical parameters and lay-up. The damage and failure mechanisms at the constituent level are also determined by the micromechanical failure criteria. All the predicted results compare favorably with available experimental data. Parametric studies are also performed to examine the effect of various mechanical and geometrical parameters on the resulting mechanical properties.
MREG V1.1 : a multi-scale image registration algorithm for SAR applications.
Eichel, Paul H.
2013-08-01
MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.
Adapting to a changing environment: non-obvious thresholds in multi-scale systems.
Perryman, Clare; Wieczorek, Sebastian
2014-10-01
Many natural and technological systems fail to adapt to changing external conditions and move to a different state if the conditions vary too fast. Such 'non-adiabatic' processes are ubiquitous, but little understood. We identify these processes with a new nonlinear phenomenon-an intricate threshold where a forced system fails to adiabatically follow a changing stable state. In systems with multiple time scales, we derive existence conditions that show such thresholds to be generic, but non-obvious, meaning they cannot be captured by traditional stability theory. Rather, the phenomenon can be analysed using concepts from modern singular perturbation theory: folded singularities and canard trajectories, including composite canards. Thus, non-obvious thresholds should explain the failure to adapt to a changing environment in a wide range of multi-scale systems including: tipping points in the climate system, regime shifts in ecosystems, excitability in nerve cells, adaptation failure in regulatory genes and adiabatic switching in technology. PMID:25294963
Adapting to a changing environment: non-obvious thresholds in multi-scale systems
Perryman, Clare; Wieczorek, Sebastian
2014-01-01
Many natural and technological systems fail to adapt to changing external conditions and move to a different state if the conditions vary too fast. Such ‘non-adiabatic’ processes are ubiquitous, but little understood. We identify these processes with a new nonlinear phenomenon—an intricate threshold where a forced system fails to adiabatically follow a changing stable state. In systems with multiple time scales, we derive existence conditions that show such thresholds to be generic, but non-obvious, meaning they cannot be captured by traditional stability theory. Rather, the phenomenon can be analysed using concepts from modern singular perturbation theory: folded singularities and canard trajectories, including composite canards. Thus, non-obvious thresholds should explain the failure to adapt to a changing environment in a wide range of multi-scale systems including: tipping points in the climate system, regime shifts in ecosystems, excitability in nerve cells, adaptation failure in regulatory genes and adiabatic switching in technology. PMID:25294963
A multi-scale approach to the physics of ion beam cancer therapy
NASA Astrophysics Data System (ADS)
Solov'yov, A. V.; Surdutovich, E.; Scifoni, E.; Mishustin, I.; Greiner, W.
2008-12-01
We are developing a multi-scale approach to understanding the physics related to ion/proton-beam cancer therapy and the calculation of the probability of DNA damage as a result of irradiation of tumours with energetic ions (up to 430 MeV/u). This approach is inclusive with respect to different scales, starting from the long scale, defined by the ion stopping, followed by a smaller scale, defined by secondary electrons and radicals, and ending with the shortest scale, defined by interactions of secondaries with the DNA. We present calculations of the probabilities of single and double strand breaks of DNA and suggest a way to further elaborate on such calculations.
Nonsolvent-assisted fabrication of multi-scaled polylactide as superhydrophobic surfaces.
Chang, Yafang; Liu, Xuying; Yang, Huige; Zhang, Li; Cui, Zhe; Niu, Mingjun; Liu, Hongzhi; Chen, Jinzhou
2016-03-14
The solution-processing fabrication of superhydrophobic surfaces is currently intriguing, owing to high-efficiency, low cost, and energy-consuming. Here, a facile nonsolvent-assisted process was proposed for the fabrication of the multi-scaled surface roughness in polylactide (PLA) films, thereby resulting in a significant transformation in the surface wettability from intrinsic hydrophilicity to superhydrophobicity. Moreover, it was found that the surface topographical structure of PLA films can be manipulated by varying the compositions of the PLA solutions. And the samples showed superhydrophobic surfaces as well as high melting enthalpy and crystallinity. In particular, a high contact angle of 155.8° together with a high adhesive force of 184 μN was yielded with the assistance of a multi-nonsolvent system, which contributed to the co-existence of micro-/nano-scale hierarchical structures. PMID:26860288
Dual roles of shear flow in nonlinear multi-scale interactions
NASA Astrophysics Data System (ADS)
Hu, Z. Q.; Wang, Z. X.; Wei, L.; Li, J. Q.; Kishimoto, Y.
2016-01-01
Effect of shear flow on the multi-scale nonlinear interaction in plasmas is numerically investigated by using a self-consistent Landau-fluid model. Dual roles of shear flow in the process are discovered, significantly suppressing micro-scale fluctuations and dramatically promoting macro-scale fluctuations. Furthermore, its similar dual roles in turbulent transport are also demonstrated. The novel underlying mechanism for the nonlinear promotion is identified as the formation of a large vortex flow inside magnetic island, which as a common phenomenon have been often observed in space and magnetic fusion plasmas. The theoretical prediction on the threshold of shear flow based on an analytical modeling is verified via numerical simulations.
Multi-scale modeling of inter-granular fracture in UO2
Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.; Biner, S. Bulent
2015-03-01
A hierarchical multi-scale approach is pursued in this work to investigate the influence of porosity, pore and grain size on the intergranular brittle fracture in UO2. In this approach, molecular dynamics simulations are performed to obtain the fracture properties for different grain boundary types. A phase-field model is then utilized to perform intergranular fracture simulations of representative microstructures with different porosities, pore and grain sizes. In these simulations the grain boundary fracture properties obtained from molecular dynamics simulations are used. The responses from the phase-field fracture simulations are then fitted with a stress-based brittle fracture model usable at the engineering scale. This approach encapsulates three different length and time scales, and allows the development of microstructurally informed engineering scale model from properties evaluated at the atomistic scale.
Local topology, multi-scale interactions and stochasticity in space plasma physics
NASA Astrophysics Data System (ADS)
Materassi, M.; Consolini, G.
2014-12-01
In space physics very important phenomena, as reconnection, are determined by the local topology of the streamlines and magnetic lines of plasma, and by multi-scale interactions. In this work, an attempt is presented to deal with dynamical variables highlighting both the local topology and the role of space scale. In order to promote local topology to the role of a dynamical variable, use is made of the gradients of the velocity and of the magnetic field, through which the description of the local topology becomes very transparent. Such a formulation, well explored in Hydrodynamics, is extended here to the MHD. The new dynamical variables evolve in a finite scale stochastic dynamics: letting the scale appear explicitly as a variable of the problem helps studying inter-scale processes, while statistical aspects of topological variable dynamics are expected to be extremely relevant in the turbulent regime, where a stochastic field scenario is, in practice, taking place.
Multi-Scale Structure of Solar Wind Transients Coincident with Electron Drift-Echoes
NASA Astrophysics Data System (ADS)
Mulligan, T. L.; O'Brien, T. P., III; Claudepierre, S. G.; Roeder, J. L.; Green, J. C.; Fennell, J. F.
2014-12-01
It is well known that impulsive substorm dipolarizations on the night side produce dispersionless injections of keV particles, for which multiple drift echoes can be observed. The impact these injections have on radiation belt particles is less well understood. We present a preliminary investigation into the types of solar wind transients (i.e. coronal mass ejections (CMEs), co-rotational and/or stream interaction regions (CIRs and/or SIRs), high-speed streams (HSS), interplanetary shock events, etc.) that correlate with observations of electron drift echoes during the Van Allen Probes mission. We use data from ACE and Wind during the current solar cycle (24) to establish criteria for determining critical regions and sub-structures within these transients that correlate with observed drift echoes. This initial study is part of a more comprehensive characterization of the multi-scale structure of solar wind drivers coincident with drift echoes through different phases of the solar cycle.
A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery
NASA Technical Reports Server (NTRS)
Gamon, John A.; Lee, Lai-Fun; Qiu, Hong-Lie; Davis, Stephen; Roberts, Dar A.; Ustin, Susan L.
1998-01-01
apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.
Multi-scale measures of rugosity, slope and aspect from benthic stereo image reconstructions.
Friedman, Ariell; Pizarro, Oscar; Williams, Stefan B; Johnson-Roberson, Matthew
2012-01-01
This paper demonstrates how multi-scale measures of rugosity, slope and aspect can be derived from fine-scale bathymetric reconstructions created from geo-referenced stereo imagery. We generate three-dimensional reconstructions over large spatial scales using data collected by Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), manned submersibles and diver-held imaging systems. We propose a new method for calculating rugosity in a Delaunay triangulated surface mesh by projecting areas onto the plane of best fit using Principal Component Analysis (PCA). Slope and aspect can be calculated with very little extra effort, and fitting a plane serves to decouple rugosity from slope. We compare the results of the virtual terrain complexity calculations with experimental results using conventional in-situ measurement methods. We show that performing calculations over a digital terrain reconstruction is more flexible, robust and easily repeatable. In addition, the method is non-contact and provides much less environmental impact compared to traditional survey techniques. For diver-based surveys, the time underwater needed to collect rugosity data is significantly reduced and, being a technique based on images, it is possible to use robotic platforms that can operate beyond diver depths. Measurements can be calculated exhaustively at multiple scales for surveys with tens of thousands of images covering thousands of square metres. The technique is demonstrated on data gathered by a diver-rig and an AUV, on small single-transect surveys and on a larger, dense survey that covers over [Formula: see text]. Stereo images provide 3D structure as well as visual appearance, which could potentially feed into automated classification techniques. Our multi-scale rugosity, slope and aspect measures have already been adopted in a number of marine science studies. This paper presents a detailed description of the method and thoroughly validates it against traditional
Automatic Multi-Scale Calibration Procedure for Nested Hydrological-Hydrogeological Regional Models
NASA Astrophysics Data System (ADS)
Labarthe, B.; Abasq, L.; Flipo, N.; de Fouquet, C. D.
2014-12-01
Large hydrosystem modelling and understanding is a complex process depending on regional and local processes. A nested interface concept has been implemented in the hydrosystem modelling platform for a large alluvial plain model (300 km2) part of a 11000 km2 multi-layer aquifer system, included in the Seine basin (65000 km2, France). The platform couples hydrological and hydrogeological processes through four spatially distributed modules (Mass balance, Unsaturated Zone, River and Groundwater). An automatic multi-scale calibration procedure is proposed. Using different data sets from regional scale (117 gauging stations and 183 piezometers over the 65000 km2) to the intermediate scale(dense past piezometric snapshot), it permits the calibration and homogenization of model parameters over scales.The stepwise procedure starts with the optimisation of the water mass balance parameters at regional scale using a conceptual 7 parameters bucket model coupled with the inverse modelling tool PEST. The multi-objective function is derived from river discharges and their de-composition by hydrograph separation. The separation is performed at each gauging station using an automatic procedure based one Chapman filter. Then, the model is run at the regional scale to provide recharge estimate and regional fluxes to the groundwater local model. Another inversion method is then used to determine the local hydrodynamic parameters. This procedure used an initial kriged transmissivity field which is successively updated until the simulated hydraulic head distribution equals a reference one obtained by krigging. Then, the local parameters are upscaled to the regional model by renormalisation procedure.This multi-scale automatic calibration procedure enhances both the local and regional processes representation. Indeed, it permits a better description of local heterogeneities and of the associated processes which are transposed into the regional model, improving the overall performances
A Multi-Scale Interaction Model for Madden-Julian Oscillation
NASA Astrophysics Data System (ADS)
Wang, B.; Liu, F.
2010-12-01
Madden-Julian oscillation (MJO) is an equatorial, planetary scale circulation system coupled with a multi-scale convective complex. The nature and roles of multi-scale interaction (MSI) on MJO dynamics has not been well understood. Here we formulate a prototype theoretical model to advance our understanding the MSI in MJO. The model integrates three essential elements: a) large scale equatorial wave dynamics driven by boundary layer frictional convergence instability (FCI), b) effects of multi-cloud heating and an instability arising from synoptic system-induced convective momentum transfer (CMT), and c) interaction between the planetary and synoptic systems. We show that the CMT mechanism tends to yield a growing stationary mode with a quadrupole-vortex horizontal structure (enhanced Rossby wave component); whereas the FCI favors a fast eastward-moving mode with a Gill-Pattern structure (enhanced Kelvin wave response). The MSI instability can stem from either FCI or CMT mechanisms or both, depending on the ratio of deep convective versus stratiform/congestus heating. With increasing stratiform/congestus heating, the FCI weakens while the CMT becomes more effective. A growing MSI mode has a mixed horizontal structure of CMT and FCI and prefers slow eastward propagation. The FCI sets the eastward propagation, and CMT plays a vital role in slowing down the propagation speed. These results encourage further observational diagnosis of multi-cloud structure and heating profiles in the MJO convective complex and improvement of models’ capability in reproducing correct partitioning of cloud amounts between deep convective and stratiform/congestus clouds.
Individual-specific multi-scale finite element simulation of cortical bone of human proximal femur
Ascenzi, Maria-Grazia; Kardas, Dieter; Nackenhorst, Udo; Keyak, Joyce H.
2013-07-01
We present an innovative method to perform multi-scale finite element analyses of the cortical component of the femur using the individual’s (1) computed tomography scan; and (2) a bone specimen obtained in conjunction with orthopedic surgery. The method enables study of micro-structural characteristics regulating strains and stresses under physiological loading conditions. The analysis of the micro-structural scenarios that cause variation of strain and stress is the first step in understanding the elevated strains and stresses in bone tissue, which are indicative of higher likelihood of micro-crack formation in bone, implicated in consequent remodeling or macroscopic bone fracture. Evidence that micro-structure varies with clinical history and contributes in significant, but poorly understood, ways to bone function, motivates the method’s development, as does need for software tools to investigate relationships between macroscopic loading and micro-structure. Three applications – varying region of interest, bone mineral density, and orientation of collagen type I, illustrate the method. We show, in comparison between physiological loading and simple compression of a patient’s femur, that strains computed at the multi-scale model’s micro-level: (i) differ; and (ii) depend on local collagen-apatite orientation and degree of calcification. Our findings confirm the strain concentration role of osteocyte lacunae, important for mechano-transduction. We hypothesize occurrence of micro-crack formation, leading either to remodeling or macroscopic fracture, when the computed strains exceed the elastic range observed in micro-structural testing.
Monitoring forest dynamics with multi-scale and time series imagery.
Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong
2016-05-01
To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable. PMID:27056478
Response of Moist Convection to Multi-scale Surface Flux Heterogeneity
NASA Astrophysics Data System (ADS)
Kang, S. L.; Ryu, J. H.
2015-12-01
We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.
Multi-scale curvature for automated identification of glaciated mountain landscapes☆
Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar
2014-01-01
Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes. PMID:24748703
Multi-scale thermalhydraulic analyses performed in Nuresim and Nurisp projects
Bestion, D.; Lucas, D.; Anglart, H.; Niceno, B.; Vyskocil, L.
2012-07-01
The NURESIM and NURISP successive projects of the 6. and 7. European Framework Programs joined the efforts of 21 partners for developing and validating a reference multi-physics and multi-scale platform for reactor simulation. The platform includes system codes, component codes, and also CFD or CMFD simulation tools. Fine scale CFD simulations are useful for a better understanding of physical processes, for the prediction of small scale geometrical effects and for solving problems that require a fine space and/or time resolution. Many important safety issues usually treated at the system scale may now benefit from investigations at a CFD scale. The Pressurized Thermal Shock is investigated using several simulation scales including Direct Numerical Simulation, Large Eddy Simulation, Very Large Eddy Simulation and RANS approaches. At the end a coupling of system code and CFD is applied. Condensation Induced Water-Hammer was also investigated at both CFD and 1-D scale. Boiling flow in a reactor core up to Departure from Nucleate Boiling or Dry-Out is investigated at scales much smaller than the classical subchannel analysis codes. DNS was used to investigate very local processes whereas CFD in both RANS and LES was used to simulate bubbly flow and Euler-Lagrange simulations were used for annular mist flow investigations. Loss of Coolant Accidents are usually treated by system codes. Some related issues are now revisited at the CFD scale. In each case the progress of the analysis is summarized and the benefit of the multi-scale approach is shown. (authors)
Multi-Scale Entrainment of Coupled Neuronal Oscillations in Primary Auditory Cortex
O’Connell, M. N.; Barczak, A.; Ross, D.; McGinnis, T.; Schroeder, C. E.; Lakatos, P.
2015-01-01
Earlier studies demonstrate that when the frequency of rhythmic tone sequences or streams is task relevant, ongoing excitability fluctuations (oscillations) of neuronal ensembles in primary auditory cortex (A1) entrain to stimulation in a frequency dependent way that sharpens frequency tuning. The phase distribution across A1 neuronal ensembles at time points when attended stimuli are predicted to occur reflects the focus of attention along the spectral attribute of auditory stimuli. This study examined how neuronal activity is modulated if only the temporal features of rhythmic stimulus streams are relevant. We presented macaques with auditory clicks arranged in 33 Hz (gamma timescale) quintets, repeated at a 1.6 Hz (delta timescale) rate. Such multi-scale, hierarchically organized temporal structure is characteristic of vocalizations and other natural stimuli. Monkeys were required to detect and respond to deviations in the temporal pattern of gamma quintets. As expected, engagement in the auditory task resulted in the multi-scale entrainment of delta- and gamma-band neuronal oscillations across all of A1. Surprisingly, however, the phase-alignment, and thus, the physiological impact of entrainment differed across the tonotopic map in A1. In the region of 11–16 kHz representation, entrainment most often aligned high excitability oscillatory phases with task-relevant events in the input stream and thus resulted in response enhancement. In the remainder of the A1 sites, entrainment generally resulted in response suppression. Our data indicate that the suppressive effects were due to low excitability phase delta oscillatory entrainment and the phase amplitude coupling of delta and gamma oscillations. Regardless of the phase or frequency, entrainment appeared stronger in left A1, indicative of the hemispheric lateralization of auditory function. PMID:26696866
Multi-scale model analysis and hindcast of the 2013 Colorado Flood
NASA Astrophysics Data System (ADS)
Gochis, David; Yu, Wei; Sampson, Kevin; Dugger, Aubrey; McCreight, James; Zhang, Yongxin; Ikeda, Kyoko
2015-04-01
While the generation of most flood and flash flood events is fundamentally linked to the occurrence of heavy rainfall, the physical mechanisms responsible for translating rainfall into floods are complex and manifold. These runoff generation processes evolve over many spatial and temporal scales during the course of flooding events. As such robust flood and flash flood prediction systems need to account for multitude of terrestrial processes occurring over a wide range of space and time scales. One such extreme multiscale flood event was the 2013 Colorado Flood in which over 400 mm of rainfall fell along the Rock Mountain mountain front region over the course of a few days. The flooding impacts from this heavy rainfall event included not only high, fast flows in steep mountain streams but also included large areas of inundation on the adjacent plains and numerous soil saturation excess impacts such as hillslope failures and groundwater intrusions into domestic structures. A multi-scale and multi-process evaluation of this flood event is performed using the community WRF-Hydro modeling system. We incorporate several operational quantitative precipitation estimate and quantitative precipitation forecast products in the analysis and document the skill of multiple configurations of WRF-Hydro physics options across a range of contributing area length scales. Emphasis is placed on assessing how well the different model configurations capture the multi-scale streamflow response from small headwater catchments out to the entire South Platte River basin whose total contributing area exceeds 25,000 sq km. In addition to streamflow we also present evaluations of event simulations and hindcasts of soil saturation fraction, groundwater levels and inundated areas as a means of assessing different runoff generation mechanisms. Finally, results from a U.S. national-scale, fully-coupled hydrometeorological hindcast of the 2013 Colorado flood event using the combined WRF atmospheric
Multi-scale approach for predicting fish species distributions across coral reef seascapes.
Pittman, Simon J; Brown, Kerry A
2011-01-01
Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation
A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function
Röhrle, O.; Davidson, J. B.; Pullan, A. J.
2012-01-01
Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509
Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes
Pittman, Simon J.; Brown, Kerry A.
2011-01-01
Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support
Multi-Scale Entrainment of Coupled Neuronal Oscillations in Primary Auditory Cortex.
O'Connell, M N; Barczak, A; Ross, D; McGinnis, T; Schroeder, C E; Lakatos, P
2015-01-01
Earlier studies demonstrate that when the frequency of rhythmic tone sequences or streams is task relevant, ongoing excitability fluctuations (oscillations) of neuronal ensembles in primary auditory cortex (A1) entrain to stimulation in a frequency dependent way that sharpens frequency tuning. The phase distribution across A1 neuronal ensembles at time points when attended stimuli are predicted to occur reflects the focus of attention along the spectral attribute of auditory stimuli. This study examined how neuronal activity is modulated if only the temporal features of rhythmic stimulus streams are relevant. We presented macaques with auditory clicks arranged in 33 Hz (gamma timescale) quintets, repeated at a 1.6 Hz (delta timescale) rate. Such multi-scale, hierarchically organized temporal structure is characteristic of vocalizations and other natural stimuli. Monkeys were required to detect and respond to deviations in the temporal pattern of gamma quintets. As expected, engagement in the auditory task resulted in the multi-scale entrainment of delta- and gamma-band neuronal oscillations across all of A1. Surprisingly, however, the phase-alignment, and thus, the physiological impact of entrainment differed across the tonotopic map in A1. In the region of 11-16 kHz representation, entrainment most often aligned high excitability oscillatory phases with task-relevant events in the input stream and thus resulted in response enhancement. In the remainder of the A1 sites, entrainment generally resulted in response suppression. Our data indicate that the suppressive effects were due to low excitability phase delta oscillatory entrainment and the phase amplitude coupling of delta and gamma oscillations. Regardless of the phase or frequency, entrainment appeared stronger in left A1, indicative of the hemispheric lateralization of auditory function. PMID:26696866
Multi-scale curvature for automated identification of glaciated mountain landscapes.
Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R; Schrott, Lothar
2014-03-15
Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes. PMID:24748703
Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions
Friedman, Ariell; Pizarro, Oscar; Williams, Stefan B.; Johnson-Roberson, Matthew
2012-01-01
This paper demonstrates how multi-scale measures of rugosity, slope and aspect can be derived from fine-scale bathymetric reconstructions created from geo-referenced stereo imagery. We generate three-dimensional reconstructions over large spatial scales using data collected by Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), manned submersibles and diver-held imaging systems. We propose a new method for calculating rugosity in a Delaunay triangulated surface mesh by projecting areas onto the plane of best fit using Principal Component Analysis (PCA). Slope and aspect can be calculated with very little extra effort, and fitting a plane serves to decouple rugosity from slope. We compare the results of the virtual terrain complexity calculations with experimental results using conventional in-situ measurement methods. We show that performing calculations over a digital terrain reconstruction is more flexible, robust and easily repeatable. In addition, the method is non-contact and provides much less environmental impact compared to traditional survey techniques. For diver-based surveys, the time underwater needed to collect rugosity data is significantly reduced and, being a technique based on images, it is possible to use robotic platforms that can operate beyond diver depths. Measurements can be calculated exhaustively at multiple scales for surveys with tens of thousands of images covering thousands of square metres. The technique is demonstrated on data gathered by a diver-rig and an AUV, on small single-transect surveys and on a larger, dense survey that covers over . Stereo images provide 3D structure as well as visual appearance, which could potentially feed into automated classification techniques. Our multi-scale rugosity, slope and aspect measures have already been adopted in a number of marine science studies. This paper presents a detailed description of the method and thoroughly validates it against traditional in
Next Generation Multi-Scale Quantum Simulation Software for Strongly Correlated Materials
Jarrell, Mark
2014-11-18
The goal of this project was to develop a new formalism for the correlated electron problem, which we call, the Multi Scale Many Body formalism. This report will focus on the work done at the Louisiana State University (LSU) since the mid term report. The LSU group moved from the University of Cincinnati (UC) to LSU in the summer of 2008. In the last full year at UC, only half of the funds were received and it took nearly two years for the funds to be transferred from UC to LSU . This effectively shut down the research at LSU until the transfer was completed in 2011, there were also two no-cost extensions of the grant until August of this year. The grant ended for the other SciDAC partners at Davis and ORNL in 2011. Since the mid term report, the LSU group has published 19 papers [P1-P19] acknowledging this SciDAC, which are listed below. In addition, numerous invited talked acknowledged the SciDAC. Below, we will summarize the work at LSU since the mid-term report and mainly since funding resumed. The projects include the further development of multi-scale methods for correlated systems (1), the study of quantum criticality at finite doping in the Hubbard model (2), the description of a promising new method to study Anderson localization with a million-fold reduction of computational complexity!, the description of other projects (4), and (5) a workshop to close out the project that brought together exascale program developers (Stellar, MPI, OpenMP,...) with applications developers.
Multi-scale evaluation of the IFloodS radar-rainfall products
NASA Astrophysics Data System (ADS)
Seo, Bong-Chul; Krajewski, Witold; Cunha, Luciana; Dolan, Brenda; Smith, James; Rutledge, Steven; Petersen, Walter
2014-05-01
Rainfall products estimated using ground-based radars are often used as reference to assess capabilities and limitations of using satellite rainfall estimates in hydrologic modeling and prediction. During the spring of 2013, NASA conducted a hydrology-oriented field campaign called Iowa Flood Studies (IFloodS) in the central and northeastern Iowa in the United States, as a part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related rainfall processes and the predictability in flood forecasting. While there are multiple types of rainfall data sets (e.g., satellite, radar, rain gauge, and disdrometer) available as the observational assets of IFloodS, the authors focus on the evaluation of multi-scale rainfall products observed from ground-based radars. The radar-only products used in the evaluation are the NEXRAD single polarization products (i.e., Stage IV, NMQ Q2, and Iowa Flood Center rainfall maps) and products generated using dual-polarization procedures (i.e., the U.S. National Weather Service operational and Colorado State University experimental blended precipitation processing algorithms) with comparable space and time resolution. The NASA NPOL S-band radar products are also evaluated and compared with the aforementioned NEXRAD products. The uncertainty for different temporal and spatial resolution products is characterized using ground reference data of dense rain gauge and disdrometer networks. This multi-scale characterization is required for hydrologic modeling frameworks that assess model predictive abilities as a function of space and time scales.
Soranno, Patricia A; Bissell, Edward G; Cheruvelil, Kendra S; Christel, Samuel T; Collins, Sarah M; Fergus, C Emi; Filstrup, Christopher T; Lapierre, Jean-Francois; Lottig, Noah R; Oliver, Samantha K; Scott, Caren E; Smith, Nicole J; Stopyak, Scott; Yuan, Shuai; Bremigan, Mary Tate; Downing, John A; Gries, Corinna; Henry, Emily N; Skaff, Nick K; Stanley, Emily H; Stow, Craig A; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E
2015-01-01
Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km(2)). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated
Soranno, Patricia A.; Bissell, E.G.; Cheruvelil, Kendra S.; Christel, Samuel T.; Collins, Sarah M.; Fergus, C. Emi; Filstrup, Christopher T.; Lapierre, Jean-Francois; Lotting, Noah R.; Oliver, Samantha K.; Scott, Caren E.; Smith, Nicole J.; Stopyak, Scott; Yuan, Shuai; Bremigan, Mary Tate; Downing, John A.; Gries, Corinna; Henry, Emily N.; Skaff, Nick K.; Stanley, Emily H.; Stow, Craig A.; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E.
2015-01-01
Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km2). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated
NASA Astrophysics Data System (ADS)
Knap, J.; Spear, C. E.; Borodin, O.; Leiter, K. W.
2015-10-01
We describe the development of a large-scale high-throughput application for discovery in materials science. Our point of departure is a computational framework for distributed multi-scale computation. We augment the original framework with a specialized module whose role is to route evaluation requests needed by the high-throughput application to a collection of available computational resources. We evaluate the feasibility and performance of the resulting high-throughput computational framework by carrying out a high-throughput study of battery solvents. Our results indicate that distributed multi-scale computing, by virtue of its adaptive nature, is particularly well-suited for building high-throughput applications.
Multi-scale osteointegration and neovascularization of biphasic calcium phosphate bone scaffolds
NASA Astrophysics Data System (ADS)
Lan, Sheeny K.
presence of osteocytes within scaffold micropores is an indication of scaffold osteoinductivity because a chemotactic factor must be present to induce cell migration into pores on the order of the cell diameter. It is likely that the scaffold undergoes in vivo modifications involving formation of a biological apatite layer within scaffold micropores and possibly co-precipitation of endogenous osteoinductive proteins. To further investigate the effects of scaffold osteoinductivity, BCP scaffolds were implanted in porcine mandibular defects with rhBMP-2, which was partially sequestered in the micropores. Cell migration into osteoinductive scaffold micropores can be enhanced through the delivery of exogenous rhBMP-2 further promoting multi-scale osteointegration. Finally, endothelial colony forming cells (ECFCs) isolated from human umbilical cord blood (UCB) were evaluated in terms of their in vivo vasculogenic potential in the context of bone formation. This work was completed to determine if ECFCs could be utilized in a bone tissue engineering construct to promote neovascularization. ECFCs were combined with a BCP scaffold and rhBMP-2 and implanted subcutaneously on the abdominal wall of NOD/SCID mice. The result was formation of perfused human vessels within BCP scaffold macropores that were present at 4 weeks. The high density and persistence of human vessels at four weeks indicates that human UCB ECFCs exceed their reported in vivo vasculogenic potential when combined with rhBMP-2 and a BCP scaffold. This shows a dual role for BMP-2 in the context of bone regeneration. Collectively, the thesis demonstrates that (1) the design of synthetic bone scaffolds should include controlled multi-scale porosity to promote multi-scale osteointegration, which may significantly improve scaffold mechanical properties and (2) human umbilical cord blood-derived endothelial colony forming cells have potential for promoting neovascularization in a bone defect when combined with rhBMP-2.
NASA Astrophysics Data System (ADS)
Loizos, Kyle; RamRakhyani, Anil Kumar; Anderson, James; Marc, Robert; Lazzi, Gianluca
2016-06-01
This study proposes a methodology for computationally estimating resistive properties of tissue in multi-scale computational models, used for studying the interaction of electromagnetic fields with neural tissue, with applications to both dosimetry and neuroprosthetics. Traditionally, models at bulk tissue- and cellular-level scales are solved independently, linking resulting voltage from existing resistive tissue-scale models as extracellular sources to cellular models. This allows for solving the effects that external electric fields have on cellular activity. There are two major limitations to this approach: first, the resistive properties of the tissue need to be chosen, of which there are contradicting measurements in literature; second, the measurements of resistivity themselves may be inaccurate, leading to the mentioned contradicting results found across different studies. Our proposed methodology allows for constructing computed resistivity profiles using knowledge of only the neural morphology within the multi-scale model, resulting in a practical implementation of the effective medium theory; this bypasses concerns regarding the choice of resistive properties and accuracy of measurement setups. A multi-scale model of retina is constructed with an external electrode to serve as a test bench for analyzing existing and resulting resistivity profiles, and validation is presented through the reconstruction of a published resistivity profile of retina tissue. Results include a computed resistivity profile of retina tissue for use with a retina multi-scale model used to analyze effects of external electric fields on neural activity.
Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.
2015-01-01
Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228
Loizos, Kyle; RamRakhyani, Anil Kumar; Anderson, James; Marc, Robert; Lazzi, Gianluca
2016-06-21
This study proposes a methodology for computationally estimating resistive properties of tissue in multi-scale computational models, used for studying the interaction of electromagnetic fields with neural tissue, with applications to both dosimetry and neuroprosthetics. Traditionally, models at bulk tissue- and cellular-level scales are solved independently, linking resulting voltage from existing resistive tissue-scale models as extracellular sources to cellular models. This allows for solving the effects that external electric fields have on cellular activity. There are two major limitations to this approach: first, the resistive properties of the tissue need to be chosen, of which there are contradicting measurements in literature; second, the measurements of resistivity themselves may be inaccurate, leading to the mentioned contradicting results found across different studies. Our proposed methodology allows for constructing computed resistivity profiles using knowledge of only the neural morphology within the multi-scale model, resulting in a practical implementation of the effective medium theory; this bypasses concerns regarding the choice of resistive properties and accuracy of measurement setups. A multi-scale model of retina is constructed with an external electrode to serve as a test bench for analyzing existing and resulting resistivity profiles, and validation is presented through the reconstruction of a published resistivity profile of retina tissue. Results include a computed resistivity profile of retina tissue for use with a retina multi-scale model used to analyze effects of external electric fields on neural activity. PMID:27223656
The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...
NASA Astrophysics Data System (ADS)
Lahousse, T.; Chang, K. T.; Lin, Y. H.
2011-10-01
We developed a multi-scale OBIA (object-based image analysis) landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR) of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.
A Multi-Scale Comparative Study of Shape and Sprawl in Metropolitan Regions of the United States
ERIC Educational Resources Information Center
Kugler, Tracy A.
2012-01-01
This dissertation constitutes a multi-scale quantitative and qualitative investigation of patterns of urban development in metropolitan regions of the United States. This work has generated a comprehensive data set on spatial patterns of metropolitan development in the U.S. and an approach to the study of such patterns that can be used to further…
Onishi, Koshiro; Sakamoto, Hidetoshi; Kuramae, Hiroyuki; Morimoto, Hideo; Nakamachi, Eiji
2010-06-15
The purpose of this study is forming a high formability aluminum alloy sheet metal by controlling the microcrystal structure and the texture. So asymmetric rolling is applied to the material process. Analysis method is crystal plasticity multi-scale finite element analysis based on crystallographic homogenization.
Loizos, Kyle; RamRakhyani, Anil Kumar; Anderson, James; Marc, Robert; Lazzi, Gianluca
2016-01-01
This study proposes a methodology for computationally estimating resistive properties of tissue in multi-scale computational models, used for studying the interaction of electromagnetic fields with neural tissue, with applications to both dosimetry and neuroprosthetics. Traditionally, models at bulk tissue- and cellular-level scales are solved independently, linking resulting voltage from existing resistive tissue-scale models as extracellular sources to cellular models. This allows for solving the effects that external electric fields have on cellular activity. There are two major limitations to this approach: first, the resistive properties of the tissue need to be chosen, of which there are contradicting measurements in literature; second, the measurements of resistivity themselves may be inaccurate, leading to the mentioned contradicting results found across different studies. Our proposed methodology allows for constructing computed resistivity profiles using knowledge of only the neural morphology within the multi-scale model, resulting in a practical implementation of the effective medium theory; this bypasses concerns regarding the choice of resistive properties and accuracy of measurement setups. A multi-scale model of retina is constructed with an external electrode to serve as a test bench for analyzing existing and resulting resistivity profiles, and validation is presented through the reconstruction of a published resistivity profile of retina tissue. Results include a computed resistivity profile of retina tissue for use with a retina multi-scale model used to analyze effects of external electric fields on neural activity. PMID:27223656
Optimal Multi-scale Demand-side Management for Continuous Power-Intensive Processes
NASA Astrophysics Data System (ADS)
Mitra, Sumit
With the advent of deregulation in electricity markets and an increasing share of intermittent power generation sources, the profitability of industrial consumers that operate power-intensive processes has become directly linked to the variability in energy prices. Thus, for industrial consumers that are able to adjust to the fluctuations, time-sensitive electricity prices (as part of so-called Demand-Side Management (DSM) in the smart grid) offer potential economical incentives. In this thesis, we introduce optimization models and decomposition strategies for the multi-scale Demand-Side Management of continuous power-intensive processes. On an operational level, we derive a mode formulation for scheduling under time-sensitive electricity prices. The formulation is applied to air separation plants and cement plants to minimize the operating cost. We also describe how a mode formulation can be used for industrial combined heat and power plants that are co-located at integrated chemical sites to increase operating profit by adjusting their steam and electricity production according to their inherent flexibility. Furthermore, a robust optimization formulation is developed to address the uncertainty in electricity prices by accounting for correlations and multiple ranges in the realization of the random variables. On a strategic level, we introduce a multi-scale model that provides an understanding of the value of flexibility of the current plant configuration and the value of additional flexibility in terms of retrofits for Demand-Side Management under product demand uncertainty. The integration of multiple time scales leads to large-scale two-stage stochastic programming problems, for which we need to apply decomposition strategies in order to obtain a good solution within a reasonable amount of time. Hence, we describe two decomposition schemes that can be applied to solve two-stage stochastic programming problems: First, a hybrid bi-level decomposition scheme with
Multi-scale Seismic Waveform Tomography and the Evolution of Oceanic Lithosphere
NASA Astrophysics Data System (ADS)
Auer, L.; Boschi, L.; Becker, T. W.; van Driel, M.; Stähler, S. C.; Nissen-Meyer, T.; Sigloch, K.
2014-12-01
The advent of high-resolution seismometer array deployments such as USArray, IberArray or the upcoming AlpArray pave the way for significantly enhanced tomographic resolution across their tectonically complex target areas. The optimal interpretation of these datasets requires a new generation of multiple-resolution tomographic imaging approaches. Our recent anisotropic S-wave tomography model SAVANI is adaptive and multi-scale in the sense that it relies on a data-driven adaptive parameterization scheme, which automatically adjusts grid size to local ray sampling density, where demanded by the data. Such automatic rescaling of the parameterization grid provides an efficient means to stepwise improve upon a global background model by updating the tomographic system whenever new observations become available. Since our method employs phase and dispersion measurements from the complete time- and frequency range of the seismic record, it is akin to other types of waveform inversion and sensitive across the entire depth extent of the mantle. We present our current work towards an update of the purely ray-theoretical first version of SAVANI, which involves the reinterpretation of the regional portion of our global dataset using more accurate full-waveform based sensitivity functions that should facilitate an adequate extraction of high-resolution regional structure in areas where data coverage permits it. Adaptive-resolution tomography models, as developed with our algorithm, honour the multi-scale nature of mantle convection, and have various advantages over purely global models when applied in the study of global and regional geodynamics. We focus here on upper mantle dynamics and the evolution of the oceanic lithosphere. Importantly, we find a distinct decorrelation between anisotropy patterns as observed in our tomography and conceptual half-space cooling models or dynamic predictions of anisotropic texture, respectively. This observation implies that sub
Multi-scale analysis of hydrologic change in the Japanese megalopolis by using integrated approach
NASA Astrophysics Data System (ADS)
Nakayama, T.; Fujita, T.; Hashimoto, S.; Hamano, H.
2008-12-01
We coupled the process-based NIES Integrated Catchment-based Eco-hydrology (NICE) model (Nakayama,2008a,2008b; Nakayama and Watanabe,2004,2006,2008a,2008b; Nakayama et al.,2006,2007) to an urban canopy model and the Regional Atmospheric Modeling System (RAMS) in order to simulate the effect of urban structure and human activity on the change of water and heat cycles in the atmospheric/land and the interfacial areas of the Japanese megalopolis. The simulation was conducted with multi-scale levels in horizontally regional (130x130 mesh with a grid spacing of 2 km) - urban area (180x130 mesh with a grid spacing of 200 m), and in vertically atmosphere-surface-unsaturated-saturated layers. The model reproduced excellently the water and heat budgets including groundwater level, air temperature, and humidity, et al. in various types of natural/artificial landcover. The simulated results suggest that the latent heat flux has a strong impact on the hydrologic cycle and the cooling temperature in comparison with the heat budget analysis of observation data. Because the water temperature in an aquifer is almost constant throughout the year, it is estimated that the use of groundwater as a heat sink would be very effective for tackling the urban heat island phenomenon, particularly during the summer (Ministry of Environment, 2003). We evaluated the relationship between the effect of groundwater use to ameliorate the heat island phenomenon and the effect of infiltration on the water cycle in the catchment. The procedure to integrate the multi-scale model simulation with political scenario for the effective selection and use of ecosystem service sites in would be a very powerful approach to create thermally-pleasing environments in the megalopolis. References; Ministry of Environment,http://www.env.go.jp/air/report/h15-02/,2003. Nakayama,ECOMOD,doi:10.1016/j.ecolmodel.2008.02.017,2008a. Nakayama,FORECO,doi:10.1016/j.foreco.2008.07.017,2008b. Nakayama and Watanabe,WRR,doi:10
SLIM: A multi-scale model of the land-sea continuum
NASA Astrophysics Data System (ADS)
De Maet, T.; Hanert, E.; Deleersnijder, E.; Fichefet, T.; Legat, V.; Remacle, J. F.; Soares Frazao, S.; Vanclooster, M.; Lambrechts, J.; König Beatty, C.; Bouillon, S.; de Brye, B.; Gourgue, O.; Kärnä, T.; Lietaer, O.; Pestiaux, A.; Slaoui, K.; Thomas, C.
2012-04-01
The hydrosphere is made up of a number media, such as the oceans, the shelf seas, the estuaries, the rivers, the land surface and ground water as well as the sea ice - which, for the sake of simplicity, is considered herein to be part of the hydrosphere. The processes taking place in these domains are vastly different in nature and are characterized by a wide range of space- and time-scales. The components of the hydrosphere interact with each other. For instance, the shallow marine and estuarine regions, though accounting for less than 1% of the volume of the oceans, have a biomass far from negligible as compared to that of the oceans, implying that they play a significant role in global biogeochemical cycles. This is one of the reasons why models are now needed that deal with most, if not all, of the components of the hydrospheric system. Numerical models of each of the components of the hydrosphere already exist. However, an integrated model of the whole hydrosphere has yet to be developed. Building such a model is a daunting task, requiring the development of multi-scale/physics simulation tools. Numerical methods for dealing with multi-scale problems are developing rapidly. Unstructured meshes offer an almost infinite geometrical flexibility, allowing the space resolution to be increased when and where necessary. In addition, time steppings for dealing with a wide spectrum of timescales while retaining a high order of accuracy have been developed over recent years (e.g. multi-rate schemes). The Discontinuous Galerkin Finite Element (DGFE) framework SLIM is at his third implementation. It has been build on the GMSH code (http://geuz.org/gmsh), which a state-of-the-art open-source meshing tool. This allows the use of the same definitions and easy interactions between the mesher and the model. Moreover, this provides the same user interface for meshing and visualizing results. It also enables the use of the most recent advances in mesh generation, as GMSH has a
Solving the problem of imaging resolution: stochastic multi-scale image fusion
NASA Astrophysics Data System (ADS)
Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril
2016-04-01
Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil and rock microstructure X-ray microtomography is extremely useful. However, as any other imaging technique, this one also has a significant drawback - a trade-off between sample size and resolution. The latter is a significant problem for multi-scale complex structures, especially such as soils and carbonates. Other imaging techniques, for example, SEM/FIB-SEM or X-ray macrotomography can be helpful in obtaining higher resolution or wider field of view. The ultimate goal is to create a single dataset containing information from all scales or to characterize such multi-scale structure. In this contribution we demonstrate a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images representing macro, micro and nanoscale spatial information on porous media structure. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Potential practical applications of this method are abundant in soil science, hydrology and petroleum engineering, as well as other geosciences. This work was partially supported by RSF grant 14-17-00658 (X-ray microtomography study of shale
Symptoms of change in multi-scale observations of arctic ecosystem carbon cycling
NASA Astrophysics Data System (ADS)
Stoy, P. C.; Williams, M. D.; Hartley, I. P.; Street, L.; Hill, T. C.; Prieto-Blanco, A.; Wayolle, A.; Disney, M.; Evans, J.; Fletcher, B.; Poyatos, R.; Wookey, P.; Merbold, L.; Wade, T. J.; Moncrieff, J.
2009-12-01
Arctic ecosystems are responding rapidly to observed climate change. Quantifying the magnitude of these changes, and their implications for the climate system, requires observations of their current structure and function, as well as extrapolation and modelling (i.e. ‘upscaling’) across time and space. Here, we describe the major results of the International Polar Year (IPY) ABACUS project, a multi-scale investigation across arctic Fennoscandia that couples plant and soil process studies, isotope analyses, flux and micrometeorological measurements, process modelling, and aircraft and satellite observations to improve predictions of the response of the arctic terrestrial biosphere to global change. We begin with a synthesis of eddy covariance observations from the global FLUXNET database. We demonstrate that a simple model parameterized using pan-arctic chamber measurements explains over 80% of the variance of half-hourly CO2 fluxes during the growing season across most arctic and montane tundra ecosystems given accurate measurements of leaf area index (LAI), which agrees with the recently proposed ‘functional convergence’ paradigm for tundra vegetation. The ability of MODIS to deliver accurate LAI estimates is briefly discussed and an adjusted algorithm is presented and validated using direct observations. We argue for an Information Theory-based framework for upscaling in Earth science by conceptualizing multi-scale research as a transfer of information across scales. We then demonstrate how error in upscaled arctic C flux estimates can be reduced to less than 4% from their high-resolution counterpart by formally preserving the information content of high spatial and spectral resolution aircraft and satellite imagery. Jaynes’ classic Maximum Entropy (MaxEnt) principle is employed to incorporate logical, biological and physical constraints to reduce error in downscaled flux estimates. Errors are further reduced by assimilating flux, biological and remote
A multi-scale modelling procedure to quantify hydrological impacts of upland land management
NASA Astrophysics Data System (ADS)
Wheater, H. S.; Jackson, B.; Bulygina, N.; Ballard, C.; McIntyre, N.; Marshall, M.; Frogbrook, Z.; Solloway, I.; Reynolds, B.
2008-12-01
Recent UK floods have focused attention on the effects of agricultural intensification on flood risk. However, quantification of these effects raises important methodological issues. Catchment-scale data have proved inadequate to support analysis of impacts of land management change, due to climate variability, uncertainty in input and output data, spatial heterogeneity in land use and lack of data to quantify historical changes in management practices. Manipulation experiments to quantify the impacts of land management change have necessarily been limited and small scale, and in the UK mainly focused on the lowlands and arable agriculture. There is a need to develop methods to extrapolate from small scale observations to predict catchment-scale response, and to quantify impacts for upland areas. With assistance from a cooperative of Welsh farmers, a multi-scale experimental programme has been established at Pontbren, in mid-Wales, an area of intensive sheep production. The data have been used to support development of a multi-scale modelling methodology to assess impacts of agricultural intensification and the potential for mitigation of flood risk through land use management. Data are available from replicated experimental plots under different land management treatments, from instrumented field and hillslope sites, including tree shelter belts, and from first and second order catchments. Measurements include climate variables, soil water states and hydraulic properties at multiple depths and locations, tree interception, overland flow and drainflow, groundwater levels, and streamflow from multiple locations. Fine resolution physics-based models have been developed to represent soil and runoff processes, conditioned using experimental data. The detailed models are used to calibrate simpler 'meta- models' to represent individual hydrological elements, which are then combined in a semi-distributed catchment-scale model. The methodology is illustrated using field
multi-scale approaches for full waveform difference inversion and tomographic model analysis
NASA Astrophysics Data System (ADS)
Yuan, Y.; Simons, F. J.; Luo, Y.
2012-12-01
Tomographic Earth models are solutions to mixed-determined inverse problems, which are formulated to minimize some measure of difference between synthetics and observed data. Typically, the measurement takes the form of a cross-correlation travel-time difference, or it might be the norm of the difference between the entire waveforms, in which case every wiggle is being used to extract information from the data. Full-waveform difference tomography suffers from a slow convergence rate and a danger of converging to local minima. In this presentation, we explore several routes to improving full-waveform inversion strategies for global and regional seismic tomography. First, we will discuss a wavelet-based multi-scale approach that works progressively from low to higher scales, step-by-step involving more details of the waveform. Second, we will discuss a hybrid misfit strategy that combines cross-correlation traveltime and waveform-difference measurements. We will discuss the making of multiscale sensitivity kernels using wavelet decompositions of the seismogram. Lastly, we move to the model space to conduct a multi-scale analysis of global tomographic models using a class of 3-D spherical wavelet bases that are implemented on the ``cubed ball'', the 3-D extension of the ``cubed sphere''. Using this novel transform we study the sparsity of global seismic tomographic models via thresholded reconstruction, and characterize the relative importance and patterns of features in the Earth models via individual and cumulative reconstructions of their wavelet coefficients. Whether on the side of the data, the sensitivity kernels, or in the model space, tomographic inverse problems have much to gain from the flexibility of the wavelet decomposition in one, two and three dimensions, and this on a global, regional or exploration scale, as we show by example. Full waveform difference inversion. The first figure shows our target model with two anomalous regions. The red stars
A multi-scale approach to quantifying non-rainfall water inputs
NASA Astrophysics Data System (ADS)
Agam, Nurit; Florentin, Anat
2015-04-01
Non-rainfall water inputs (NRWIs) are a gain of water to the surface soil layer caused by sources other than rainfall, i.e., by fog deposition, dew formation, or water vapor adsorption. These water inputs usually evaporate the following morning, creating a diurnal cycle of water content in the uppermost soil layer, which involves exchange of latent-heat flux (LE) between the soil and the atmosphere. The significance of the formation and evaporation of NRWIs in drylands is largely acknowledged, yet understanding of the environmental conditions controlling its magnitude are still lacking, and its spatial extent was not studied before. A multi-scale approach to quantifying NWRIs and the corresponding diurnal water cycle in arid regions will be presented. The research has been conducted over a bare loess soil in the Negev desert (30o51'35.30" N, 34o46'40.97" E) during the dry season (May-September 2014). During this dry period, gain in soil water content is only a result of NRWIs. A micro-lysimeter (ML) with a 20 cm diameter and 50 cm depth filled with an undisturbed soil sample was placed on a scale buried in the soil such that the top end of the sample was level with the soil surface and the sample's mass was continuously monitored. The ML served as a point measurement to which larger-scale micrometeorological methods, i.e., eddy covariance (EC) flux tower (field scale, ~2X103 m2) and a surface layer scintillometer (field scale, ~8X103 m2). The ability to obtain spatially distributed NWRIs at the regional scale through mapping changes in land surface emissivity was tested as well. Preliminary results indicate that despite the acknowledged limitations in nighttime measurements, the EC LE followed closely the micro-lysimeter LE; and the sensible heat flux derived by the EC and the scintillometer were in good agreement; demonstrating the feasibility of measuring NRWIs with both methods. This innovative multi-scale approach sheds light on various aspects of the NRWI
Simulating Multi-Scale Mercury Fate and Transport in a Coastal Plain Watershed
NASA Astrophysics Data System (ADS)
Knightes, C. D.; Davis, G. M.; Golden, H. E.; Conrads, P. A.; Bradley, P. M.; Journey, C. A.
2012-12-01
Mercury is the toxicant responsible for the largest number of fish advisories across the United States, with 1.1 million river miles under advisory. The processes governing fate, transport, and transformation of mercury in streams and rivers are not well understood, in large part, because these systems are intimately linked with their surrounding watersheds and are often highly spatially variable. In this study, we applied a linked watershed hydrology and biogeochemical cycling (N, C, and Hg) model (VELMA, Visualizing Ecosystems for Land Management Assessment) to simulate daily flow, fluxes, and soil and stream concentrations of total mercury (THg) and methylmercury (MeHg) at multiple spatial scales in McTier Creek, a Coastal Plain watershed within the Edisto River basin of South Carolina, USA. Our goals were to (1) calibrate and simulate Hg fate and transport processes at a focused reach scale (0.1 km2) and (2) assess how representative the reach-scale parameters and processes are when multi-scale watershed information is included in Hg cycling simulations. Thus, reach-scale parameterization was applied to multi-scaled watersheds, including two headwater sub-watersheds (28 km2 and 25 km2) nested within the McTier Creek watershed (79 km2), to evaluate model performance and how well reach-scale parameterization and processes characterize nested watersheds with increasing drainage areas. The current VELMA simulations suggest that stream water column THg concentration predictions perform reasonably well at different scales based on reach-scale calibrations, but the model simulations of MeHg reach, sub-watershed, and watershed stream concentrations are out-of-phase with observed MeHg concentrations. This result suggests that processes governing MeHg loading to the main channel may be under-represented in the current model structure and underscores the complexity of simulating MeHg dynamics in watershed models. This work supports the importance of hydrology in
NASA Astrophysics Data System (ADS)
Abedi, S.; Mashhadian, M.; Noshadravan, A.
2015-12-01
Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the
Land-Atmosphere Coupling in the Multi-Scale Modelling Framework
NASA Astrophysics Data System (ADS)
Kraus, P. M.; Denning, S.
2015-12-01
The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced
Multi-scale functional mapping of tidal marsh vegetation for restoration monitoring
NASA Astrophysics Data System (ADS)
Tuxen Bettman, Karin
2007-12-01
Nearly half of the world's natural wetlands have been destroyed or degraded, and in recent years, there have been significant endeavors to restore wetland habitat throughout the world. Detailed mapping of restoring wetlands can offer valuable information about changes in vegetation and geomorphology, which can inform the restoration process and ultimately help to improve chances of restoration success. I studied six tidal marshes in the San Francisco Estuary, CA, US, between 2003 and 2004 in order to develop techniques for mapping tidal marshes at multiple scales by incorporating specific restoration objectives for improved longer term monitoring. I explored a "pixel-based" remote sensing image analysis method for mapping vegetation in restored and natural tidal marshes, describing the benefits and limitations of this type of approach (Chapter 2). I also performed a multi-scale analysis of vegetation pattern metrics for a recently restored tidal marsh in order to target the metrics that are consistent across scales and will be robust measures of marsh vegetation change (Chapter 3). Finally, I performed an "object-based" image analysis using the same remotely sensed imagery, which maps vegetation type and specific wetland functions at multiple scales (Chapter 4). The combined results of my work highlight important trends and management implications for monitoring wetland restoration using remote sensing, and will better enable restoration ecologists to use remote sensing for tidal marsh monitoring. Several findings important for tidal marsh restoration monitoring were made. Overall results showed that pixel-based methods are effective at quantifying landscape changes in composition and diversity in recently restored marshes, but are limited in their use for quantifying smaller, more fine-scale changes. While pattern metrics can highlight small but important changes in vegetation composition and configuration across years, scientists should exercise caution when
Madden-Julian oscillation and sea surface temperature interactions in a multi-scale framework
NASA Astrophysics Data System (ADS)
Zhou, Lei
2009-12-01
frequency shifts between oscillations with different scales and the atmospheric/oceanic responses to small variations in the external forcing are also tested with numerical models. Incorporating the oceanic influence on MJOs and the multi-scale interaction appropriately in a numerical model is supposed to help improve the simulation and forecast of MJOs. The hypothesis of multi-scale interaction is also expected to have wide applications in other studies, in addition to the MJO-SST interaction. The theoretical and numerical approach adopted here should also serve as a prototype for enhancing the process understanding of intraseasonal variability and lead to improved predictive understanding.
Banerjee, Sourav; Ahmed, Riaz
2013-06-01
A systematic framework for incubation of damage- state quantification in composites is almost absent in the current practice. Identification and quantification of the material state at its early stage has become significantly important in the field of structural health monitoring. Interaction between the intrinsic material state and ultrasonic wave signals, e.g., nonlinear ultrasonic, higher harmonic generation, etc., in metals are quite well known and well documented in the literature. However, it is extremely challenging to quantify the precursor to damage state in composite materials. Thus, in this paper, a comparatively simple but efficient novel approach is proposed to quantify the "incubation of damage" state using scanning acoustic microscopy. The proposed approach exploits the hybrid microcontinuum field theory to quantify the intrinsic (multi-scale) damage state. Defying the conventional route of bottom-up multi-scale modeling methods, a hybrid top-down approach is presented, which is then correlated to the ultrasonic signature obtained from the materials. A parameter to quantify incubation of damage at meso-scale has been identified in this paper. The intrinsic length-scale-dependent parameter called "damage entropy" closely resembles the material state resulting from fatigue, extreme environments, operational hazards or spatio-temporal variability, etc. The proposed quantification process involves a fusion between micromorphic physics and high-frequency ultrasonics in an unconventional way. The proposed approach is validated through an experimental study conducted on glass-fiber reinforced polymer composites which are mechanically fatigued. Specimens were characterized under a scanning acoustic microscope at 50 and 100 MHz. The imaging data and the sensor signals are characterized to quantify the incubation of damage state by the new parameter damage entropy. PMID:25004477
NASA Astrophysics Data System (ADS)
Wu, Z.; Jiang, C.; Ma, T.
2012-12-01
Earthquake hazard and risk in the Chinese mainland exhibit multi-scale characteristics. Temporal scales from centuries to months, spatial scales from the whole mainland to specific engineering structures, and energy scales from great disastrous earthquakes to small earthquakes causing social disturbance and economic loss, feature the complexity of earthquake disasters. Coping with such complex challenge, several research and application projects have been undertaken since recent years. Lessons and experiences of the 2008 Wenchuan earthquake contributed much to the launching and conducting of these projects. Understandings of the scientific problems and technical approaches taken in the mainstream studies in the Chinese mainland have no significant difference from those in the international scientific communities, albeit using of some of the terminologies have "cultural differences" - for instance, in the China Earthquake Administration (CEA), the terminology "earthquake forecast/prediction (study)" is generally used in a much broader sense, mainly indicating time-dependent seismic hazard at different spatio-temporal scales. Several scientific products have been produced serving the society in different forms. These scientific products have unique academic merits due to the long-term persistence feature and the forward forecast nature, which are all essential for the evaluation of the technical performance and the falsification of the scientific ideas. On the other hand, using the language of the "actor network theory (ANT)" in science studies (or the sociology of science), at present, the hierarchical "actors' network", making the science transformed to the actions of the public and government for the preparedness, mitigation, and management of multi-scale earthquake disasters, is still in need of careful construction and improvement.
A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images
Maxwell, S.K.; Schmidt, G.L.; Storey, J.C.
2007-01-01
On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.
NASA Technical Reports Server (NTRS)
Cornell, Stephen R.; Leser, William P.; Hochhalter, Jacob D.; Newman, John A.; Hartl, Darren J.
2014-01-01
A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.
Integrating multi-scale data to create a virtual physiological mouse heart.
Land, Sander; Niederer, Steven A; Louch, William E; Sejersted, Ole M; Smith, Nicolas P
2013-04-01
While the virtual physiological human (VPH) project has made great advances in human modelling, many of the tools and insights developed as part of this initiative are also applicable for facilitating mechanistic understanding of the physiology of a range of other species. This process, in turn, has the potential to provide human relevant insights via a different scientific path. Specifically, the increasing use of mice in experimental research, not yet fully complemented by a similar increase in computational modelling, is currently missing an important opportunity for using and interpreting this growing body of experimental data to improve our understanding of cardiac function. This overview describes our work to address this issue by creating a virtual physiological mouse model of the heart. We describe the similarities between human- and mouse-focused modelling, including the reuse of VPH tools, and the development of methods for investigating parameter sensitivity that are applicable across species. We show how previous results using this approach have already provided important biological insights, and how these can also be used to advance VPH heart models. Finally, we show an example application of this approach to test competing multi-scale hypotheses by investigating variations in length-dependent properties of cardiac muscle. PMID:24427525
Benchtop fabrication of multi-scale micro-electromagnets for capturing magnetic particles
NASA Astrophysics Data System (ADS)
Hosseini, A.; Soleymani, L.
2014-08-01
Micro-electromagnets hold great promise for integration into portable and handheld lab-on-a- chip systems applicable to point-of-care disease management. Two major requirements must be satisfied in order for such devices to be applicable into practical, miniaturized, and portable biomedical instrumentation: low power operation and low-cost fabrication. In this paper, we use numerical modeling combined with a lithography-free fabrication process to create micro-electromagnets on a polymer substrate. Numerical modeling reveals that active-passive devices—ferromagnetic layers coupled with current-controlled planar coils—are essential for generating a sufficient magnetic force for magnetic particle manipulation at low currents (<50 mA). In addition, it is shown that current carrying conductors created from micro/nanotextured materials further enhance the generated magnetic force at a given current. To combine low-cost fabrication with low-current operation, we developed a benchtop fabrication method based on craft cutting, polymer induced thin film wrinkling, and electrodeposition to create a multilevel arrangement of multi-scale materials essential for low-current operation. We demonstrate that the fabricated active-passive devices featuring wrinkled copper active layers and permalloy passive layers capture 2.8 μm magnetic particles upon the application of a 35 mA current.
Multi-scale finite element modeling allows the mechanics of amphibian neurulation to be elucidated
NASA Astrophysics Data System (ADS)
Chen, Xiaoguang; Brodland, G. Wayne
2008-03-01
The novel multi-scale computational approach introduced here makes possible a new means for testing hypotheses about the forces that drive specific morphogenetic movements. A 3D model based on this approach is used to investigate neurulation in the axolotl (Ambystoma mexicanum), a type of amphibian. The model is based on geometric data from 3D surface reconstructions of live embryos and from serial sections. Tissue properties are described by a system of cell-based constitutive equations, and parameters in the equations are determined from physical tests. The model includes the effects of Shroom-activated neural ridge reshaping and lamellipodium-driven convergent extension. A typical whole-embryo model consists of 10 239 elements and to run its 100 incremental time steps requires 2 days. The model shows that a normal phenotype does not result if lamellipodium forces are uniform across the width of the neural plate; but it can result if the lamellipodium forces decrease from a maximum value at the mid-sagittal plane to zero at the plate edge. Even the seemingly simple motions of neurulation are found to contain important features that would remain hidden, they were not studied using an advanced computational model. The present model operates in a setting where data are extremely sparse and an important outcome of the study is a better understanding of the role of computational models in such environments.
Automated parameterisation for multi-scale image segmentation on multiple layers
NASA Astrophysics Data System (ADS)
Drăguţ, L.; Csillik, O.; Eisank, C.; Tiede, D.
2014-02-01
We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and segments them iteratively with a multiresolution segmentation algorithm in a bottom-up approach, where the scale factor in the segmentation, namely, the scale parameter (SP), increases with a constant increment. The average LV value of the objects in all of the layers is computed and serves as a condition for stopping the iterations: when a scale level records an LV value that is equal to or lower than the previous value, the iteration ends, and the objects segmented in the previous level are retained. Three orders of magnitude of SP lags produce a corresponding number of scale levels. Tests on very high resolution imagery provided satisfactory results for generic applicability. The tool has a significant potential for enabling objectivity and automation of GEOBIA analysis.
Automated parameterisation for multi-scale image segmentation on multiple layers.
Drăguţ, L; Csillik, O; Eisank, C; Tiede, D
2014-02-01
We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and segments them iteratively with a multiresolution segmentation algorithm in a bottom-up approach, where the scale factor in the segmentation, namely, the scale parameter (SP), increases with a constant increment. The average LV value of the objects in all of the layers is computed and serves as a condition for stopping the iterations: when a scale level records an LV value that is equal to or lower than the previous value, the iteration ends, and the objects segmented in the previous level are retained. Three orders of magnitude of SP lags produce a corresponding number of scale levels. Tests on very high resolution imagery provided satisfactory results for generic applicability. The tool has a significant potential for enabling objectivity and automation of GEOBIA analysis. PMID:24748723
Multi-scale and Multi-modal Analysis of Metamorphic Rocks Coupling Fluorescence and TXM Techniques
NASA Astrophysics Data System (ADS)
De Andrade, V. J. D.; Gursoy, D.; Wojcik, M.; DeCarlo, F.; Ganne, J.; Dubacq, B.
2014-12-01
Rocks are commonly polycrystalline systems presenting multi-scale chemical and structural heterogeneities inherited from crystallization processes or successive metamorphic events. Through different applications on metamorphic rocks involving fluorescence microprobes and full-field spectroscopy, one will illustrate how spatially resolved analytical techniques allow rock compositional variations to be related to large-scale geodynamic processes. Those examples also stress the importance of multi-modality instruments with zoom-in capability to study samples from mm to several μm large fields of view, with micrometer down to sub-100 nanometer spatial resolutions. In this perspective, imaging capabilities offered by the new ultra-bright diffraction limited synchrotron sources will be described based on experimental data. At last, the new hard X-ray Transmission X-ray Microscope (TXM) at Sector 32 of the APS at Argonne National Laboratory, performing nano computed tomography with in situ capabilities will be presented. The instrument benefit from several R&D key activities like the fabrication of new zone plates in the framework of the Multi-Bend Achromat Lattice (MBA) upgrade at APS, or the development of powerful tomography reconstruction algorithms able to operate with a limited number of projections.
Fast multi-scale edge detection algorithm based on wavelet transform
NASA Astrophysics Data System (ADS)
Zang, Jie; Song, Yanjun; Li, Shaojuan; Luo, Guoyun
2011-11-01
The traditional edge detection algorithms have certain noise amplificat ion, making there is a big error, so the edge detection ability is limited. In analysis of the low-frequency signal of image, wavelet analysis theory can reduce the time resolution; under high time resolution for high-frequency signal of the image, it can be concerned about the transient characteristics of the signal to reduce the frequency resolution. Because of the self-adaptive for signal, the wavelet transform can ext ract useful informat ion from the edge of an image. The wavelet transform is at various scales, wavelet transform of each scale provides certain edge informat ion, so called mult i-scale edge detection. Multi-scale edge detection is that the original signal is first polished at different scales, and then detects the mutation of the original signal by the first or second derivative of the polished signal, and the mutations are edges. The edge detection is equivalent to signal detection in different frequency bands after wavelet decomposition. This article is use of this algorithm which takes into account both details and profile of image to detect the mutation of the signal at different scales, provided necessary edge information for image analysis, target recognition and machine visual, and achieved good results.
Boundary conditions between poro-elastic medium and pure fluid in multi-scale modelling
NASA Astrophysics Data System (ADS)
Lacis, Ugis; Bagheri, Shervin
2015-11-01
Accurate modelling of porous and poro-elastic media has been a long standing issue in geophysics, fluid mechanics, and biology. There has been a notable development of continuous models for both porous and poro-elastic materials, nevertheless there is still an on-going debate about the modelling of effective boundary conditions between different types of media, such as, poro-elastic medium and free fluid, porous medium and solid wall. Some recent works have rigorously treated interface between porous medium and free fluid, however, there have been no detailed investigation regarding the interface between poro-elastic medium and free fluid. We use the multi-scale modelling to arrive with averaged, effective macroscopic equations for description of a poro-elastic medium. Then we investigate the interface in detail and arrive with effective boundary conditions. To validate our model, we construct direct numerical simulations using an immersed boundary (IB) method. The IB method is beforehand validated with respect to theoretical predictions for Darcy's flow in porous materials with a given pore structure.
Multi-scale modelling of cancer cell intravasation: the role of cadherins in metastasis
NASA Astrophysics Data System (ADS)
Ramis-Conde, Ignacio; Chaplain, Mark A. J.; Anderson, Alexander R. A.; Drasdo, Dirk
2009-03-01
Transendothelial migration is a crucial process of the metastatic cascade in which a malignant cell attaches itself to the endothelial layer forming the inner wall of a blood or lymph vessel and creates a gap through which it enters into the bloodstream (or lymphatic system) and then is transported to distant parts of the body. In this process both biological pathways involving cell adhesion molecules such as VE-cadherin and N-cadherin, and the biophysical properties of the cells play an important role. In this paper, we present one of the first mathematical models considering the problem of cancer cell intravasation. We use an individual force-based multi-scale approach which accounts for intra- and inter-cellular protein pathways and for the physical properties of the cells, and a modelling framework which accounts for the biological shape of the vessel. Using our model, we study the influence of different protein pathways in the achievement of transendothelial migration and give quantitative simulation results comparable with real experiments.
Nest fidelity is driven by multi-scale information in a long-lived seabird.
Robert, Alexandre; Paiva, Vítor H; Bolton, Mark; Jiguet, Frédéric; Bried, Joël
2014-10-22
Although the reproductive success of most organisms depends on factors acting at several spatial scales, little is known about how organisms are able to synthesize multi-scale information to optimize reproduction. Using longitudinal data from a long-lived seabird, Monteiro's storm-petrel, we show that average breeding success is strongly related to oceanic conditions at the population level, and we postulate that (i) individuals use proximal information (their own reproduction outcome in year t) to assess the qualities of their mate and nest and to decide to retain them or not in year t + 1; (ii) the intensity of these responses depends on the quality of the oceanic environment in year t, which affects the predictability of reproduction outcome in year t + 1. Our results confirm that mate and nest fidelities are higher following successful reproduction and that the relationship between the success of a given pair and subsequent nest fidelity is stronger in years with unfavourable oceanic conditions, suggesting that individuals rely on distant information to modulate their use of proximal information and adjust their breeding strategy. PMID:25209940
NASA Astrophysics Data System (ADS)
Lasa, Ane; Safi, Elnaz; Nordlund, Kai
2015-11-01
Recent experiments and Molecular Dynamics (MD) simulations show erosion rates of Be exposed to deuterium (D) plasma varying with surface temperature and the correlated D concentration. Little is understood how these three parameters relate for Be surfaces, despite being essential for reliable prediction of impurity transport and plasma facing material lifetime in current (JET) and future (ITER) devices. A multi-scale exercise is presented here to relate Be surface temperatures, concentrations and sputtering yields. Kinetic Monte Carlo (MC) code MMonCa is used to estimate equilibrium D concentrations in Be at different temperatures. Then, mixed Be-D surfaces - that correspond to the KMC profiles - are generated in MD, to calculate Be-D molecular erosion yields due to D irradiation. With this new database implemented in the 3D MC impurity transport code ERO, modeling scenarios studying wall erosion, such as RF-induced enhanced limiter erosion or main wall surface temperature scans run at JET, can be revisited with higher confidence. Work supported by U.S. DOE under Contract DE-AC05-00OR22725.
Kirsch, Joseph; Peterson, James T.
2014-01-01
There is considerable uncertainty about the relative roles of stream habitat and landscape characteristics in structuring stream-fish assemblages. We evaluated the relative importance of environmental characteristics on fish occupancy at the local and landscape scales within the upper Little Tennessee River basin of Georgia and North Carolina. Fishes were sampled using a quadrat sample design at 525 channel units within 48 study reaches during two consecutive years. We evaluated species–habitat relationships (local and landscape factors) by developing hierarchical, multispecies occupancy models. Modeling results suggested that fish occupancy within the Little Tennessee River basin was primarily influenced by stream topology and topography, urban land coverage, and channel unit types. Landscape scale factors (e.g., urban land coverage and elevation) largely controlled the fish assemblage structure at a stream-reach level, and local-scale factors (i.e., channel unit types) influenced fish distribution within stream reaches. Our study demonstrates the utility of a multi-scaled approach and the need to account for hierarchy and the interscale interactions of factors influencing assemblage structure prior to monitoring fish assemblages, developing biological management plans, or allocating management resources throughout a stream system.
Advanced computations of multi-physics, multi-scale effects in beam dynamics
Amundson, J.F.; Macridin, A.; Spentzouris, P.; Stern, E.G.; /Fermilab
2009-01-01
Current state-of-the-art beam dynamics simulations include multiple physical effects and multiple physical length and/or time scales. We present recent developments in Synergia2, an accelerator modeling framework designed for multi-physics, multi-scale simulations. We summarize recent several recent results in multi-physics beam dynamics, including simulations of three Fermilab accelerators: the Tevatron, the Main Injector and the Debuncher. Early accelerator simulations focused on single-particle dynamics. To a first approximation, the forces on the particles in an accelerator beam are dominated by the external fields due to magnets, RF cavities, etc., so the single-particle dynamics are the leading physical effects. Detailed simulations of accelerators must include collective effects such as the space-charge repulsion of the beam particles, the effects of wake fields in the beam pipe walls and beam-beam interactions in colliders. These simulations require the sort of massively parallel computers that have only become available in recent times. We give an overview of the accelerator framework Synergia2, which was designed to take advantage of the capabilities of modern computational resources and enable simulations of multiple physical effects. We also summarize some recent results utilizing Synergia2 and BeamBeam3d, a tool specialized for beam-beam simulations.
A multi scale multi-dimensional thermo electrochemical modelling of high capacity lithium-ion cells
NASA Astrophysics Data System (ADS)
Tourani, Abbas; White, Peter; Ivey, Paul
2014-06-01
Lithium iron phosphate (LFP) and lithium manganese oxide (LMO) are competitive and complementary to each other as cathode materials for lithium-ion batteries, especially for use in electric vehicles. A multi scale multi-dimensional physic-based model is proposed in this paper to study the thermal behaviour of the two lithium-ion chemistries. The model consists of two sub models, a one dimensional (1D) electrochemical sub model and a two dimensional (2D) thermo-electric sub model, which are coupled and solved concurrently. The 1D model predicts the heat generation rate (Qh) and voltage (V) of the battery cell through different load cycles. The 2D model of the battery cell accounts for temperature distribution and current distribution across the surface of the battery cell. The two cells are examined experimentally through 90 h load cycles including high/low charge/discharge rates. The experimental results are compared with the model results and they are in good agreement. The presented results in this paper verify the cells temperature behaviour at different operating conditions which will lead to the design of a cost effective thermal management system for the battery pack.
Circadian clock and cardiac vulnerability: A time stamp on multi-scale neuroautonomic regulation
NASA Astrophysics Data System (ADS)
Ivanov, Plamen Ch.
2005-03-01
Cardiovascular vulnerability displays a 24-hour pattern with a peak between 9AM and 11AM. This daily pattern in cardiac risk is traditionally attributed to external factors including activity levels and sleep-wake cycles. However,influences from the endogenous circadian pacemaker independent from behaviors may also affect cardiac control. We investigate heartbeat dynamics in healthy subjects recorded throughout a 10-day protocol wherein the sleep/wake and behavior cycles are desynchronized from the endogenous circadian cycle,enabling assessment of circadian factors while controlling for behavior-related factors. We demonstrate that the scaling exponent characterizing temporal correlations in heartbeat dynamics over multiple time scales does exhibit a significant circadian rhythm with a sharp peak at the circadian phase corresponding to the period 9-11AM, and that this rhythm is independent from scheduled behaviors and mean heart rate. Our findings of strong circadian rhythms in the multi-scale heartbeat dynamics of healthy young subjects indicate that the underlying mechanism of cardiac regulation is strongly influenced by the endogenous circadian pacemaker. A similar circadian effect in vulnerable individuals with underlying cardiovascular disease would contribute to the morning peak of adverse cardiac events observed in epidemiological studies.
Synergy of multi-scale toughening and protective mechanisms at hierarchical branch-stem interfaces
Müller, Ulrich; Gindl-Altmutter, Wolfgang; Konnerth, Johannes; Maier, Günther A.; Keckes, Jozef
2015-01-01
Biological materials possess a variety of artful interfaces whose size and properties are adapted to their hierarchical levels and functional requirements. Bone, nacre, and wood exhibit an impressive fracture resistance based mainly on small crystallite size, interface organic adhesives and hierarchical microstructure. Currently, little is known about mechanical concepts in macroscopic biological interfaces like the branch-stem junction with estimated 1014 instances on earth and sizes up to few meters. Here we demonstrate that the crack growth in the upper region of the branch-stem interface of conifer trees proceeds along a narrow predefined region of transversally loaded tracheids, denoted as sacrificial tissue, which fail upon critical bending moments on the branch. The specific arrangement of the tracheids allows disconnecting the overloaded branch from the stem in a controlled way by maintaining the stem integrity. The interface microstructure based on the sharply adjusted cell orientation and cell helical angle secures a zig-zag crack propagation path, mechanical interlock closing after the bending moment is removed, crack gap bridging and self-repairing by resin deposition. The multi-scale synergetic concepts allows for a controllable crack growth between stiff stem and flexible branch, as well as mechanical tree integrity, intact physiological functions and recovery after the cracking. PMID:26415835
A New Multi-Scale Flow Network Generation Scheme for Land Surface Models
Guo, Jianzhong; Liang, Xu; Leung, Lai-Yung R.
2004-12-11
This paper presents a new approach of generating flow networks for land surface models that are applied at different spatial scales based on a fine-resolution digital elevation model (DEM). Without losing computational efficiency, the new multi-scale approach has the advantages that (1) it allows surface and subsurface runoff in a land surface model grid to exit through multiple directions simultaneously rather than through only one of the eight directions as in many other methods; and (2) it introduces the concept of elastic coefficient to determine hydrological features, such as river slope and length for more accurate flow routing across different spatial scales. The new flow network generation scheme has been applied to the Blue River watershed in Oklahoma at different spatial resolutions used in conjunction with a kinematic wave routing method. Comparisons of the routed streamflows at the watershed outlet show clear advantages of the new approach over the widely used eight directions (D8) method, especially at coarser spatial resolution. This method is particularly suitable for macroscale hydrologic models and climate models where the accuracy of river routing can be severely limited by the coarse spatial resolution.
CHEMDNER system with mixed conditional random fields and multi-scale word clustering
2015-01-01
Background The chemical compound and drug name recognition plays an important role in chemical text mining, and it is the basis for automatic relation extraction and event identification in chemical information processing. So a high-performance named entity recognition system for chemical compound and drug names is necessary. Methods We developed a CHEMDNER system based on mixed conditional random fields (CRF) with word clustering for chemical compound and drug name recognition. For the word clustering, we used Brown's hierarchical algorithm and Skip-gram model based on deep learning with massive PubMed articles including titles and abstracts. Results This system achieved the highest F-score of 88.20% for the CDI task and the second highest F-score of 87.11% for the CEM task in BioCreative IV. The performance was further improved by multi-scale clustering based on deep learning, achieving the F-score of 88.71% for CDI and 88.06% for CEM. Conclusions The mixed CRF model represents both the internal complexity and external contexts of the entities, and the model is integrated with word clustering to capture domain knowledge with PubMed articles including titles and abstracts. The domain knowledge helps to ensure the performance of the entity recognition, even without fine-grained linguistic features and manually designed rules. PMID:25810775
Monniaux, Danielle; Michel, Philippe; Postel, Marie; Clément, Frédérique
2016-06-01
In this review, we present multi-scale mathematical models of ovarian follicular development that are based on the embedding of physiological mechanisms into the cell scale. During basal follicular development, follicular growth operates through an increase in the oocyte size concomitant with the proliferation of its surrounding granulosa cells. We have developed a spatio-temporal model of follicular morphogenesis explaining how the interactions between the oocyte and granulosa cells need to be properly balanced to shape the follicle. During terminal follicular development, the ovulatory follicle is selected amongst a cohort of simultaneously growing follicles. To address this process of follicle selection, we have developed a model giving a continuous and deterministic description of follicle development, adapted to high numbers of cells and based on the dynamical and hormonally regulated repartition of granulosa cells into different cell states, namely proliferation, differentiation and apoptosis. This model takes into account the hormonal feedback loop involving the growing ovarian follicles and the pituitary gland, and enables the exploration of mechanisms regulating the number of ovulations at each ovarian cycle. Both models are useful for addressing ovarian physio-pathological situations. Moreover, they can be proposed as generic modelling environments to study various developmental processes and cell interaction mechanisms. PMID:26856895
A Multi-scale Modeling System: Developments, Applications and Critical Issues
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Chern, Jiundar; Atlas, Robert; Randall, David; Lin, Xin; Khairoutdinov, Marat; Li, Jui-Lin; Waliser, Duane E.; Hou, Arthur; Peters-Lidard, Christa; Lau, William; Simpson, Joanne
2006-01-01
A multi-scale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The GCM allows global coverage and the CRM allows explicit simulation of cloud processes and their interactions with radiation and surface processes. A new MMF has been developed that is based the Goddard finite volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved .surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger, propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using conventional cloud parameterizations. Both MMFs also produce a precipitation bias in the western Pacific during Northern Hemisphere summer. However, there are also notable differences between two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF overestimates global rainfall because of its oceanic component. Some critical issues associated with the Goddard MMF are presented in this paper.
NASA Astrophysics Data System (ADS)
Qian, Fang; Guo, Jin; Sun, Tao; Wang, Tingfeng
2015-04-01
Laser active imaging systems are widespread tools used in region surveillance and threat identification. However, the photoelectric imaging detector in the imaging systems is easy to be disturbed and this leads to errors of the recognition and even the missing of the target. In this paper, a novel wavelet-weighted multi-scale structural similarity (WWMS-SSIM) algorithm is proposed. 2-D four-level wavelet decomposition is performed for the original and disturbed images. Each image can be partitioned into one low-frequency subband (LL) and a series of octave high-frequency subbands (HL, LH and HH). Luminance, contrast and structure comparison are computed in different subbands with different weighting factors. Based on the results of the above, we can construct a modified WWMS-SSIM. Cross-distorted image quality assessment experiments show that the WWMS-SSIM algorithm is more suitable for the subjective visual feeling comparing with NMSE and SSIM. In the laser-dazzling image quality assessment experiments, the WWMS-SSIM gives more reasonable evaluations to the images with different power and laser spot positions, which can be useful to give the guidance of the laser active imaging system defense and application.
Multi-scale deep networks and regression forests for direct bi-ventricular volume estimation.
Zhen, Xiantong; Wang, Zhijie; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo
2016-05-01
Direct estimation of cardiac ventricular volumes has become increasingly popular and important in cardiac function analysis due to its effectiveness and efficiency by avoiding an intermediate segmentation step. However, existing methods rely on either intensive user inputs or problematic assumptions. To realize the full capacities of direct estimation, this paper presents a general, fully learning-based framework for direct bi-ventricular volume estimation, which removes user inputs and unreliable assumptions. We formulate bi-ventricular volume estimation as a general regression framework which consists of two main full learning stages: unsupervised cardiac image representation learning by multi-scale deep networks and direct bi-ventricular volume estimation by random forests. By leveraging strengths of generative and discriminant learning, the proposed method produces high correlations of around 0.92 with ground truth by human experts for both the left and right ventricles using a leave-one-subject-out cross validation, and largely outperforms existing direct methods on a larger dataset of 100 subjects including both healthy and diseased cases with twice the number of subjects used in previous methods. More importantly, the proposed method can not only be practically used in clinical cardiac function analysis but also be easily extended to other organ volume estimation tasks. PMID:26919699
NASA Astrophysics Data System (ADS)
Brüggemann, Matthias; Kays, Rüdiger; Springer, Paul; Erdler, Oliver
2015-03-01
In this paper we present a combination of block-matching and differential motion field estimation. We initialize the motion field using a predictive hierarchical block-matching approach. This vector field is refined by a pixel-recursive differential motion estimation method. We integrate image warping and adaptive filter kernels into the Horn and Schunck differential optical flow estimation approach to break the block structure of the initial correspondence vector fields and compute motion field updates to fulfill the smoothness constraint inside motion boundaries. The influence of occlusion areas is reduced by integrating an in-the-loop occlusion detection and adjusting the adaptive filter weights in the iteration process. We integrate the combined estimation into a hierarchical multi-scale framework. The refined motion on the current scale is upscaled and used as prediction for block-matching motion estimation on the next scale. With the proposed system we are able to combine the advantages of block-matching and differential motion estimation and achieve a dense vector field with floating point precision even for large motion.
NASA Astrophysics Data System (ADS)
Howard, N. T.; Holland, C.; White, A. E.; Greenwald, M.; Candy, J.; Creely, A. J.
2016-05-01
To better understand the role of cross-scale coupling in experimental conditions, a series of multi-scale gyrokinetic simulations were performed on Alcator C-Mod, L-mode plasmas. These simulations, performed using all experimental inputs and realistic ion to electron mass ratio ((mi/me)1/2 = 60.0), simultaneously capture turbulence at the ion ( kθρs˜O (1.0 ) ) and electron-scales ( kθρe˜O (1.0 ) ). Direct comparison with experimental heat fluxes and electron profile stiffness indicates that Electron Temperature Gradient (ETG) streamers and strong cross-scale turbulence coupling likely exist in both of the experimental conditions studied. The coupling between ion and electron-scales exists in the form of energy cascades, modification of zonal flow dynamics, and the effective shearing of ETG turbulence by long wavelength, Ion Temperature Gradient (ITG) turbulence. The tightly coupled nature of ITG and ETG turbulence in these realistic plasma conditions is shown to have significant implications for the interpretation of experimental transport and fluctuations. Initial attempts are made to develop a "rule of thumb" based on linear physics, to help predict when cross-scale coupling plays an important role and to inform future modeling of experimental discharges. The details of the simulations, comparisons with experimental measurements, and implications for both modeling and experimental interpretation are discussed.
Multi-scale Analysis of MEMS Sensors Subject to Drop Impacts
Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah
2007-01-01
The effect of accidental drops on MEMS sensors are examined within the framework of a multi-scale finite element approach. With specific reference to a polysilicon MEMS accelerometer supported by a naked die, the analysis is decoupled into macro-scale (at die length-scale) and meso-scale (at MEMS length-scale) simulations, accounting for the very small inertial contribution of the sensor to the overall dynamics of the device. Macro-scale analyses are adopted to get insights into the link between shock waves caused by the impact against a target surface and propagating inside the die, and the displacement/acceleration histories at the MEMS anchor points. Meso-scale analyses are adopted to detect the most stressed details of the sensor and to assess whether the impact can lead to possible localized failures. Numerical results show that the acceleration at sensor anchors cannot be considered an objective indicator for drop severity. Instead, accurate analyses at sensor level are necessary to establish how MEMS can fail because of drops.
Plasmonic lithography for fabricating nanoimprint masters with multi-scale patterns
NASA Astrophysics Data System (ADS)
Jung, Howon; Kim, Seok; Han, Dandan; Jang, Jinhee; Oh, Seonghyeon; Choi, Jun-Hyuk; Lee, Eung-Sug; Hahn, Jae W.
2015-05-01
We successfully demonstrate the practical application of plasmonic lithography to fabricate nanoimprint masters. Using the properties of a non-propagating near-field, we achieve high-speed multi-scale patterning with different exposure time during the scanning. We modulate the width of the line patterns using a pulse light source with different duty cycles during the scanning of the probe. For practical application in plasmonic lithography, we apply a deep reactive ion etching process to transfer an arbitrary fluidic channel into a silicon substrate and fabricate a high-aspect-ratio imprint master. Subsequently, we carry out the imprint process to replicate the fluidic channel with an aspect ratio of 7.2. For pattern width below 100 nm, we adopt a three-layer structure of photoresist, hard layer, and polymer to record the near field and form a hard mask and transfer mask. Using the multilayer structure, we fabricate high-resolution nanoimprint masters in a silicon substrate with an aspect ratio greater than 1.
Multi-scale simulation of plant tissue deformation using a model for individual cell mechanics.
Ghysels, P; Samaey, G; Tijskens, B; Van Liedekerke, P; Ramon, H; Roose, D
2009-01-01
We present a micro-macro method for the simulation of large elastic deformations of plant tissue. At the microscopic level, we use a mass-spring model to describe the geometrical structure and basic properties of individual plant cells. The macroscopic domain is discretized using standard finite elements, in which the macroscopic material properties (the stress-strain relation) are not given in analytical form, but are computed using the microscopic model in small subdomains, called representative volume elements (RVEs), centered around the macroscopic quadrature points. The boundary conditions for these RVEs are derived from the macroscopic deformation gradient. The computation of the macroscopic stress tensor is based on the definition of virial stress, as defined in molecular dynamics. The anisotropic Eulerian elasticity tensor is estimated using a forward finite difference approximation for the Truesdell rate of the Cauchy stress tensor. We investigate the influence of the size of the RVE and the boundary conditions. This multi-scale method converges to the solution of the full microscopic simulation, for both globally and adaptively refined finite element meshes, and achieves a significant speedup compared to the full microscopic simulation. PMID:19321921
Nest fidelity is driven by multi-scale information in a long-lived seabird
Robert, Alexandre; Paiva, Vítor H.; Bolton, Mark; Jiguet, Frédéric; Bried, Joël
2014-01-01
Although the reproductive success of most organisms depends on factors acting at several spatial scales, little is known about how organisms are able to synthesize multi-scale information to optimize reproduction. Using longitudinal data from a long-lived seabird, Monteiro's storm-petrel, we show that average breeding success is strongly related to oceanic conditions at the population level, and we postulate that (i) individuals use proximal information (their own reproduction outcome in year t) to assess the qualities of their mate and nest and to decide to retain them or not in year t + 1; (ii) the intensity of these responses depends on the quality of the oceanic environment in year t, which affects the predictability of reproduction outcome in year t + 1. Our results confirm that mate and nest fidelities are higher following successful reproduction and that the relationship between the success of a given pair and subsequent nest fidelity is stronger in years with unfavourable oceanic conditions, suggesting that individuals rely on distant information to modulate their use of proximal information and adjust their breeding strategy. PMID:25209940
Automated parameterisation for multi-scale image segmentation on multiple layers
Drăguţ, L.; Csillik, O.; Eisank, C.; Tiede, D.
2014-01-01
We introduce a new automated approach to parameterising multi-scale image segmentation of multiple layers, and we implemented it as a generic tool for the eCognition® software. This approach relies on the potential of the local variance (LV) to detect scale transitions in geospatial data. The tool detects the number of layers added to a project and segments them iteratively with a multiresolution segmentation algorithm in a bottom-up approach, where the scale factor in the segmentation, namely, the scale parameter (SP), increases with a constant increment. The average LV value of the objects in all of the layers is computed and serves as a condition for stopping the iterations: when a scale level records an LV value that is equal to or lower than the previous value, the iteration ends, and the objects segmented in the previous level are retained. Three orders of magnitude of SP lags produce a corresponding number of scale levels. Tests on very high resolution imagery provided satisfactory results for generic applicability. The tool has a significant potential for enabling objectivity and automation of GEOBIA analysis. PMID:24748723
New multi-scale perspectives on the stromatolites of Shark Bay, Western Australia
Suosaari, E. P.; Reid, R. P.; Playford, P. E.; Foster, J. S.; Stolz, J. F.; Casaburi, G.; Hagan, P. D.; Chirayath, V.; Macintyre, I. G.; Planavsky, N. J.; Eberli, G. P.
2016-01-01
A recent field-intensive program in Shark Bay, Western Australia provides new multi-scale perspectives on the world’s most extensive modern stromatolite system. Mapping revealed a unique geographic distribution of morphologically distinct stromatolite structures, many of them previously undocumented. These distinctive structures combined with characteristic shelf physiography define eight ‘Stromatolite Provinces’. Morphological and molecular studies of microbial mat composition resulted in a revised growth model where coccoid cyanobacteria predominate in mat communities forming lithified discrete stromatolite buildups. This contradicts traditional views that stromatolites with the best lamination in Hamelin Pool are formed by filamentous cyanobacterial mats. Finally, analysis of internal fabrics of stromatolites revealed pervasive precipitation of microcrystalline carbonate (i.e. micrite) in microbial mats forming framework and cement that may be analogous to the micritic microstructures typical of Precambrian stromatolites. These discoveries represent fundamental advances in our knowledge of the Shark Bay microbial system, laying a foundation for detailed studies of stromatolite morphogenesis that will advance our understanding of benthic ecosystems on the early Earth. PMID:26838605
Multi-scale Science: Supporting Emerging Practice with Semantically Derived Provenance
Myers, James D.; Pancerella, Carmen M.; Lansing, Carina S.; Schuchardt, Karen L.; Didier, Brett T.; Ashish, N., Goble, C
2003-10-20
Scientific progress is becoming increasingly dependent of our ability to study phenomena at multiple scales and from multiple perspectives. The ability to recontextualize third party data within the semantic and syntactic framework of a given research project is increasingly seen as a primary barrier in multi-scale science. Within the Collaboratory for Multiscale Chemical Science (CMCS) project, we are developing a general-purpose informatics-based approach that emphasizes ''on-demand'' metadata creation, configurable data translations, and semantic mapping to support the rapidly increasing and continually evolving requirements for managing data, metadata, and data relationships in such projects. A concrete example of this approach is the design of the CMCS provenance subsystem. The concept of provenance varies across communities, and multiple independent applications contribute to and use provenance. In CMCS, we have developed generic tools for viewing provenance relationships and for using them to, for example, scope notifications and searches. These tools rely on a configurable concept of provenance defined in terms of other relationships. The result is a very flexible mechanism capable of tracking data provenance across many disciplines and supporting multiple uses of provenance information.
Multi-time multi-scale correlation functions in hydrodynamic turbulence
NASA Astrophysics Data System (ADS)
Biferale, Luca; Calzavarini, Enrico; Toschi, Federico
2011-08-01
High Reynolds numbers Navier-Stokes equations are believed to break self-similarity concerning both spatial and temporal properties: correlation functions of different orders exhibit distinct decorrelation times and anomalous spatial scaling properties. Here, we present a systematic attempt to measure multi-time and multi-scale correlations functions, by using high Reynolds numbers numerical simulations of fully homogeneous and isotropic turbulent flow. The main idea is to set-up an ensemble of probing stations riding the flow, i.e., measuring correlations in a reference frame centered on the trajectory of distinct fluid particles (the quasi-Lagrangian reference frame introduced by Belinicher and L'vov [Sov. Phys. JETP 66, 303 (1987)]). In this way, we reduce the large-scale sweeping and measure the non-trivial temporal dynamics governing the turbulent energy transfer from large to small scales. We present evidences of the existence of the dynamic multiscaling properties of turbulence - first proposed by L'vov et al. [Phys. Rev. E 55, 7030 (1997)] - in which multi-time correlation functions are characterized by an infinite set of characteristic times.
Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks
Gearhart, Jared Lee; Kurtz, Nolan Scot
2014-09-01
The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.
Topographical modulation of macrophage phenotype by shrink-film multi-scale wrinkles.
Wang, Tingting; Luu, Thuy U; Chen, Aaron; Khine, Michelle; Liu, Wendy F
2016-06-24
The host immune response to foreign materials is a major hurdle for implanted medical devices. To control this response, modulation of macrophage behavior has emerged as a promising strategy, given their prominent role in inflammation and wound healing. Towards this goal, we explore the effect of biomimetic multi-scale wrinkles on macrophage adhesion and expression of phenotype markers. We find that macrophages elongate along the direction of the uniaxial wrinkles made from shape memory polymers, and express more arginase-1 and IL-10, and less TNF-α, suggesting polarization towards an alternatively activated, anti-inflammatory phenotype. Materials were further implanted in the subcutaneous space of mice and tissue surrounding the material evaluated by histology and immunohistochemistry. We found that material surface topography altered the distribution of collagen deposition in the adjacent tissue, with denser collagen tissue observed near flat materials when compared to wrinkled materials. Furthermore, cells surrounding wrinkled materials exhibited higher arginase-1 expression. Together these data suggest that wrinkled material surfaces promote macrophage alternative activation, and may influence the foreign body response to implants. PMID:27125253
Multi-scale upper mantle tomography of the Eurasia using surface waveform data
NASA Astrophysics Data System (ADS)
Gung, Y.; Chiao, L.
2006-12-01
We invert long period seismograms in the time domain in the framework of normal-mode-based nonlinear asymptotic coupling theory (NACT) [Li and Romanowicz, 1995] for the seismic structure underneath Eurasia. While only Eurasia region, where the sensitivity is the highest in the selected data set, is inverted for its radial anisotropic structure, the effects from global 3D heterogeneous structure are taken into account in the forward stage. The implementation of multi-scale inversion is achieved by converting the partial derivative matrices of the initial model parameters, either spherical harmonics or globally distributed spherical triangle meshes, into a multi-resolution wavelet representation in our interested region. In the scheme of multi-resolution wavelet representation, model parameters are grouped into natural hierarchy of local scales such that the damping regularization acts to sort through successive scales depending on the local data constraints. In other word, the spatially nonstationary smoothness enhancement is automatically invoked depending on the in-situ rigors of the model constraints offered from the data. As a result, sites with strong constraints are capable of resolving more details robustly whereas stable long wavelength components are still available for sparsely constrained area [Chiao and Liang, 2003].
Multi-scale analysis and optimized design of laminated-MRE bearings
NASA Astrophysics Data System (ADS)
Chen, Shiwei; Li, Rui; Zhang, Ze; Wang, Xiaojie
2016-04-01
We propose a method to analyze and design a laminated MRE bearing, in which the optimal parameters of materials and mechanical structure of the MRE bearing are determined. Based on the multi-scale and magneto-mechanical coupling theories, we establish a comprehensive model for the MRE bearing considering the influence of particle volume fraction, particle distribution, and thickness of MRE laminated layers on its mechanical performance. Within the micro-scale analysis, the representative volume unit (RVU) is used to address the effect of particle volume fraction and distribution on mechanical and magnetic properties of MRE itself. Within the macro-scale analysis, we build both mechanical and magnetic models for the laminated MRE bearing. Based on the theoretical analysis, a laminated MRE bearing with four-layer MRE is designed and fabricated. The performance of the MRE bearing has been tested by using MTS test bench. The results are compared with that of model analysis. It demonstrates that the proposed method can be a useful tool in the development of laminated-MRE bearings for practical applications.
NASA Astrophysics Data System (ADS)
Harris, B.; McDougall, K.; Barry, M.
2012-07-01
Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.
Oxley, Tim; Dore, Anthony J; ApSimon, Helen; Hall, Jane; Kryza, Maciej
2013-11-01
Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned. PMID:24096039
New multi-scale perspectives on the stromatolites of Shark Bay, Western Australia
NASA Astrophysics Data System (ADS)
Suosaari, E. P.; Reid, R. P.; Playford, P. E.; Foster, J. S.; Stolz, J. F.; Casaburi, G.; Hagan, P. D.; Chirayath, V.; MacIntyre, I. G.; Planavsky, N. J.; Eberli, G. P.
2016-02-01
A recent field-intensive program in Shark Bay, Western Australia provides new multi-scale perspectives on the world’s most extensive modern stromatolite system. Mapping revealed a unique geographic distribution of morphologically distinct stromatolite structures, many of them previously undocumented. These distinctive structures combined with characteristic shelf physiography define eight ‘Stromatolite Provinces’. Morphological and molecular studies of microbial mat composition resulted in a revised growth model where coccoid cyanobacteria predominate in mat communities forming lithified discrete stromatolite buildups. This contradicts traditional views that stromatolites with the best lamination in Hamelin Pool are formed by filamentous cyanobacterial mats. Finally, analysis of internal fabrics of stromatolites revealed pervasive precipitation of microcrystalline carbonate (i.e. micrite) in microbial mats forming framework and cement that may be analogous to the micritic microstructures typical of Precambrian stromatolites. These discoveries represent fundamental advances in our knowledge of the Shark Bay microbial system, laying a foundation for detailed studies of stromatolite morphogenesis that will advance our understanding of benthic ecosystems on the early Earth.
Study on multi-scale urban planning supported by spatial information technology
NASA Astrophysics Data System (ADS)
Dang, Anrong; He, Xindong; Li, Yongfu
2008-10-01
Considering the demand of urban and rural planning and the characteristics of spatial information technology (SIT), the study focuses on the application of SIT to support multi-scale urban planning. Three scales of urban and rural planning, such as city and town system planning, urban master planning, and detailed urban planning, were studied based on SIT. Firstly, tacking Great Beijing Region as an example, which includes Beijing, Tianjin, and northern of Hebei province, the city and town system planning was studied, supported by the theory of spatial interaction between cities and towns, and GIS spatial analysis. Then, for the urban master planning of Beijing, the RS and GIS were applied to do the spatial development analysis based on RS image data and GIS spatial analysis. Regarding to the conservation planning of Beijing's Inner city, the third scale is detailed urban planning. RS, GIS, and VR were integrated to determine the conservation region and digital conservation way as well. Finally, three conclusions were worked out.
Multi-scale sampling to evaluate assemblage dynamics in an oceanic marine reserve.
Thompson, Andrew R; Watson, William; McClatchie, Sam; Weber, Edward D
2012-01-01
To resolve the capacity of Marine Protected Areas (MPA) to enhance fish productivity it is first necessary to understand how environmental conditions affect the distribution and abundance of fishes independent of potential reserve effects. Baseline fish production was examined from 2002-2004 through ichthyoplankton sampling in a large (10,878 km(2)) Southern Californian oceanic marine reserve, the Cowcod Conservation Area (CCA) that was established in 2001, and the Southern California Bight as a whole (238,000 km(2) CalCOFI sampling domain). The CCA assemblage changed through time as the importance of oceanic-pelagic species decreased between 2002 (La Niña) and 2003 (El Niño) and then increased in 2004 (El Niño), while oceanic species and rockfishes displayed the opposite pattern. By contrast, the CalCOFI assemblage was relatively stable through time. Depth, temperature, and zooplankton explained more of the variability in assemblage structure at the CalCOFI scale than they did at the CCA scale. CalCOFI sampling revealed that oceanic species impinged upon the CCA between 2002 and 2003 in association with warmer offshore waters, thus explaining the increased influence of these species in the CCA during the El Nino years. Multi-scale, spatially explicit sampling and analysis was necessary to interpret assemblage dynamics in the CCA and likely will be needed to evaluate other focal oceanic marine reserves throughout the world. PMID:22448236
An Eye Model for Computational Dosimetry Using A Multi-Scale Voxel Phantom
NASA Astrophysics Data System (ADS)
Caracappa, Peter F.; Rhodes, Ashley; Fiedler, Derek
2014-06-01
The lens of the eye is a radiosensitive tissue with cataract formation being the major concern. Recently reduced recommended dose limits to the lens of the eye have made understanding the dose to this tissue of increased importance. Due to memory limitations, the voxel resolution of computational phantoms used for radiation dose calculations is too large to accurately represent the dimensions of the eye. A revised eye model is constructed using physiological data for the dimensions of radiosensitive tissues, and is then transformed into a high-resolution voxel model. This eye model is combined with an existing set of whole body models to form a multi-scale voxel phantom, which is used with the MCNPX code to calculate radiation dose from various exposure types. This phantom provides an accurate representation of the radiation transport through the structures of the eye. Two alternate methods of including a high-resolution eye model within an existing whole body model are developed. The accuracy and performance of each method is compared against existing computational phantoms.
Synergy of multi-scale toughening and protective mechanisms at hierarchical branch-stem interfaces.
Müller, Ulrich; Gindl-Altmutter, Wolfgang; Konnerth, Johannes; Maier, Günther A; Keckes, Jozef
2015-01-01
Biological materials possess a variety of artful interfaces whose size and properties are adapted to their hierarchical levels and functional requirements. Bone, nacre, and wood exhibit an impressive fracture resistance based mainly on small crystallite size, interface organic adhesives and hierarchical microstructure. Currently, little is known about mechanical concepts in macroscopic biological interfaces like the branch-stem junction with estimated 10(14) instances on earth and sizes up to few meters. Here we demonstrate that the crack growth in the upper region of the branch-stem interface of conifer trees proceeds along a narrow predefined region of transversally loaded tracheids, denoted as sacrificial tissue, which fail upon critical bending moments on the branch. The specific arrangement of the tracheids allows disconnecting the overloaded branch from the stem in a controlled way by maintaining the stem integrity. The interface microstructure based on the sharply adjusted cell orientation and cell helical angle secures a zig-zag crack propagation path, mechanical interlock closing after the bending moment is removed, crack gap bridging and self-repairing by resin deposition. The multi-scale synergetic concepts allows for a controllable crack growth between stiff stem and flexible branch, as well as mechanical tree integrity, intact physiological functions and recovery after the cracking. PMID:26415835
Multi-scale experimental analysis of rate dependent metal-elastomer interface mechanics
NASA Astrophysics Data System (ADS)
Neggers, J.; Hoefnagels, J. P. M.; van der Sluis, O.; Geers, M. G. D.
2015-07-01
A remarkable high fracture toughness is sometimes observed for interfaces between materials with a large elastic mismatch, which is reported to be caused by the fibrillar microstructure appearing in the fracture process zone. In this work, this fibrillation mechanism is investigated further to investigate how this mechanism is dissipating energy. For that purpose, thermoplastic urethane (TPU)-copper interfaces are delaminated at various rates in a peel test experimental setup. The fracture process zone is visualized in situ at the meso-scale using optical microscopy and at the micro-scale using Environmental Scanning Electron Microscopy (ESEM). It is shown that the geometry of the fracture process zone is insensitive to the delamination rate, while the interface traction scales logarithmically with the rate. This research has revealed that, the interface roughness is shown to be pivotal in initiating the fibrillation delamination process, which facilitates the high fracture toughness. The multi-scale experimental approach identified two mechanisms responsible for this high fracture toughness. Namely, the viscous dissipation of the TPU at the high strain levels occurring in the fibrils and the loss of stored elastic energy which is disjointed from the propagation due to the size of the process zone.
Multi-scale models of grassland passerine abundance in a fragmented system in Wisconsin
Renfrew, R.B.; Ribic, C.A.
2008-01-01
Fragmentation of grasslands has been implicated in grassland bird population declines. Multi-scale models are being increasingly used to assess potential factors that influence grassland bird presence, abundance, and productivity. However, studies rarely assess fragmentation metrics, and seldom evaluate more than two scales or interactions among scales. We evaluated the relative importance of characteristics at multiple scales to patterns in relative abundance of Savannah Sparrow (Passerculus sandwichensis), Grasshopper Sparrow (Ammodramus savannarum), Eastern Meadowlark (Sturnella magna), and Bobolink (Dolichonyx oryzivorus). We surveyed birds in 74 southwestern Wisconsin pastures from 1997 to 1999 and compared models with explanatory variables from multiple scales: within-patch vegetation structure (microhabitat), patch (macrohabitat), and three landscape extents. We also examined interactions between macrohabitat and landscape factors. Core area of pastures was an important predictor of relative abundance, and composition of the landscape was more important than configuration. Relative abundance was frequently higher in pastures with more core area and in landscapes with more grassland and less wooded area. The direction and strength of the effect of core pasture size on relative abundance changed depending on amount of wooded area in the landscape. Relative abundance of grassland birds was associated with landscape variables more frequently at the 1200-m scale than at smaller scales. To develop better predictive models, parameters at multiple scales and their interactive effects should be included, and results should be evaluated in the context of microhabitat variability, landscape composition, and fragmentation in the study area. ?? 2007 Springer Science+Business Media B.V.
NASA Astrophysics Data System (ADS)
Lázár, Dóra; Weidinger, Tamás
2016-04-01
For our days, it has become important to measure and predict the concentration of harmful atmospheric pollutants such as dust, aerosol particles of different size ranges, nitrogen compounds, and ozone. The Department of Meteorology at Eötvös Loránd University has been applying the WRF (Weather Research and Forecasting) model several years ago, which is suitable for weather forecasting tasks and provides input data for various environmental models (e.g. DNDC). By adapting the CMAQ (Community Multi-scale Air Quality) model we have designed a combined ambient air-meteorological model (WRF-CMAQ). In this research it is important to apply different emission databases and a background model describing the initial distribution of the pollutant. We used SMOKE (Sparse Matrix Operator Kernel Emissions) model for construction emission dataset from EMEP (European Monitoring and Evaluation Programme) inventories and GEOS-Chem model for initial and boundary conditions. Our model settings were CMAQ CB05 (Carbon Bond 2005) chemical mechanism with 108 x 108 km, 36 x 36 km and 12 x 12 km grids for regions of Europe, the Carpathian Basin and Hungary respectively. i) The structure of the model system, ii) a case study for Carpathian Basin (an anticyclonic weather situation at 21th September 2012) are presented. iii) Verification of ozone forecast has been provided based on the measurements of background air pollution stations. iv) Effects of model attributes (f.e. transition time, emission dataset, parameterizations) for the ozone forecast in Hungary are also investigated.
NASA Astrophysics Data System (ADS)
Li, Changbo; Wang, Liangshu; Sun, Bin; Feng, Runhai; Wu, Yongjing
2015-09-01
In this paper, we introduce the method of Wavelet Multi-scale Decomposition (WMD) combined with Power Spectrum Analysis (PSA) for the separation of regional gravity and magnetic anomalies. The Songliao Basin is situated between the Siberian Plate and the North China Plate, and its main structural trend of gravity and magnetic anomaly fields is NNE. The study area shows a significant feature of deep collage-type construction. According to the feature of gravity field, the region was divided into five sub-regions. The gravity and magnetic fields of the Songliao Basin were separated using WMD with a 4th order separation. The apparent depth of anomalies in each order was determined by Logarithmic PSA. Then, the shallow high-frequency anomalies were removed and the 2nd-4th order wavelet detail anomalies were used to study the basin's major faults. Twenty-six faults within the basement were recognized. The 4th order wavelet approximate anomalies were used for the inversion of the Moho discontinuity and the Curie isothermal surface.
Dilts, Thomas E.; Weisberg, Peter J.; Leitner, Phillip; Matocq, Marjorie D.; Inman, Richard D.; Nussear, Ken E.; Esque, Todd
2016-01-01
Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land-use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multi-scale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods including graph theory, circuit theory and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this California threatened species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American Southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously-distributed habitat, and should be applicable across a broad range of taxa.
MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate
NASA Astrophysics Data System (ADS)
Baklanov, A.; Lawrence, M.; Pandis, S.; Mahura, A.; Finardi, S.; Moussiopoulos, N.; Beekmann, M.; Laj, P.; Gomes, L.; Jaffrezo, J.-L.; Borbon, A.; Coll, I.; Gros, V.; Sciare, J.; Kukkonen, J.; Galmarini, S.; Giorgi, F.; Grimmond, S.; Esau, I.; Stohl, A.; Denby, B.; Wagner, T.; Butler, T.; Baltensperger, U.; Builtjes, P.; van den Hout, D.; van der Gon, H. D.; Collins, B.; Schluenzen, H.; Kulmala, M.; Zilitinkevich, S.; Sokhi, R.; Friedrich, R.; Theloke, J.; Kummer, U.; Jalkinen, L.; Halenka, T.; Wiedensholer, A.; Pyle, J.; Rossow, W. B.
2010-11-01
The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.
NASA Astrophysics Data System (ADS)
Wang, Ping; Dai, Xin-Gang
2016-09-01
The term "APEC Blue" has been created to describe the clear sky days since the Asia-Pacific Economic Cooperation (APEC) summit held in Beijing during November 5-11, 2014. The duration of the APEC Blue is detected from November 1 to November 14 (hereafter Blue Window) by moving t test in statistics. Observations show that APEC Blue corresponds to low air pollution with respect to PM2.5, PM10, SO2, and NO2 under strict emission-control measures (ECMs) implemented in Beijing and surrounding areas. Quantitative assessment shows that ECM is more effective on reducing aerosols than the chemical constituents. Statistical investigation has revealed that the window also resulted from intensified wind variability, as well as weakened static stability of atmosphere (SSA). The wind and ECMs played key roles in reducing air pollution during November 1-7 and 11-13, and strict ECMs and weak SSA become dominant during November 7-10 under weak wind environment. Moving correlation manifests that the emission reduction for aerosols can increase the apparent wind cleanup effect, leading to significant negative correlations of them, and the period-wise changes in emission rate can be well identified by multi-scale correlations basing on wavelet decomposition. In short, this case study manifests statistically how human interference modified air quality in the mega city through controlling local and surrounding emissions in association with meteorological condition.
Fu, Hai-Yan; Guo, Jun-Wei; Yu, Yong-Jie; Li, He-Dong; Cui, Hua-Peng; Liu, Ping-Ping; Wang, Bing; Wang, Sheng; Lu, Peng
2016-06-24
Peak detection is a critical step in chromatographic data analysis. In the present work, we developed a multi-scale Gaussian smoothing-based strategy for accurate peak extraction. The strategy consisted of three stages: background drift correction, peak detection, and peak filtration. Background drift correction was implemented using a moving window strategy. The new peak detection method is a variant of the system used by the well-known MassSpecWavelet, i.e., chromatographic peaks are found at local maximum values under various smoothing window scales. Therefore, peaks can be detected through the ridge lines of maximum values under these window scales, and signals that are monotonously increased/decreased around the peak position could be treated as part of the peak. Instrumental noise was estimated after peak elimination, and a peak filtration strategy was performed to remove peaks with signal-to-noise ratios smaller than 3. The performance of our method was evaluated using two complex datasets. These datasets include essential oil samples for quality control obtained from gas chromatography and tobacco plant samples for metabolic profiling analysis obtained from gas chromatography coupled with mass spectrometry. Results confirmed the reasonability of the developed method. PMID:27207578
Complex coordination of multi-scale cellular responses to environmental stress.
Fonseca, Luís L; Sánchez, Claudia; Santos, Helena; Voit, Eberhard O
2011-03-01
Cells and organisms are regularly exposed to a variety of stresses, and effective responses are a matter of survival. The article describes a multi-scale experimental and dynamical modeling analysis that clearly indicates concerted stress control in different temporal and organizational domains, and a strong synergy between the dynamics of genes, proteins and metabolites. Specifically, we show with in vivo NMR measurements of metabolic profiles that baker's yeast responds to a paradigmatic stress, heat, at three organizational levels and in two time regimes. At the metabolic level, an almost immediate response is mounted. However, this response is a "quick fix" in comparison to a much more effective response that had been pre-organized in earlier periods of heat stress and is an order of magnitude stronger. Equipped with the metabolic profile data, our modeling efforts resulted in a crisp, quantitative separation of response actions at the levels of metabolic control and gene regulation. They also led to predictions of necessary changes in protein levels and clearly demonstrated that formerly observed temperature profiles of key enzyme activities are not sufficient to explain the accumulation of trehalose as an immediate response to sudden heat stress. PMID:21088798
YUP: A Molecular Simulation Program for Coarse-Grained and Multi-Scaled Models.
Tan, Robert K Z; Petrov, Anton S; Harvey, Stephen C
2006-05-01
Coarse-grained models can be very different from all-atom models and are highly varied. Each class of model is assembled very differently and some models need customized versions of the standard molecular mechanics methods. The most flexible way to meet these diverse needs is to provide access to internal data structures and a programming language to manipulate these structures. We have created YUP, a general-purpose program for coarse-grained and multi-scaled models. YUP extends the Python programming language by adding new data types. We have then used the extended language to implement three classes of coarse-grained models. The coarse-grained RNA model type is an unusual non-linear polymer and the assembly was easily handled with a simple program. The molecular dynamics algorithm had to be extended for a coarse-grained DNA model so that it could detect a failure that is invisible to a standard implementation. A third model type took advantage of access to the force field to simulate the packing of DNA in viral capsid. We find that objects are easy to modify, extend and redeploy. Thus, new classes of coarse-grained models can be implemented easily. PMID:22844233
A multi-scale controlled tissue engineering scaffold prepared by 3D printing and NFES technology
NASA Astrophysics Data System (ADS)
Yan, Feifei; Liu, Yuanyuan; Chen, Haiping; Zhang, Fuhua; Zheng, Lulu; Hu, Qingxi
2014-03-01
The current focus in the field of life science is the use of tissue engineering scaffolds to repair human organs, which has shown great potential in clinical applications. Extracellular matrix morphology and the performance and internal structure of natural organs are required to meet certain requirements. Therefore, integrating multiple processes can effectively overcome the limitations of the individual processes and can take into account the needs of scaffolds for the material, structure, mechanical properties and many other aspects. This study combined the biological 3D printing technology and the near-field electro-spinning (NFES) process to prepare a multi-scale controlled tissue engineering scaffold. While using 3D printing technology to directly prepare the macro-scaffold, the compositing NFES process to build tissue micro-morphology ultimately formed a tissue engineering scaffold which has the specific extracellular matrix structure. This scaffold not only takes into account the material, structure, performance and many other requirements, but also focuses on resolving the controllability problems in macro- and micro-forming which further aim to induce cell directed differentiation, reproduction and, ultimately, the formation of target tissue organs. It has in-depth immeasurable significance to build ideal scaffolds and further promote the application of tissue engineering.
Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension.
Backes, André Ricardo; Gerhardinger, Leandro Cavaleri; Batista Neto, João do Espírito Santo; Bruno, Odemir Martinez
2015-02-01
Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered. PMID:25586375
Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension
NASA Astrophysics Data System (ADS)
Backes, André Ricardo; Cavaleri Gerhardinger, Leandro; do Espírito Santo Batista Neto, João; Martinez Bruno, Odemir
2015-02-01
Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered.
Realistic Modeling of Multi-Scale MHD Dynamics of the Solar Atmosphere
NASA Technical Reports Server (NTRS)
Kitiashvili, Irina; Mansour, Nagi N.; Wray, Alan; Couvidat, Sebastian; Yoon, Seokkwan; Kosovichev, Alexander
2014-01-01
Realistic 3D radiative MHD simulations open new perspectives for understanding the turbulent dynamics of the solar surface, its coupling to the atmosphere, and the physical mechanisms of generation and transport of non-thermal energy. Traditionally, plasma eruptions and wave phenomena in the solar atmosphere are modeled by prescribing artificial driving mechanisms using magnetic or gas pressure forces that might arise from magnetic field emergence or reconnection instabilities. In contrast, our 'ab initio' simulations provide a realistic description of solar dynamics naturally driven by solar energy flow. By simulating the upper convection zone and the solar atmosphere, we can investigate in detail the physical processes of turbulent magnetoconvection, generation and amplification of magnetic fields, excitation of MHD waves, and plasma eruptions. We present recent simulation results of the multi-scale dynamics of quiet-Sun regions, and energetic effects in the atmosphere and compare with observations. For the comparisons we calculate synthetic spectro-polarimetric data to model observational data of SDO, Hinode, and New Solar Telescope.
A multi-scale relevance vector regression approach for daily urban water demand forecasting
NASA Astrophysics Data System (ADS)
Bai, Yun; Wang, Pu; Li, Chuan; Xie, Jingjing; Wang, Yin
2014-09-01
Water is one of the most important resources for economic and social developments. Daily water demand forecasting is an effective measure for scheduling urban water facilities. This work proposes a multi-scale relevance vector regression (MSRVR) approach to forecast daily urban water demand. The approach uses the stationary wavelet transform to decompose historical time series of daily water supplies into different scales. At each scale, the wavelet coefficients are used to train a machine-learning model using the relevance vector regression (RVR) method. The estimated coefficients of the RVR outputs for all of the scales are employed to reconstruct the forecasting result through the inverse wavelet transform. To better facilitate the MSRVR forecasting, the chaos features of the daily water supply series are analyzed to determine the input variables of the RVR model. In addition, an adaptive chaos particle swarm optimization algorithm is used to find the optimal combination of the RVR model parameters. The MSRVR approach is evaluated using real data collected from two waterworks and is compared with recently reported methods. The results show that the proposed MSRVR method can forecast daily urban water demand much more precisely in terms of the normalized root-mean-square error, correlation coefficient, and mean absolute percentage error criteria.
Synergy of multi-scale toughening and protective mechanisms at hierarchical branch-stem interfaces
NASA Astrophysics Data System (ADS)
Müller, Ulrich; Gindl-Altmutter, Wolfgang; Konnerth, Johannes; Maier, Günther A.; Keckes, Jozef
2015-09-01
Biological materials possess a variety of artful interfaces whose size and properties are adapted to their hierarchical levels and functional requirements. Bone, nacre, and wood exhibit an impressive fracture resistance based mainly on small crystallite size, interface organic adhesives and hierarchical microstructure. Currently, little is known about mechanical concepts in macroscopic biological interfaces like the branch-stem junction with estimated 1014 instances on earth and sizes up to few meters. Here we demonstrate that the crack growth in the upper region of the branch-stem interface of conifer trees proceeds along a narrow predefined region of transversally loaded tracheids, denoted as sacrificial tissue, which fail upon critical bending moments on the branch. The specific arrangement of the tracheids allows disconnecting the overloaded branch from the stem in a controlled way by maintaining the stem integrity. The interface microstructure based on the sharply adjusted cell orientation and cell helical angle secures a zig-zag crack propagation path, mechanical interlock closing after the bending moment is removed, crack gap bridging and self-repairing by resin deposition. The multi-scale synergetic concepts allows for a controllable crack growth between stiff stem and flexible branch, as well as mechanical tree integrity, intact physiological functions and recovery after the cracking.
Multi-scale Observation of Biological Interactions of Nanocarriers: from Nano to Macro
Jin, Su-Eon; Bae, Jin Woo; Hong, Seungpyo
2010-01-01
Microscopic observations have played a key role in recent advancements in nanotechnology-based biomedical sciences. In particular, multi-scale observation is necessary to fully understand the nano-bio interfaces where a large amount of unprecedented phenomena have been reported. This review describes how to address the physicochemical and biological interactions of nanocarriers within the biological environments using microscopic tools. The imaging techniques are categorized based on the size scale of detection. For observation of the nano-scale biological interactions of nanocarriers, we discuss atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). For the micro to macro-scale (in vitro and in vivo) observation, we focus on confocal laser scanning microscopy (CLSM) as well as in vivo imaging systems such as magnetic resonance imaging (MRI), superconducting quantum interference devices (SQUIDs), and IVIS®. Additionally, recently developed combined techniques such as AFM-CLSM, correlative Light and Electron Microscopy (CLEM), and SEM-spectroscopy are also discussed. In this review, we describe how each technique helps elucidate certain physicochemical and biological activities of nanocarriers such as dendrimers, polymers, liposomes, and polymeric/inorganic nanoparticles, thus providing a toolbox for bioengineers, pharmaceutical scientists, biologists, and research clinicians. PMID:20232368
Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction
NASA Technical Reports Server (NTRS)
Li, Zhijin; Chao, Yi; Li, P. Peggy
2012-01-01
A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.
Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems
NASA Astrophysics Data System (ADS)
Shyy, Wei; Cho, Young-Chang; Du, Wenbo; Gupta, Amit; Tseng, Chien-Chou; Sastry, Ann Marie
2011-12-01
Successful modeling and/or design of engineering systems often requires one to address the impact of multiple "design variables" on the prescribed outcome. There are often multiple, competing objectives based on which we assess the outcome of optimization. Since accurate, high fidelity models are typically time consuming and computationally expensive, comprehensive evaluations can be conducted only if an efficient framework is available. Furthermore, informed decisions of the model/hardware's overall performance rely on an adequate understanding of the global, not local, sensitivity of the individual design variables on the objectives. The surrogate-based approach, which involves approximating the objectives as continuous functions of design variables from limited data, offers a rational framework to reduce the number of important input variables, i.e., the dimension of a design or modeling space. In this paper, we review the fundamental issues that arise in surrogate-based analysis and optimization, highlighting concepts, methods, techniques, as well as modeling implications for mechanics problems. To aid the discussions of the issues involved, we summarize recent efforts in investigating cryogenic cavitating flows, active flow control based on dielectric barrier discharge concepts, and lithium (Li)-ion batteries. It is also stressed that many multi-scale mechanics problems can naturally benefit from the surrogate approach for "scale bridging."
Multi-scale simulations predict responses to non-invasive nerve root stimulation
NASA Astrophysics Data System (ADS)
Laakso, Ilkka; Matsumoto, Hideyuki; Hirata, Akimasa; Terao, Yasuo; Hanajima, Ritsuko; Ugawa, Yoshikazu
2014-10-01
Objective. Established biophysical neurone models have achieved limited success in reproducing electrophysiological responses to non-invasive stimulation of the human nervous system. This is related to our insufficient knowledge of the induced electric currents inside the human body. Despite the numerous research and clinical applications of non-invasive stimulation, it is still unclear which internal sites are actually affected by it. Approach. We performed multi-scale computer simulations that, by making use of advances in computing power and numerical algorithms, combine a microscopic model of electrical excitation of neurones with a macroscopic electromagnetic model of the realistic whole-body anatomy. Main results. The simulations yield responses consistent with those experimentally recorded following magnetic and electrical motor root stimulation in human subjects, and reproduce the observed amplitudes and latencies for a wide variety of stimulation parameters. Significance. Our findings demonstrate that modern computational techniques can produce detailed predictions about which and where neurones are activated, leading to improved understanding of the physics and basic mechanisms of non-invasive stimulation and enabling potential new applications that make use of improved targeting of stimulation.
New multi-scale perspectives on the stromatolites of Shark Bay, Western Australia.
Suosaari, E P; Reid, R P; Playford, P E; Foster, J S; Stolz, J F; Casaburi, G; Hagan, P D; Chirayath, V; Macintyre, I G; Planavsky, N J; Eberli, G P
2016-01-01
A recent field-intensive program in Shark Bay, Western Australia provides new multi-scale perspectives on the world's most extensive modern stromatolite system. Mapping revealed a unique geographic distribution of morphologically distinct stromatolite structures, many of them previously undocumented. These distinctive structures combined with characteristic shelf physiography define eight 'Stromatolite Provinces'. Morphological and molecular studies of microbial mat composition resulted in a revised growth model where coccoid cyanobacteria predominate in mat communities forming lithified discrete stromatolite buildups. This contradicts traditional views that stromatolites with the best lamination in Hamelin Pool are formed by filamentous cyanobacterial mats. Finally, analysis of internal fabrics of stromatolites revealed pervasive precipitation of microcrystalline carbonate (i.e. micrite) in microbial mats forming framework and cement that may be analogous to the micritic microstructures typical of Precambrian stromatolites. These discoveries represent fundamental advances in our knowledge of the Shark Bay microbial system, laying a foundation for detailed studies of stromatolite morphogenesis that will advance our understanding of benthic ecosystems on the early Earth. PMID:26838605
A top-down multi-scale modeling for actuation response of polymeric artificial muscles
NASA Astrophysics Data System (ADS)
Yang, Qianxi; Li, Guoqiang
2016-07-01
A class of innovative artificial muscles made of high-strength polymeric fibers such as fishing lines or sewing threads have been discovered recently. These muscles are fabricated by a simple "twist-insertion" procedure, which have attracted increasing attention due to their low cost and readily availability, giant tensile stroke, record energy density, and easy controllability. In the present paper, we established a multi-scale modeling framework for the thermomechanical actuation responses by a top-down strategy, spanning from macro-scale helical spring analysis down to molecular level chain interaction study. Comparison between modeling results and experimental results exhibited excellent agreement. The effect of the micro-, meso- and macro-scale parameters on the actuation responses of the artificial muscle was further discussed through a parametric study per the validated model. This work helps understand the physical origin behind the remarkable tensile actuation behavior of the twisted-then-coiled polymeric artificial muscles and also provides inspirations for optimal design of advanced artificial muscles made by twist-insertion procedure.
Multi-Scale Modeling and the Eddy-Diffusivity/Mass-Flux (EDMF) Parameterization
NASA Astrophysics Data System (ADS)
Teixeira, J.
2015-12-01
Turbulence and convection play a fundamental role in many key weather and climate science topics. Unfortunately, current atmospheric models cannot explicitly resolve most turbulent and convective flow. Because of this fact, turbulence and convection in the atmosphere has to be parameterized - i.e. equations describing the dynamical evolution of the statistical properties of turbulence and convection motions have to be devised. Recently a variety of different models have been developed that attempt at simulating the atmosphere using variable resolution. A key problem however is that parameterizations are in general not explicitly aware of the resolution - the scale awareness problem. In this context, we will present and discuss a specific approach, the Eddy-Diffusivity/Mass-Flux (EDMF) parameterization, that not only is in itself a multi-scale parameterization but it is also particularly well suited to deal with the scale-awareness problems that plague current variable-resolution models. It does so by representing small-scale turbulence using a classic Eddy-Diffusivity (ED) method, and the larger-scale (boundary layer and tropospheric-scale) eddies as a variety of plumes using the Mass-Flux (MF) concept.
Coastal ocean data assimilation using a multi-scale three-dimensional variational scheme
NASA Astrophysics Data System (ADS)
Li, Zhijin; McWilliams, James C.; Ide, Kayo; Farrara, John D.
2015-07-01
A multi-scale three-dimensional variational scheme (MS-3DVAR) is implemented to improve the effectiveness of the assimilation of both very sparse and high-resolution observations into models with resolutions down to 1 km. The improvements are realized through the use of background error covariances of multi-decorrelation length scales and by reducing the inherent observational representativeness errors. MS-3DVAR is applied to coastal ocean data assimilation to handle the wide range of spatial scales that exist in both the dynamics and observations. In the implementation presented here, the cost function consists of two components for large and small scales, and MS-3DVAR is implemented sequentially from large to small scales. A set of observing system simulation experiments (OSSEs) are performed to illustrate the advantages of MS-3DVAR over conventional 3DVAR in assimilating two of the most common types of observations—sparse vertical profiles and high-resolution surface measurements—simultaneously. One month of results from an operational implementation show that both the analysis error and bias are reduced more effectively when using MS-3DVAR.
McKenna, J.E.; Castiglione, C.
2010-01-01
Classification is a valuable conservation tool for examining natural resource status and problems and is being developed for coastal aquatic habitats. We present an objective, multi-scale hydrospatial framework for nearshore areas of the Great Lakes. The hydrospatial framework consists of spatial units at eight hierarchical scales from the North American Continent to the individual 270-m spatial cell. Characterization of spatial units based on fish abundance and diversity provides a fish-guided classification of aquatic areas at each spatial scale and demonstrates how classifications may be generated from that framework. Those classification units then provide information about habitat, as well as biotic conditions, which can be compared, contrasted, and hierarchically related spatially. Examples within several representative coastal or open water zones of the Western Lake Erie pilot area highlight potential application of this classification system to management problems. This classification system can assist natural resource managers with planning and establishing priorities for aquatic habitat protection, developing rehabilitation strategies, or identifying special management actions.
Multi-scale model for hepatitis C viral load kinetics under treatment with direct acting antivirals.
Clausznitzer, Diana; Harnisch, Julia; Kaderali, Lars
2016-06-15
Hepatitis C virus (HCV) infections are a global health problem, and extensive research over the last decades has been targeted at understanding its molecular biology and developing effective antiviral treatments. Recently, a number of potent direct acting antiviral drugs have been developed targeting specific processes in the viral life cycle. Here, we developed a mathematical multi-scale model of the within-host dynamics of HCV infection by integrating a standard model for viral infection with a detailed model of the viral replication cycle inside infected cells. We use this model to study patient time courses of viral load under treatment with daclatasvir, an inhibitor of the viral non-structural protein NS5A. Model analysis predicts that treatment efficacy can be increased by combining daclatasvir with dedicated viral polymerase inhibitors, corresponding to promising current strategies in drug development. Hence, our model presents a predictive tool for in silico simulations, which can be used to study and optimize direct acting antiviral drug treatment. PMID:26409026
A new multi-scale measure for analysing animal movement data.
Postlethwaite, Claire M; Brown, Pieta; Dennis, Todd E
2013-01-21
We present a new measure for analysing animal movement data, which we term a 'Multi-Scale Straightness Index' (MSSI). The measure is a generalisation of the 'Straightness Index', the ratio of the beeline distance between the start and end of a track to the total distance travelled. In our new measure, the Straightness Index is computed repeatedly for track segments at all possible temporal scales. The MSSI offers advantages over the standard Straightness Index, and other simple measures of track tortuosity (such as Sinuosity and Fractal Dimension), because it provides multiple characterisations of straightness, rather than just a single summary measure. Thus, comparisons can be made among different segments of trajectories and changes in behaviour can be inferred, both over time and at different temporal granularities. The measure also has an important advantage over several recent and increasingly popular methods for detecting behavioural changes in time-series locational data (e.g., state-space models and positional entropy methods), in that it is extremely simple to compute. Here, we demonstrate use of the MSSI on both synthetic and real animal-movement trajectories. We show how behavioural changes can be inferred within individual tracks and how behaviour varies across spatio-temporal scales. Our aim is to present a useful tool for researchers requiring a computationally simple but effective means of analysing the movement patterns of animals. PMID:23079283
Arkle, Robert S.; Pilliod, David S.; Hanser, Steven E.; Brooks, Matthew L.; Chambers, Jeanne C.; Grace, James B.; Knutson, Kevin C.; Pyke, David A.; Welty, Justin L.
2014-01-01
A recurrent challenge in the conservation of wide-ranging, imperiled species is understanding which habitats to protect and whether we are capable of restoring degraded landscapes. For Greater Sage-grouse (Centrocercus urophasianus), a species of conservation concern in the western United States, we approached this problem by developing multi-scale empirical models of occupancy in 211 randomly located plots within a 40 million ha portion of the species' range. We then used these models to predict sage-grouse habitat quality at 826 plots associated with 101 post-wildfire seeding projects implemented from 1990 to 2003. We also compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe prevalence, and negatively associated with non-native plants and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.09) and not substantially different from burned areas that had not been treated. Restoration sites with quality habitat tended to occur at higher elevation locations with low annual temperatures, high spring precipitation, and high plant diversity. Of 313 plots seeded after fire, none met all sagebrush guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This pattern was similar for summer habitat. Less than 2% of treated plots met winter habitat guidelines. Restoration actions did not increase the probability of burned areas meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, climate, and topography. Our results suggest that sage-grouse are relatively unlikely to use many burned areas within 20 years of fire, regardless of treatment. Understory habitat conditions are more likely to be adequate than overstory
Multi-scale characterization by FIB-SEM/TEM/3DAP.
Ohkubo, T; Sepehri-Amin, H; Sasaki, T T; Hono, K
2014-11-01
In order to improve properties of functional materials, it is important to understand the relation between the structure and the properties since the structure has large effect to the properties. This can be done by using multi-scale microstructure analysis from macro-scale to nano and atomic scale. Scanning electron microscope (SEM) equipped with focused ion beam (FIB), transmission electron microscope (TEM) and 3D atom probe (3DAP) are complementary analysis tools making it possible to know the structure and the chemistry from micron to atomic resolution. SEM gives us overall microstructural and chemical information by various kinds of detectors such as secondary electron, backscattered electron, EDS and EBSD detectors. Also, it is possible to analyze 3D structure and chemistry via FIB serial sectioning. In addition, using TEM we can focus on desired region to get more complementary information from HRTEM/STEM/Lorentz images, SAED/NBD patterns and EDS/EELS to see the detail micro or nano-structure and chemistry. Especially, combination of probe Cs corrector and split EDS detectors with large detector size enable us to analyze the atomic scale elemental distribution. Furthermore, if the specimen has a complicated 3D nanostructure, or we need to analyze light elements such as hydrogen, lithium or boron, 3DAP can be used as the only technique which can visualize and analyze distribution of all constituent atoms of our materials within a few hundreds nm area. Hence, site-specific sample preparation using FIB/SEM is necessary to get desired information from region of interest. Therefore, this complementary analysis combination works very well to understand the detail of materials.In this presentation, we will show the analysis results obtained from some of functional materials by Carl Zeiss CrossBeam 1540EsB FIB/SEM, FEI Tecnai G(2) F30, Titan G2 80-200 TEMs and locally build laser assisted 3DAP. As the one of the example, result of multi-scale characterization for
Helicity, geostrophic balance and mixing in rotating stratified turbulence: a multi-scale problem
NASA Astrophysics Data System (ADS)
Pouquet, A.; Marino, R.; Mininni, P.; Rorai, C.; Rosenberg, D. L.
2012-12-01
Helicity, geostrophic balance and mixing in rotating stratified turbulence: a multi-scale problem A. Pouquet, R. Marino, P. D. Mininni, C. Rorai & D. Rosenberg, NCAR Interactions between winds and waves have important roles in planetary and oceanic boundary layers, affecting momentum, heat and CO2 transport. Within the Abyssal Southern Ocean at Mid latitude, this may result in a mixed layer which is too shallow in climate models thereby affecting the overall evolution because of poor handling of wave breaking as in Kelvin-Helmoltz instabilities: gravity waves couple nonlinearly on slow time scales and undergo steepening through resonant interactions, or due to the presence of shear. In the oceans, sub-mesoscale frontogenesis and significant departure from quasi-geostrophy can be seen as turbulence intensifies. The ensuing anomalous vertical dispersion may not be simply modeled by a random walk, due to intermittent structures, wave propagation and to their interactions. Conversely, the energy and seeds required for such intermittent events to occur, say in the stable planetary boundary layer, may come from the wave field that is perturbed, or from winds and the effect of topography. Under the assumption of stationarity, weak nonlinearities, dissipation and forcing, one obtains large-scale geostrophic balance linking pressure gradient, gravity and Coriolis force. The role of helicity (velocity-vorticity correlations) has not received as much attention, outside the realm of astrophysics when considering the growth of large-scale magnetic fields. However, it is measured routinely in the atmosphere in order to gauge the likelihood of supercell convective storms to strengthen, and it may be a factor to consider in the formation of hurricanes. In this context, we examine the transition from a wave-dominated regime to an isotropic small-scale turbulent one in rotating flows with helical forcing. Using a direct numerical simulation (DNS) on a 3072^3 grid with Rossby and
a Region-Based Multi-Scale Approach for Object-Based Image Analysis
NASA Astrophysics Data System (ADS)
Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.
2016-06-01
Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.
Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography
NASA Astrophysics Data System (ADS)
Lowe, T.; Bradley, R. S.; Yue, S.; Barii, K.; Gelb, J.; Rohbeck, N.; Turner, J.; Withers, P. J.
2015-06-01
TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3-10 μm and 3-100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions.
Multi-scale X-ray Microtomography Imaging of Immiscible Fluids After Imbibition
NASA Astrophysics Data System (ADS)
Garing, C.; de Chalendar, J.; Voltolini, M.; Ajo Franklin, J. B.; Benson, S. M.
2015-12-01
A major issue for CO2 storage security is the efficiency and long-term reliability of the trapping mechanisms occurring in the reservoir where CO2 is injected. Residual trapping is one of the key processes for storage security beyond the primary stratigraphic seal. Although classical conceptual models of residual fluid trapping assume that disconnected ganglia are permanently immobilized, multiple mechanisms exist which could allow the remobilization of residually trapped CO2. The aim of this study is to quantify fluid phases saturation, connectivity and morphology after imbibition using x-ray microtomography in order to evaluate potential changes in droplets organization due to differences in capillary pressure between disconnected ganglia. Particular emphasis is placed on the effect of image resolution. Synchrotron-based x-ray microtomographic datasets of air-water spontaneous imbibition were acquired in sintered glass beads and sandstone samples with voxel sizes varying from 0.64 to 4.44 μm. The results show that for both sandstones the residual air phase is homogeneously distributed within the entire pore space and consists of disconnected clusters of multiple sizes and morphologies. The multi-scale analysis of subsamples of few pores and throats imaged at the same location of the sample reveals significant variations in the estimation of connectivity, size and shape of the fluid phases. This is particularly noticeable when comparing the results from the images with voxel sizes above 1 μm with the results from the images acquired with voxel sizes below 1 μm.
NASA Astrophysics Data System (ADS)
Watlet, Arnaud; Poulain, Amaël; Van Camp, Michel; Francis, Olivier; Triantafyllou, Antoine; Rochez, Gaëtan; Hallet, Vincent; Kaufmann, Olivier
2016-04-01
The vadose zone of karst systems plays an important role on the water dynamics. In particular, temporary perched aquifers can appear in the subsurface due to changes of weather conditions, reduced evapotranspiration and the vertical gradients of porosity and permeability. Although many difficulties are usually encountered when studying karst environments due to their heterogeneities, cave systems offer an outstanding opportunity to investigate vadose zone from the inside. We present a multi-scale study covering two years of hydrogeological and geophysical monitoring of the Lomme Karst System (LKS) located in the Variscan fold-and-thrust belt (Belgium), a region (~ 3000 ha) that shows many karstic networks within Devonian limestone units. Hydrogeological data cover the whole LKS and involve e.g. flows and levels monitoring or tracer tests performed in both vadose and saturated zones. Such data bring valuable information on the hydrological context of the studied area at the catchment scale. Combining those results with geophysical measurements allows validating and imaging them at a smaller scale, with more integrative techniques. Hydrogeophysical measurements are focused on only one cave system of the LKS, at the Rochefort site (~ 40 ha), taking benefit of the Rochefort Cave Laboratory (RCL) infrastructures. In this study, a microgravimetric monitoring and an Electrical Resistivity Tomography (ERT) monitoring are involved. The microgravimetric monitoring consists in a superconducting gravimeter continuously measuring gravity changes at the surface of the RCL and an additional relative gravimeter installed in the underlying cave located 35 meters below the surface. While gravimeters are sensible to changes that occur in both the vadose zone and the saturated zone of the whole cave system, combining their recorded signals allows enhancing vadose zone's gravity changes. Finally, the surface ERT monitoring provide valuable information at the (sub)-meter scale on the
Ikin, Karen; Barton, Philip S; Stirnemann, Ingrid A; Stein, John R; Michael, Damian; Crane, Mason; Okada, Sachiko; Lindenmayer, David B
2014-01-01
Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1) How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2) Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3) Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha) over two time periods across a large (6,800 km(2)) agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities. PMID:24830684
Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes
NASA Astrophysics Data System (ADS)
Scafetta, N.
2014-07-01
Herein I propose a multi-scale dynamical analysis to facilitate the physical interpretation of tide gauge records. The technique uses graphical diagrams. It is applied to six secular-long tide gauge records representative of the world oceans: Sydney, Pacific coast of Australia; Fremantle, Indian Ocean coast of Australia; New York City, Atlantic coast of USA; Honolulu, US state of Hawaii; San Diego, US state of California; and Venice, Mediterranean Sea, Italy. For comparison, an equivalent analysis is applied to the Pacific Decadal Oscillation (PDO) index and to the Atlantic Multidecadal Oscillation (AMO) index. Finally, a global reconstruction of sea level (Jevrejeva et al. in Geophys Res Lett 35:L08715, 2008) and a reconstruction of the North Atlantic Oscillation (NAO) index (Luterbacher et al. in Geophys Res Lett 26:2745-2748, 1999) are analyzed and compared: both sequences cover about three centuries from 1700 to 2000. The proposed methodology quickly highlights oscillations and teleconnections among the records at the decadal and multidecadal scales. At the secular time scales tide gauge records present relatively small (positive or negative) accelerations, as found in other studies (Houston and Dean in J Coast Res 27:409-417, 2011). On the contrary, from the decadal to the secular scales (up to 110-year intervals) the tide gauge accelerations oscillate significantly from positive to negative values mostly following the PDO, AMO and NAO oscillations. In particular, the influence of a large quasi 60-70 year natural oscillation is clearly demonstrated in these records. The multiscale dynamical evolutions of the rate and of the amplitude of the annual seasonal cycle of the chosen six tide gauge records are also studied.
NASA Astrophysics Data System (ADS)
El Said, Bassam; Ivanov, Dmitry; Long, Andrew C.; Hallett, Stephen R.
2016-03-01
3D composite materials are characterized by complex internal yarn architectures, leading to complex deformation and failure development mechanisms. Net-shaped preforms, which are originally periodic in nature, lose their periodicity when the fabric is draped, deformed on a tool, and consolidated to create geometrically complex composite components. As a result, the internal yarn architecture, which dominates the mechanical behaviour, becomes dependent on the structural geometry. Hence, predicting the mechanical behaviour of 3D composites requires an accurate representation of the yarn architecture within structural scale models. When applied to 3D composites, conventional finite element modelling techniques are limited to either homogenised properties at the structural scale, or the unit cell scale for a more detailed material property definition. Consequently, these models fail to capture the complex phenomena occurring across multiple length scales and their effects on a 3D composite's mechanical response. Here a multi-scale modelling approach based on a 3D spatial Voronoi tessellation is proposed. The model creates an intermediate length scale suitable for homogenisation to deal with the non-periodic nature of the final material. Information is passed between the different length scales to allow for the effect of the structural geometry to be taken into account on the smaller scales. The stiffness and surface strain predictions from the proposed model have been found to be in good agreement with experimental results. The proposed modelling framework has been used to gain important insight into the behaviour of this category of materials. It has been observed that the strain and stress distributions are strongly dependent on the internal yarn architecture and consequently on the final component geometry. Even for simple coupon tests, the internal architecture and geometric effects dominate the mechanical response. Consequently, the behaviour of 3D woven
Multi-scale structural and tensile mechanical response of annulus fibrosus to osmotic loading.
Han, Woojin M; Nerurkar, Nandan L; Smith, Lachlan J; Jacobs, Nathan T; Mauck, Robert L; Elliott, Dawn M
2012-07-01
This study investigates differential multi-scale structure and function relationships of the outer and inner annulus fibrosus (AF) to osmotic swelling in different buffer solutions by quantifying tensile mechanics, glycoasamino-glycan(GAG) content, water content and tissue swelling, and collagen fibril ultrastructure. In the outer AF, the tensile modulus decreased by over 70% with 0.15 M PBS treatment but was unchanged with 2 M PBS treatment. Moreover, the modulus loss following 0.15 M PBS treatment was reversed when followed by 2 M PBS treatment, potentially from increased interfibrillar and interlamellar shearing associated with fibril swelling. In contrast, the inner AF tensile modulus was unchanged by 0.15 M PBS treatment and increased following 2 M treatment. Transmission electron microscopy revealed that the mean collagen fibril diameters of the untreated outer and inner AF were 87.8 ± 27.9 and 71.0 ± 26.9 nm, respectively. In the outer AF, collagen fibril swelling was observed with both 0.15 M and 2 M PBS treatments, but inherently low GAG content remained unchanged. In the inner AF, 2 M PBS treatment caused fibril swelling and GAG loss, suggesting that GAG plays a role in maintaining the structure of collagen fibrils leading to modulation of the native tissue mechanical properties. These results demonstrate important regional variations in structure and composition, and their influence on the heterogeneous mechanics of the AF. Moreover, because the composition and structure is altered as a consequence of progressive disk degeneration, quantification of these interactions is critical for study of the AF pathogenesis of degeneration and tissue engineering PMID:22314837
Bush Encroachment Mapping for Africa - Multi-Scale Analysis with Remote Sensing and GIS
NASA Astrophysics Data System (ADS)
Graw, V. A. M.; Oldenburg, C.; Dubovyk, O.
2015-12-01
Bush encroachment describes a global problem which is especially facing the savanna ecosystem in Africa. Livestock is directly affected by decreasing grasslands and inedible invasive species which defines the process of bush encroachment. For many small scale farmers in developing countries livestock represents a type of insurance in times of crop failure or drought. Among that bush encroachment is also a problem for crop production. Studies on the mapping of bush encroachment so far focus on small scales using high-resolution data and rarely provide information beyond the national level. Therefore a process chain was developed using a multi-scale approach to detect bush encroachment for whole Africa. The bush encroachment map is calibrated with ground truth data provided by experts in Southern, Eastern and Western Africa. By up-scaling location specific information on different levels of remote sensing imagery - 30m with Landsat images and 250m with MODIS data - a map is created showing potential and actual areas of bush encroachment on the African continent and thereby provides an innovative approach to map bush encroachment on the regional scale. A classification approach links location data based on GPS information from experts to the respective pixel in the remote sensing imagery. Supervised classification is used while actual bush encroachment information represents the training samples for the up-scaling. The classification technique is based on Random Forests and regression trees, a machine learning classification approach. Working on multiple scales and with the help of field data an innovative approach can be presented showing areas affected by bush encroachment on the African continent. This information can help to prevent further grassland decrease and identify those regions where land management strategies are of high importance to sustain livestock keeping and thereby also secure livelihoods in rural areas.
MULTI-SCALE MODELING AND APPROXIMATION ASSISTED OPTIMIZATION OF BARE TUBE HEAT EXCHANGERS
Bacellar, Daniel; Ling, Jiazhen; Aute, Vikrant; Radermacher, Reinhard; Abdelaziz, Omar
2014-01-01
Air-to-refrigerant heat exchangers are very common in air-conditioning, heat pump and refrigeration applications. In these heat exchangers, there is a great benefit in terms of size, weight, refrigerant charge and heat transfer coefficient, by moving from conventional channel sizes (~ 9mm) to smaller channel sizes (< 5mm). This work investigates new designs for air-to-refrigerant heat exchangers with tube outer diameter ranging from 0.5 to 2.0mm. The goal of this research is to develop and optimize the design of these heat exchangers and compare their performance with existing state of the art designs. The air-side performance of various tube bundle configurations are analyzed using a Parallel Parameterized CFD (PPCFD) technique. PPCFD allows for fast-parametric CFD analyses of various geometries with topology change. Approximation techniques drastically reduce the number of CFD evaluations required during optimization. Maximum Entropy Design method is used for sampling and Kriging method is used for metamodeling. Metamodels are developed for the air-side heat transfer coefficients and pressure drop as a function of tube-bundle dimensions and air velocity. The metamodels are then integrated with an air-to-refrigerant heat exchanger design code. This integration allows a multi-scale analysis of air-side performance heat exchangers including air-to-refrigerant heat transfer and phase change. Overall optimization is carried out using a multi-objective genetic algorithm. The optimal designs found can exhibit 50 percent size reduction, 75 percent decrease in air side pressure drop and doubled air heat transfer coefficients compared to a high performance compact micro channel heat exchanger with same capacity and flow rates.
Multi-Scale Model of Galactic Cosmic Ray Effects on the Hippocampus
NASA Astrophysics Data System (ADS)
Cucinotta, Francis
An important concern for risk assessment from galactic cosmic ray (GCR) exposures is impacts to the central nervous systems including changes in cognition, and associations with increased risk of Alzheimer’s disease (AD). AD, which affects about 50 percent of the population above age 80-yr, is a degenerative disease that worsens with time after initial onset leading to death, and has no known cure. AD is difficult to detect at early stages, and the small number of epidemiology studies that have considered the possibility have not identified an association with low dose radiation. However, experimental studies in transgenic mice suggest the possibility exits. We discuss modeling approaches to consider mechanisms whereby GCR would accelerate the occurrence of AD to earlier ages. Biomarkers of AD include Amyloid beta plaques, and neurofibrillary tangles (NFT) made up of aggregates of the hyper-phosphorylated form of the micro-tubule associated, tau protein. Related markers include synaptic degeneration, dendritic spine loss, and neuronal cell loss through apoptosis. GCR may affect these processes by causing oxidative stress, aberrant signaling following DNA damage, and chronic neuro-inflammation. Cell types considered in multi-scale models are neurons, astrocytes, and microglia. We developed biochemical and cell kinetics models of DNA damage signaling related to glycogen synthase kinase-3 beta and neuro-inflammation, and considered approaches to develop computer simulations of GCR induced cell interactions and their relationships to Amyloid beta plaques and NFTs. Comparison of model results to experimental data for the age specific development of plaques in transgenic mice and predictions of space radiation effects will be discussed.
HYPERstream: a multi-scale framework for streamflow routing in large-scale hydrological model
NASA Astrophysics Data System (ADS)
Piccolroaz, Sebastiano; Di Lazzaro, Michele; Zarlenga, Antonio; Majone, Bruno; Bellin, Alberto; Fiori, Aldo
2016-05-01
We present HYPERstream, an innovative streamflow routing scheme based on the width function instantaneous unit hydrograph (WFIUH) theory, which is specifically designed to facilitate coupling with weather forecasting and climate models. The proposed routing scheme preserves geomorphological dispersion of the river network when dealing with horizontal hydrological fluxes, irrespective of the computational grid size inherited from the overlaying climate model providing the meteorological forcing. This is achieved by simulating routing within the river network through suitable transfer functions obtained by applying the WFIUH theory to the desired level of detail. The underlying principle is similar to the block-effective dispersion employed in groundwater hydrology, with the transfer functions used to represent the effect on streamflow of morphological heterogeneity at scales smaller than the computational grid. Transfer functions are constructed for each grid cell with respect to the nodes of the network where streamflow is simulated, by taking advantage of the detailed morphological information contained in the digital elevation model (DEM) of the zone of interest. These characteristics make HYPERstream well suited for multi-scale applications, ranging from catchment up to continental scale, and to investigate extreme events (e.g., floods) that require an accurate description of routing through the river network. The routing scheme enjoys parsimony in the adopted parametrization and computational efficiency, leading to a dramatic reduction of the computational effort with respect to full-gridded models at comparable level of accuracy. HYPERstream is designed with a simple and flexible modular structure that allows for the selection of any rainfall-runoff model to be coupled with the routing scheme and the choice of different hillslope processes to be represented, and it makes the framework particularly suitable to massive parallelization, customization according to
NASA Astrophysics Data System (ADS)
McIntyre, Neil; Larsen, Josh; Reading, Lucy; Bulovic, Nevenka; Jarihani, Abdollah; Finch, Warren
2015-04-01
Groundwater recharge estimates are required to evaluate sustainable groundwater abstractions and to support groundwater impacts assessments associated with minerals and energy extraction. Increasingly, recharge estimates are also needed for regional and global scale water cycle modelling. This is especially the case in the great arid and semi-arid basins of the world due to increased water scarcity and dependence of ecosystems and livelihoods on their water supplies, and the considerable potential influence of groundwater on the hydrological cycle. Groundwater resources in the semi-arid Surat Basin of south-east Queensland, Australia, support extensive groundwater-dependent ecosystems and have historically been utilised for regional agriculture and urban water-use. Large volumes of water are currently being produced and will continue to do so as a part of coal seam gas extraction. There is considerable uncertainty about the impacts of gas extraction on water resources and the hydrological cycle, and much of this uncertainty stems from our limited knowledge about recharge processes and how to upscale them. Particular questions are about the role of storm events in controlling annual recharge, the relative contributions of local 'recharge zones' versus diffuse recharge and the translation of (relatively easily quantified) shallow drainage estimates to groundwater recharge. A multi-scale recharge research program is addressing these questions, using multiple approaches in estimating groundwater recharge, including plot and catchment scale monitoring, use of remote sensed data and simulation models. Results during the first year of the program have resulted in development of process hypotheses and experimental designs at three field sites representing key gaps in knowledge. The presentation will overview the process of designing the experimental program; how the results from these sites will be integrated with existing knowledge; and how results will be used to advance
GOSIM: A multi-scale iterative multiple-point statistics algorithm with global optimization
NASA Astrophysics Data System (ADS)
Yang, Liang; Hou, Weisheng; Cui, Chanjie; Cui, Jie
2016-04-01
Most current multiple-point statistics (MPS) algorithms are based on a sequential simulation procedure, during which grid values are updated according to the local data events. Because the realization is updated only once during the sequential process, errors that occur while updating data events cannot be corrected. Error accumulation during simulations decreases the realization quality. Aimed at improving simulation quality, this study presents an MPS algorithm based on global optimization, called GOSIM. An objective function is defined for representing the dissimilarity between a realization and the TI in GOSIM, which is minimized by a multi-scale EM-like iterative method that contains an E-step and M-step in each iteration. The E-step searches for TI patterns that are most similar to the realization and match the conditioning data. A modified PatchMatch algorithm is used to accelerate the search process in E-step. M-step updates the realization based on the most similar patterns found in E-step and matches the global statistics of TI. During categorical data simulation, k-means clustering is used for transforming the obtained continuous realization into a categorical realization. The qualitative and quantitative comparison results of GOSIM, MS-CCSIM and SNESIM suggest that GOSIM has a better pattern reproduction ability for both unconditional and conditional simulations. A sensitivity analysis illustrates that pattern size significantly impacts the time costs and simulation quality. In conditional simulations, the weights of conditioning data should be as small as possible to maintain a good simulation quality. The study shows that big iteration numbers at coarser scales increase simulation quality and small iteration numbers at finer scales significantly save simulation time.
Simulations of Ecosystem Hydrological Processes Using a Unified Multi-Scale Model
Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin; Hinkle, Ross; Li, Hongyi; Bailey, Vanessa L.; Bond-Lamberty, Benjamin
2015-01-24
This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling of hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.
PUPIL: A systematic approach to software integration in multi-scale simulations
NASA Astrophysics Data System (ADS)
Torras, Juan; He, Yao; Cao, Chao; Muralidharan, Krishna; Deumens, E.; Cheng, H.-P.; Trickey, S. B.
2007-08-01
We present a relatively straightforward way to integrate existing software packages into a full multi-scale simulation package in which each application runs in its own address space and there is no run-time intervention by the researcher. The PUPIL (Program for User Package Interfacing and Linking) architectural concept is to provide a simulation Supervisor, implemented as a Manager and various Workers which involve small wrapper interfaces written and installed within each application package and various communication services. The different, autonomous packages ("Calculation Units") are plugged into the PUPIL system which one then operates as a software driver for them. Well-defined protocols are provided for communication between the different Calculation Units and the PUPIL system. The CORBA communication protocol is used to exchange information between running processes. All simulation directives from the user are stored in an XML file that is interpreted by the PUPIL Manager and Workers. An initial version has been designed using the Object Oriented (OO) paradigm and implemented in Java as a fast prototyping language. Tests of implementation ease and of operational correctness (on toy physical systems) have been carried out. In the former category, we document how interfaces to both DL_POLY and SIESTA were done relatively straightforwardly. In the latter category, the most demanding test was the joining of three different packages to do a MD calculation with pattern recognition to identify the QM-forces region and an external QM force calculation. The results show that PUPIL provides ease of operation and maintenance with little overhead.
Path planning in multi-scale ocean flows: Coordination and dynamic obstacles
NASA Astrophysics Data System (ADS)
Lolla, T.; Haley, P. J., Jr.; Lermusiaux, P. F. J.
2015-10-01
As the concurrent use of multiple autonomous vehicles in ocean missions grows, systematic control for their coordinated operation is becoming a necessity. Many ocean vehicles, especially those used in longer-range missions, possess limited operating speeds and are thus sensitive to ocean currents. Yet, the effect of currents on their trajectories is ignored by many coordination techniques. To address this issue, we first derive a rigorous level-set methodology for distance-based coordination of vehicles operating in minimum time within strong and dynamic ocean currents. The new methodology integrates ocean modeling, time-optimal level-sets and optimization schemes to predict the ocean currents, the short-term reachability sets, and the optimal headings for the desired coordination. Schemes are developed for dynamic formation control, where multiple vehicles achieve and maintain a given geometric pattern as they carry out their missions. To do so, a new score function that is suitable for regular polygon formations is obtained. Secondly, we obtain an efficient, non-intrusive technique for level-set-based time-optimal path planning in the presence of moving obstacles. The results are time-optimal path forecasts that rigorously avoid moving obstacles and sustain the desired coordination. They are exemplified and investigated for a variety of simulated ocean flows. A wind-driven double-gyre flow is used to study time-optimal dynamic formation control. Currents exiting an idealized strait or estuary are employed to explore dynamic obstacle avoidance. Finally, results are analyzed for the complex geometry and multi-scale ocean flows of the Philippine Archipelago.
Multi-scale modeling of the structure and dynamics of macromolecules
NASA Astrophysics Data System (ADS)
Serohijos, Adrian Wendil R.
Biology is defined by phenomena that are inherently complex spanning multiple length and time scales. To understand these processes, there is a need for multi-scale approaches that provide a coherent framework for describing and interrogating these phenomena. Here, we employ multiple approaches to investigate specific biological systems. The first system we studied was the cytoplasmic dynein motor, a protein that walks along the microtubule tracks in cells. The major objective in the dynein motors field is to understand its mechanism. Specifically, what is dynein's structure and how does it transduce chemical energy into mechanical work? We proposed a theoretical structural model of the motor and performed normal mode analysis and molecular dynamics on the motor unit structure. These studies hypothesized new structural features in the dynein motor unit and proposed a potential mechanism for energy transduction [5,6,80]. The second system we studied was the CFTR channel, which regulates ion transport in the apical membrane of epithelial cells. Mutations in the CFTR protein are the basis of the cystic fibosis disease. One of the primary question is how a single residue deletion (Phe508) lead to ˜90% of cystic fibrosis cases. We performed molecular dynamics simulation of the first nucleotide-binding domain of CFTR and showed that the wild type and mutant exhibit a difference in their folding kinetics, in agreement with experiments. These simulations also determined the potential structural origin of this misfolding defect. We also proposed a complete model of the CFTR channel to identify the location of the Phe508 residue in the whole protein. This result is important in understanding another aspect of the DeltaF508 defect, which is the misassembly of the whole CFTR protein during its biosynthesis.
A multi-scale structural study of the porcine anterior cruciate ligament tibial enthesis
Zhao, Lei; Thambyah, Ashvin; Broom, Neil D
2014-01-01
Like the human anterior cruciate ligament (ACL), the porcine ACL also has a double bundle structure and several biomechanical studies using this model have been carried out to show the differential effect of these two bundles on macro-level knee joint function. It is hypothesised that if the different bundles of the porcine ACL are mechanically distinct in function, then a multi-scale anatomical characterisation of their individual enthesis will also reveal significant differences in structure between the bundles. Twenty-two porcine knee joints were cleared of their musculature to expose the intact ACL following which ligament–bone samples were obtained. The samples were fixed in formalin followed by decalcification with formic acid. Thin sections containing the ligament insertion into the tibia were then obtained by cryosectioning and analysed using differential interference contrast (DIC) optical microscopy and scanning electron microscopy (SEM). At the micro-level, the anteromedial (AM) bundle insertion at the tibia displayed a significant deep-rooted interdigitation into bone, while for the posterolateral (PL) bundle the fibre insertions were less distributed and more focal. Three sub-types of enthesis were identified in the ACL and related to (i) bundle type, (ii) positional aspect within the insertion, and (iii) specific bundle function. At the nano-level the fibrils of the AM bundle were significantly larger than those in the PL bundle. The modes by which the AM and PL fibrils merged with the bone matrix fibrils were significantly different. A biomechanical interpretation of the data suggests that the porcine ACL enthesis is a specialized, functionally graded structural continuum, adapted at the micro-to-nano scales to serve joint function at the macro level. PMID:24697495
Improved color reproduction based on CIELAB color space in integrated multi-scale retinex
NASA Astrophysics Data System (ADS)
Kyung, Wang-Jun; Lee, Tae-Hyoung; Lee, Cheol-Hee; Ha, Yeong-Ho
2009-01-01
Recently, tone reproduction is widely used in the field of image enhancement and HDR imaging. This method is especially used to provide the proper luminance so that captured images give the same sensation as the scene. As a result, we can get high contrast and naturalness of colors. There is ample literature on the topic of tone reproduction that has the objective of reproducing natural looking color in digital images. In recent papers, IMSR (Integrated multi-scale Retinex) shows great naturalness in the result images. Most methods, including IMSR, work in RGB or quasi-RGB color spaces, although some method adopted the use of luminance. This raises hue distortion from the point of the human visual system, that is, hue distortion in CIELAB color space. Accordingly, this paper proposes an enhanced IMSR method in a device-independent color space, CIELAB, to preserve hue and obtain high contrast and naturalness. In order to achieve the devised objectives, a captured sRGB image is transformed to the CIELAB color space. IMSR is then applied to only L* values, thus the balance of colors components are preserved. This process causes unnatural saturation, therefore saturation adjustment is performed by applying the ratio of chroma variation at the sRGB gamut boundary according to the corrected luminance. Finally, the adjusted CIELAB values are transformed to sRGB using the inverse transform function. In the result images of the proposed method, containing both high and low luminance regions, visibility in dark shadow and bright regions was improved and color distortion was reduced.
Understanding protected area resilience: a multi-scale, social-ecological approach
Cumming, Graeme S.; Allen, Craig R.; Ban, Natalie C.; Biggs, Duan; Biggs, Harry C.; Cumming, David H.M; De Vos, Alta; Epstein, Graham; Etienne, Michel; Maciejewski, Kristine; Mathevet, Raphael; Moore, Christine; Nenadovic, Mateja; Schoon, Michael
2015-01-01
Protected areas (PAs) remain central to the conservation of biodiversity. Classical PAs were conceived as areas that would be set aside to maintain a natural state with minimal human influence. However, global environmental change and growing cross-scale anthropogenic influences mean that PAs can no longer be thought of as ecological islands that function independently of the broader social-ecological system in which they are located. For PAs to be resilient (and to contribute to broader social-ecological resilience), they must be able to adapt to changing social and ecological conditions over time in a way that supports the long-term persistence of populations, communities, and ecosystems of conservation concern. We extend Ostrom's social-ecological systems framework to consider the long-term persistence of PAs, as a form of land use embedded in social-ecological systems, with important cross-scale feedbacks. Most notably, we highlight the cross-scale influences and feedbacks on PAs that exist from the local to the global scale, contextualizing PAs within multi-scale social-ecological functional landscapes. Such functional landscapes are integral to understand and manage individual PAs for long-term sustainability. We illustrate our conceptual contribution with three case studies that highlight cross-scale feedbacks and social-ecological interactions in the functioning of PAs and in relation to regional resilience. Our analysis suggests that while ecological, economic, and social processes are often directly relevant to PAs at finer scales, at broader scales, the dominant processes that shape and alter PA resilience are primarily social and economic.
Ikin, Karen; Barton, Philip S.; Stirnemann, Ingrid A.; Stein, John R.; Michael, Damian; Crane, Mason; Okada, Sachiko; Lindenmayer, David B.
2014-01-01
Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1) How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2) Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3) Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha) over two time periods across a large (6,800 km2) agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricu