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...
MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION
The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...
This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...
He, S.; Vukovich, F. M.; Ching, J.; Gilliland, A.
2002-05-01
Models-3/CMAQ system is designed to provide a comprehensive and flexible modeling tool for states and other government agencies, and for scientific studies. The current setting of initial concentrations and boundary condition (ICBC) of air species for CMAQ system represents clean ambient condition in the eastern-half of the US, and as such. The ozone ICBC differed from observational values, significantly at upper troposphere. Because of the stratosphere-troposphere exchange, the upper troposphere may contain high concentrations of ozone (hundreds of ppbv). However the current ICBC artificially set ozone level as 70ppbv in upper troposphere throughout model domain. The large difference of standard ozone ICBC from realistic situation becomes considerable uncertainty source of CMAQ system. The purpose of this research is to improve ICBC setting for Models-3/CMAQ modeling system, and to assess the influence of introducing stratospheric ozone into troposphere on regional and urban air quality and on the tropospheric ozone budget. The approach taken is to perform a series of sensitivity studies on ICBC with CMAQ. The simulation covers the entire US with 108km grid resolution from July 2 to 12 of 1988. The domain divide in 34 layers vertically up to 40mbar. In addition to the base case with standard ICBC, ozone initial concentration and boundary condition are generated based on ozone climatology (Logan, 1999), which was derived from surface, satellite, and ozonesonde data across the globe. This new ICBC enables CMAQ model to study ozone cross-tropopause flux transporting to lower troposphere, and to analyze the impact of intercontinental ozone transport. The tropospheric ozone residue (TOR) data is used to compare with modeling tropospheric ozone budget for evaluation of CMAQ performance. Since ozone climatology was based on observation, the derived ozone ICBC are in better agreement with the ``real'' atmosphere than standard ICBC. CMAQ simulations with ozone climatology
Multiscale Modeling of Microbial Communities
Blanchard, Andrew
Although bacteria are single-celled organisms, they exist in nature primarily in the form of complex communities, participating in a vast array of social interactions through regulatory gene networks. The social interactions between individual cells drive the emergence of community structures, resulting in an intricate relationship across multiple spatiotemporal scales. Here, I present my work towards developing and applying the tools necessary to model the complex dynamics of bacterial communities. In Chapter 2, I utilize a reaction-diffusion model to determine the population dynamics for a population with two species. One species (CDI+) utilizes contact dependent inhibition to kill the other sensitive species (CDI-). The competition can produce diverse patterns, including extinction, coexistence, and localized aggregation. The emergence, relative abundance, and characteristic features of these patterns are collectively determined by the competitive benefit of CDI and its growth disadvantage for a given rate of population diffusion. The results provide a systematic and statistical view of CDI-based bacterial population competition, expanding the spectrum of our knowledge about CDI systems and possibly facilitating new experimental tests for a deeper understanding of bacterial interactions. In the following chapter, I present a systematic computational survey on the relationship between social interaction types and population structures for two-species communities by developing and utilizing a hybrid computational framework that combines discrete element techniques with reaction-diffusion equations. The impact of deleterious and beneficial interactions on the community are quantified. Deleterious interactions generate an increased variance in relative abundance, a drastic decrease in surviving lineages, and a rough expanding front. In contrast, beneficial interactions contribute to a reduced variance in relative abundance, an enhancement in lineage number, and a
Covariance, correlation matrix, and the multiscale community structure of networks.
Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing
2010-07-01
Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.
Blending science and community voices for multi-scale disaster risk ...
African Journals Online (AJOL)
Blending science and community voices for multi-scale disaster risk reduction and climate ... and local government development planning, hence continuity of the process. ... Key Words: Climate change, Disaster risk management, Pastoralism, ...
Description and evaluation of the Community Multiscale Air ...
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced
Evaluation of the Community Multiscale Air Quality model version 5.1
The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...
Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model
Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...
Incremental Testing of the Community Multiscale Air Quality (CMAQ) Modeling System Version 4.7
This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to obse...
The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O3, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...
The adaptation of the Community Multiscale Air Quality (CMAQ) modeling system to simulate O3, particulate matter, and related precursor distributions over the northern hemisphere is presented. Hemispheric simulations with CMAQ and the Weather Research and Forecasting (...
Diagnosing Disaster Resilience of Communities as Multi-scale Complex Socio-ecological Systems
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.
Community structure in time-dependent, multiscale, and multiplex networks.
Mucha, Peter J; Richardson, Thomas; Macon, Kevin; Porter, Mason A; Onnela, Jukka-Pekka
2010-05-14
Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.
Using Ants as bioindicators: Multiscale Issues in Ant Community Ecology
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Alan Andersen
1997-06-01
Full Text Available Ecological patterns and processes are characteristically scale dependent, and research findings often cannot be translated easily from one scale to another. Conservation biology is challenged by a lack of congruence between the spatial scales of ecological research (typically involving small plots and land management (typically involving whole landscapes. Here, I discuss spatial scaling issues as they relate to an understanding of ant communities and, consequently, their use as bioindicators in land management. Our perceptions of fundamental patterns and processes in ant communities depend on scale: taxa that are behaviorally dominant at one scale are not necessarily so at others, functional groups recognized at one scale are often inappropriate for others, and the role of competition in community structure depends on the scale of analysis. Patterns of species richness and composition, and the ability of total richness to be estimated by surrogates, are all also scale dependent. Ant community ecology has a tradition of detailed studies in small plots, but the use of ants as bioindicators requires a predictive understanding of community structure and dynamics at a range of spatial scales. Such an appreciation of ant communities and their most effective use as bioindicators is best served by studies integrating results from plot-scale research with the broad-scale paradigms of biogeography, systematics, and evolutionary biology.
Multi-scale analysis of the European airspace using network community detection.
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Gérald Gurtner
Full Text Available 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.
Multi-scale analysis of the European airspace using network community detection
Gurtner, Gérald; Cipolla, Marco; Lillo, Fabrizio; Mantegna, Rosario Nunzio; Miccichè, Salvatore; Pozzi, Simone
2013-01-01
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 airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, 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.
Directory of Open Access Journals (Sweden)
David Barton Bray
2012-08-01
Full Text Available Some important elements of common property theory include a focus on individual communities or user groups, local level adjudication of conflicts, local autonomy in rule making, physical harvests, and low levels of articulation with markets. We present a case study of multi-scale collective action around indigenous/community conserved areas (ICCAs in Oaxaca, Mexico that suggests a modification of these components of common property theory. A multi-community ICCA in Oaxaca demonstrates the importance of inter-community collective action as key link in multi-scale governance, that conflicts are often negotiated in multiple arenas, that rules emerge at multiple scales, and that management for conservation and environmental services implies no physical harvests. Realizing economic gains from ICCAs for strict conservation may require something very different than traditional natural resource management. It requires intense engagement with extensive networks of government and civil society actors and new forms of community and inter-community collection action, or multi-scale governance. Multi-scale governance is built on trust and social capital at multiple scales and also constitutes collective action at multiple scales. However, processes of multi-scale governance are also necessarily “turbulent” with actors frequently having conflicting values and goals to be negotiated. We present an analytic history of the process of emergence of community and inter-community collective action around strict conservation and examples of internal and external turbulence. We argue that this case study and other literature requires an extensions of the constitutive elements of common property theory.
Malanson, George P.; Zimmerman, Dale L.; Kinney, Mitch; Fagre, Daniel B.
2017-01-01
Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.
Crops in silico: A community wide multi-scale computational modeling framework of plant canopies
Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.
2016-12-01
Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem
Incremental testing of the Community Multiscale Air Quality (CMAQ modeling system version 4.7
Directory of Open Access Journals (Sweden)
K. M. Foley
2010-03-01
Full Text Available This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ modeling system version 4.7 (v4.7 and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a updates to the heterogeneous N_{2}O_{5} parameterization, (b improvement in the treatment of secondary organic aerosol (SOA, (c inclusion of dynamic mass transfer for coarse-mode aerosol, (d revisions to the cloud model, and (e new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM_{2.5} is dominated by overpredictions of unspeciated PM_{2.5} (PM_{other} in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.
Incremental testing of the community multiscale air quality (CMAQ modeling system version 4.7
Directory of Open Access Journals (Sweden)
K. M. Foley
2009-10-01
Full Text Available This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ modeling system version 4.7 (v4.7 and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a updates to the heterogeneous N_{2}O_{5} parameterization, (b improvement in the treatment of secondary organic aerosol (SOA, (c inclusion of dynamic mass transfer for coarse-mode aerosol, (d revisions to the cloud model, and (e new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM_{2.5} is dominated by overpredictions of unspeciated PM_{2.5} (PM_{other} in the winter and by underpredictions of carbon in the summer. The CMAQ v4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.
Schaub, Michael T; Delvenne, Jean-Charles; Yaliraki, Sophia N; Barahona, Mauricio
2012-01-01
multiscale structure of non clique-like communities is revealed.
Wyat Appel, K.; Napelenok, Sergey L.; Foley, Kristen M.; Pye, Havala O. T.; Hogrefe, Christian; Luecken, Deborah J.; Bash, Jesse O.; Roselle, Shawn J.; Pleim, Jonathan E.; Foroutan, Hosein; Hutzell, William T.; Pouliot, George A.; Sarwar, Golam; Fahey, Kathleen M.; Gantt, Brett; Gilliam, Robert C.; Heath, Nicholas K.; Kang, Daiwen; Mathur, Rohit; Schwede, Donna B.; Spero, Tanya L.; Wong, David C.; Young, Jeffrey O.
2017-04-01
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2. 5 bias (PM2. 5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2. 5 on average in January and July. Overall, the seasonal variation in simulated PM2. 5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2. 5
Deisboeck, Thomas S; Wang, Zhihui; Macklin, Paul; Cristini, Vittorio
2011-08-15
Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insights in the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community.
Xie, Shilin; Lu, Fei; Cao, Lei; Zhou, Weiqi; Ouyang, Zhiyun
2016-07-01
Understanding the factors that influence the characteristics of avian communities using urban parks at both the patch and landscape level is important to focus management effort towards enhancing bird diversity. Here, we investigated this issue during the breeding season across urban parks in Beijing, China, using high-resolution satellite imagery. Fifty-two bird species were recorded across 29 parks. Analysis of residence type of birds showed that passengers were the most prevalent (37%), indicating that Beijing is a major node in the East Asian–Australasian Flyway. Park size was crucial for total species abundance, but foliage height diversity was the most important factor influencing avian species diversity. Thus, optimizing the configuration of vertical vegetation structure in certain park areas is critical for supporting avian communities in urban parks. Human visitation also showed negative impact on species diversity. At the landscape level, the percentage of artificial surface and largest patch index of woodland in the buffer region significantly affected total species richness, with insectivores and granivores being more sensitive to the landscape pattern of the buffer region. In conclusion, urban birds in Beijing are influenced by various multi-scale factors; however, these effects vary with different feeding types.
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D. CABANA
2017-03-01
Full Text Available Benthic macroinvertebrate communities form the basis of the intricate lagoonal food web. Understanding their functional and taxonomic response, from a β-diversity perspective, is essential to disclose underlying patterns with potential applicability in conservation and management actions. Within the central lagoon of Messolonghi we studied the main environmental components structuring the macroinvertebrate community. We analyzed the β-taxonomic and β-functional diversity across the main habitats and seasons, over a year time frame. Our results outline habitat type and vegetation biomass as the major factors structuring the communities. We found environmental variability to have a positive correlation with functional β-diversity, however no correlation was found with taxonomic β-diversity. Across the seasons an asynchronous response of the functional and taxonomic β-diversity was identified. The taxonomic composition displayed significant heterogeneity during the driest period and the functional during the rainy season. Across the habitats the unvegetated presented higher taxonomic homogeneity and functionally heterogeneity, contrary the vegetated habitats present higher taxonomic variability and functional homogeneity. Across the seasons and habitats a pattern of functional redundancy and taxonomic replacement was identified. Besides high functional turnover versus low taxonomic turnover was documented in an anthropogenic organically enriched habitat We conclude that habitats display independent functional and taxonomic seasonal patterns, thus different processes may contribute to their variability. The framework presented here highlights the importance of studying both β-diversity components framed in a multiscale approach to better understand ecological processes and variability patterns. These results are important to understand macroinvertebrate community assembly processes and are valuable for conservation purposes.
Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.
2011-01-01
Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.
Reyes, Jeanette M.; Xu, Yadong; Vizuete, William; Serre, Marc L.
2017-01-01
The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 μm (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.
Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.
2016-01-01
Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.
Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.
2016-09-01
Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.
Community Multi-scale Air Quality (CMAQ) Modeling System for Air Quality Management
CMAQ simultaneously models multiple air pollutants including ozone, particulate matter and a variety of air toxics to help air quality managers determine the best air quality management scenarios for their communities, regions and states.
Coding of Markov dynamics for multiscale community detection in complex networks
Schaub, Michael T; Barahona, Mauricio
2011-01-01
The detection of community structure in complex networks is intimately related to the problem of finding a concise description of the network in terms of its modules. This notion has been recently exploited by the Map equation formalism (M. Rosvall and C. T. Bergstrom, PNAS, vol. 105, no. 4, pp. 1118-1123, 2008) through an information-theoretic characterization of the process of coding the transitions of a random walker inside and between communities at stationarity. However, a thorough consideration of the relationship between a time-evolving Markov dynamics and the coding mechanism is still lacking. We show that the original one-step coding scheme used by the Map equation method neglects the internal structure of the communities and introduces an upper scale, the 'field-of-view' limit, for the communities that it can detect. Although the Map equation method is known for its good performance on clique-like graphs, the field-of-view limit can result in undesirable overpartitioning when communities are far fro...
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S. F. Mueller
2010-05-01
Full Text Available A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE emissions processing system currently estimates non-methane volatile organic compound (NMVOC emissions from biogenic sources, nitrogen oxide (NOx emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide, 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide, 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride, and 84% of fine particles (i.e., those smaller than 2.5 μm in size released into the
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S. N. Smith
2010-01-01
Full Text Available A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE emissions processing system currently estimates volatile organic compound (VOC emissions from biogenic sources, nitrogen oxide (NO_{x} emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide, 44% of total NO_{x}, 80% of reactive carbonaceous gases (VOCs and carbon monoxide, 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride, and 84% of fine particles (i.e., those smaller than 2.5 μm in size released into the
Smith, S. N.; Mueller, S. F.
2010-05-01
A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere
Smith, S. N.; Mueller, S. F.
2010-01-01
A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates volatile organic compound (VOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as windblown dust and sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (VOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and
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B. Gantt
2015-05-01
Full Text Available Sea spray aerosols (SSA impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Despite their importance, the emission magnitude of SSA remains highly uncertain with global estimates varying by nearly two orders of magnitude. In this study, the Community Multiscale Air Quality (CMAQ model was updated to enhance fine mode SSA emissions, include sea surface temperature (SST dependency, and reduce coastally-enhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several regional and national observational datasets in the continental US. The updated emissions generally reduced model underestimates of sodium, chloride, and nitrate surface concentrations for an inland site of the Bay Regional Atmospheric Chemistry Experiment (BRACE near Tampa, Florida. Including SST-dependency to the SSA emission parameterization led to increased sodium concentrations in the southeast US and decreased concentrations along parts of the Pacific coast and northeastern US. The influence of sodium on the gas-particle partitioning of nitrate resulted in higher nitrate particle concentrations in many coastal urban areas due to increased condensation of nitric acid in the updated simulations, potentially affecting the predicted nitrogen deposition in sensitive ecosystems. Application of the updated SSA emissions to the California Research at the Nexus of Air Quality and Climate Change (CalNex study period resulted in modest improvement in the predicted surface concentration of sodium and nitrate at several central and southern California coastal sites. This SSA emission update enabled a more realistic simulation of the atmospheric chemistry in environments where marine air mixes with urban pollution.
Intercomparison of the community multiscale air quality model and CALGRID using process analysis.
O'Neill, Susan M; Lamb, Brian K
2005-08-01
This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit
Hao, Hua; Chang, Howard H.; Holmes, Heather A.; Mulholland, James A.; Klein, Mitch; Darrow, Lyndsey A.; Strickland, Matthew J.
2015-01-01
Background: Previous epidemiologic studies suggest associations between preterm birth and ambient air pollution. Objective: We investigated associations between 11 ambient air pollutants, estimated by combining Community Multiscale Air Quality model (CMAQ) simulations with measurements from stationary monitors, and risk of preterm birth (Darrow LA, Strickland MJ. 2016. Air pollution and preterm birth in the U.S. state of Georgia (2002–2006): associations with concentrations of 11 ambient air pollutants estimated by combining Community Multiscale Air Quality Model (CMAQ) simulations with stationary monitor measurements. Environ Health Perspect 124:875–880; http://dx.doi.org/10.1289/ehp.1409651 PMID:26485731
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J. T. Kelly
2010-04-01
Full Text Available Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-salt particles from the coastal surf zone is known to be elevated compared to that from the open ocean. Despite the importance of sea-salt emissions and chemical processing, the US EPA's Community Multiscale Air Quality (CMAQ model has traditionally treated coarse sea-salt particles as chemically inert and has not accounted for enhanced surf-zone emissions. In this article, updates to CMAQ are described that enhance sea-salt emissions from the coastal surf zone and allow dynamic transfer of HNO_{3}, H_{2}SO_{4}, HCl, and NH_{3} between coarse particles and the gas phase. Predictions of updated CMAQ models and the previous release version, CMAQv4.6, are evaluated using observations from three coastal sites during the Bay Regional Atmospheric Chemistry Experiment (BRACE in Tampa, FL in May 2002. Model updates improve predictions of NO_{3}^{−}, SO_{4}^{2−}, NH_{4}^{+}, Na^{+}, and Cl^{−} concentrations at these sites with only a 8% increase in run time. In particular, the chemically interactive coarse particle mode dramatically improves predictions of nitrate concentration and size distributions as well as the fraction of total nitrate in the particle phase. Also, the surf-zone emission parameterization improves predictions of total sodium and chloride concentration. Results of a separate study indicate that the model updates reduce the mean absolute error of nitrate predictions at coastal CASTNET and SEARCH sites in the eastern US. Although the new model features improve performance relative to CMAQv4.6, some persistent differences exist between observations and predictions
Directory of Open Access Journals (Sweden)
J. T. Kelly
2009-12-01
Full Text Available Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-salt particles from the coastal surf zone is known to be elevated compared to that from the open ocean. Despite the importance of sea-salt emissions and chemical processing, the US EPA's Community Multiscale Air Quality (CMAQ model has traditionally treated coarse sea-salt particles as chemically inert and has not accounted for enhanced surf-zone emissions. In this article, updates to CMAQ are described that enhance sea-salt emissions from the coastal surf zone and allow dynamic transfer of HNO_{3}, H_{2}SO_{4}, HCl, and NH_{3} between coarse particles and the gas phase. Predictions of updated CMAQ models and the previous release version, CMAQv4.6, are evaluated using observations from three coastal sites during the Bay Regional Atmospheric Chemistry Experiment (BRACE in Tampa, FL in May 2002. Model updates improve predictions of NO_{3}^{−}, SO_{4}^{2−}, NH_{4}^{+}, Na^{+}, and Cl^{−} concentrations at these sites with only a 8% increase in run time. In particular, the chemically interactive coarse particle mode dramatically improves predictions of nitrate concentration and size distributions as well as the fraction of total nitrate in the particle phase. Also, the surf-zone emission parameterization improves predictions of total sodium and chloride concentration. Results of a separate study indicate that the model updates reduce the mean absolute error of nitrate predictions at coastal CASTNET and SEARCH sites in the eastern US. Although the new model features improve performance relative to CMAQv4.6, some persistent differences exist between observations and predictions
Kelly, J. T.; Bhave, P. V.; Nolte, C. G.; Shankar, U.; Foley, K. M.
2010-04-01
Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-salt particles from the coastal surf zone is known to be elevated compared to that from the open ocean. Despite the importance of sea-salt emissions and chemical processing, the US EPA's Community Multiscale Air Quality (CMAQ) model has traditionally treated coarse sea-salt particles as chemically inert and has not accounted for enhanced surf-zone emissions. In this article, updates to CMAQ are described that enhance sea-salt emissions from the coastal surf zone and allow dynamic transfer of HNO3, H2SO4, HCl, and NH3 between coarse particles and the gas phase. Predictions of updated CMAQ models and the previous release version, CMAQv4.6, are evaluated using observations from three coastal sites during the Bay Regional Atmospheric Chemistry Experiment (BRACE) in Tampa, FL in May 2002. Model updates improve predictions of NO3-, SO42-, NH4+, Na+, and Cl- concentrations at these sites with only a 8% increase in run time. In particular, the chemically interactive coarse particle mode dramatically improves predictions of nitrate concentration and size distributions as well as the fraction of total nitrate in the particle phase. Also, the surf-zone emission parameterization improves predictions of total sodium and chloride concentration. Results of a separate study indicate that the model updates reduce the mean absolute error of nitrate predictions at coastal CASTNET and SEARCH sites in the eastern US. Although the new model features improve performance relative to CMAQv4.6, some persistent differences exist between observations and predictions. Modeled sodium concentration is biased low and causes under-prediction of coarse particle nitrate. Also, CMAQ over-predicts geometric mean diameter and
Betzel, Richard F
2016-01-01
The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its alteration in disease or injury. Traditional tools and approaches to study this architecture have largely focused on single scales -- of topology, time, and space. Expanding beyond this narrow view, we focus this review on pertinent questions and novel methodological advances for the multi-scale brain. We separate our exposition into content related to multi-scale topological structure, multi-scale temporal structure, and multi-scale spatial structure. In each case, we recount empirical evidence for such structures, survey network-based methodological approaches to reveal these structures, and outline current frontiers and open questions. Although predominantly peppered with examples from human neuroimaging, we hope that this account will offer an accessible guide to any neuros...
Like most air quality modeling systems, CMAQ divides the treatment of meteorological and chemical/transport processes into separate models run sequentially. A potential drawback to this approach is that it creates the illusion that these processes are minimally interdependent an...
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S. F. Mueller
2011-01-01
Full Text Available The Community Multiscale Air Quality (CMAQ model version 4.6 has been revised with regard to the representation of chlorine (HCl, ClNO_{2} and sulfur (dimethylsulfide, or DMS, and H_{2}S, and evaluated against observations and earlier published models. Chemistry parameterizations were based on published reaction kinetic data and a recently developed cloud chemistry model that includes heterogeneous reactions of organic sulfur compounds. Evaluation of the revised model was conducted using a recently enhanced data base of natural emissions that includes ocean and continental sources of DMS, H_{2}S, chlorinated gases and lightning NO_{x} for the continental United States and surrounding regions. Results using 2002 meteorology and emissions indicated that most simulated "natural" (plus background chemical and aerosol species exhibit the expected seasonal variations at the surface. Ozone exhibits a winter and early spring maximum consistent with ozone data and an earlier published model. Ozone distributions reflect the influences of atmospheric dynamics and pollutant background levels imposed on the CMAQ simulation by boundary conditions derived from a global model. A series of model experiments reveals that the consideration of gas-phase organic sulfur chemistry leads to sulfate aerosol increases over most of the continental United States. Cloud chemistry parameterization changes result in widespread decreases in SO_{2} across the modeling domain and both increases and decreases in sulfate. Most cloud-mediated sulfate increases occurred mainly over the Pacific Ocean (up to about 0.1 μg m^{−3} but also over and downwind from the Gulf of Mexico (including parts of the eastern US. Geographic variations in simulated SO_{2} and sulfate are due to the link between DMS/H_{2}S and their byproduct SO_{2}, the heterogeneity of cloud cover and precipitation (precipitating clouds act as
Directory of Open Access Journals (Sweden)
S. F. Mueller
2010-06-01
Full Text Available A recent version (4.6 of the Community Multiscale Air Quality (CMAQ model was used as the basis for testing model revisions for including reactions involving chlorine (HCl, ClNO_{2} and reduced sulfur (dimethylsulfide, or DMS, and H_{2}S species not normally treated in the CB05 gas chemical mechanism and cloud chemistry module. Model chemistry revisions were based on published reaction kinetic data and a recent cloud chemistry model that includes heterogeneous reactions of organic sulfur compounds. Testing of the revised model was conducted using a recently enhanced data base of natural emissions that includes ocean and continental sources of DMS, H_{2}S, chlorinated gases and lightning NO_{x} for the continental United States and surrounding regions. Results using 2002 meteorology and emissions indicated that most simulated chemical and aerosol species exhibit the expected seasonal variations in grid-average surface concentrations. Ozone exhibits a winter and early spring maximum – reasonably consistent with ozone data and model results produced by others – in a pattern that reflects the influences of atmospheric dynamics and pollutant background levels imposed on the CMAQ simulation by boundary conditions derived from a global model. A series of experimental model simulations reveals that the addition of gas phase organic sulfur chemistry leads to sulfate aerosol increases over most of the continental United States. Modifications to the cloud chemistry module result in widespread decreases in SO_{2} across the modeling domain and a mix of sulfate increases and decreases. Most cloud-mediated sulfate increases occurred over the Pacific Ocean (up to about 0.1 μg m^{-3} and at slightly lesser amounts over and downwind from the Gulf of Mexico (including portions of the Eastern US. Variations in the chemical response are due to the link between DMS/H_{2}S and their byproduct SO_{2 }
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Ana Belén Petro
2014-04-01
Full Text Available While the retinex theory aimed at explaining human color perception, its derivations have led to efficient algorithms enhancing local image contrast, thus permitting among other features, to "see in the shadows". Among these derived algorithms, Multiscale Retinex is probably the most successful center-surround image filter. In this paper, we offer an analysis and implementation of Multiscale Retinex. We point out and resolve some ambiguities of the method. In particular, we show that the important color correction final step of the method can be seriously improved. This analysis permits to come up with an automatic implementation of Multiscale Retinex which is as faithful as possible to the one described in the original paper. Overall, this implementation delivers excellent results and confirms the validity of Multiscale Retinex for image color restoration and contrast enhancement. Nevertheless, while the method parameters can be fixed, we show that a crucial choice must be left to the user, depending on the lightning condition of the image: the method must either be applied to each color independently if a color balance is required, or to the luminance only if the goal is to achieve local contrast enhancement. Thus, we propose two slightly different algorithms to deal with both cases.
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Richard Schuster
2013-10-01
Full Text Available Roads are a major cause of habitat fragmentation that can negatively affect many mammal populations. Mitigation measures such as crossing structures are a proposed method to reduce the negative effects of roads on wildlife, but the best methods for determining where such structures should be implemented, and how their effects might differ between species in mammal communities is largely unknown. We investigated the effects of a major highway through south-eastern British Columbia, Canada on several mammal species to determine how the highway may act as a barrier to animal movement, and how species may differ in their crossing-area preferences. We collected track data of eight mammal species across two winters, along both the highway and pre-marked transects, and used a multi-scale modeling approach to determine the scale at which habitat characteristics best predicted preferred crossing sites for each species. We found evidence for a severe barrier effect on all investigated species. Freely-available remotely-sensed habitat landscape data were better than more costly, manually-digitized microhabitat maps in supporting models that identified preferred crossing sites; however, models using both types of data were better yet. Further, in 6 of 8 cases models which incorporated multiple spatial scales were better at predicting preferred crossing sites than models utilizing any single scale. While each species differed in terms of the landscape variables associated with preferred/avoided crossing sites, we used a multi-model inference approach to identify locations along the highway where crossing structures may benefit all of the species considered. By specifically incorporating both highway and off-highway data and predictions we were able to show that landscape context plays an important role for maximizing mitigation measurement efficiency. Our results further highlight the need for mitigation measures along major highways to improve connectivity
ANALYSIS OF MULTISCALE METHODS
Institute of Scientific and Technical Information of China (English)
Wei-nan E; Ping-bing Ming
2004-01-01
The heterogeneous multiscale method gives a general framework for the analysis of multiscale methods. In this paper, we demonstrate this by applying this framework to two canonical problems: The elliptic problem with multiscale coefficients and the quasicontinuum method.
Schaub, Michael T; Yaliraki, Sophia N; Barahona, Mauricio
2011-01-01
Recently, there has been a surge of interest in community detection algorithms for complex networks. The proposed algorithms are based on a variety of heuristics, some with a long history, for the identification of communities or, alternatively, of good graph partitions. In most cases, the algorithms proceed by maximizing a particular objective function, thereby finding the `right' split into communities. Although a thorough comparative analysis of these algorithms is still lacking, there has also been an effort to design random graph models with known community structure against which the performance of different algorithms can be benchmarked. However, such benchmarks normally impose not only a known community structure but also a clique-like random structure for the communities which may differ significantly from those found in real networks. We show here that popular community detection methods are affected by a restricted `field-of-view' limit, an intrinsic upper scale that does not allow them to detect c...
Lee, Steven R.; Berlow, Eric L.; Ostoja, Steven M.; Brooks, Matthew L.; Génin, Alexandre; Matchett, John R.; Hart, Stephen C.
2017-01-01
We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes.
2015-05-01
Fahr . 2009. Pine savanna overstorey influences on ground-cover biodiversity. Applied Vegetation Science 9:37–50. Plue, J., M. Hermy, K. Verheyen, P...perspectives on large-scale patterns in predation, disease , and communities. Michigan State University. Veldman, J.W. 2012. Grasses, trees, and
Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community...
MULTISCALE PHENOMENA IN MATERIALS
Energy Technology Data Exchange (ETDEWEB)
A. BISHOP
2000-09-01
This project developed and supported a technology base in nonequilibrium phenomena underpinning fundamental issues in condensed matter and materials science, and applied this technology to selected problems. In this way the increasingly sophisticated synthesis and characterization available for classes of complex electronic and structural materials provided a testbed for nonlinear science, while nonlinear and nonequilibrium techniques helped advance our understanding of the scientific principles underlying the control of material microstructure, their evolution, fundamental to macroscopic functionalities. The project focused on overlapping areas of emerging thrusts and programs in the Los Alamos materials community for which nonlinear and nonequilibrium approaches will have decisive roles and where productive teamwork among elements of modeling, simulations, synthesis, characterization and applications could be anticipated--particularly multiscale and nonequilibrium phenomena, and complex matter in and between fields of soft, hard and biomimetic materials. Principal topics were: (i) Complex organic and inorganic electronic materials, including hard, soft and biomimetic materials, self-assembly processes and photophysics; (ii) Microstructure and evolution in multiscale and hierarchical materials, including dynamic fracture and friction, dislocation and large-scale deformation, metastability, and inhomogeneity; and (iii) Equilibrium and nonequilibrium phases and phase transformations, emphasizing competing interactions, frustration, landscapes, glassy and stochastic dynamics, and energy focusing.
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C. G. Nolte
2015-05-01
Full Text Available This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ model using Micro-Orifice Uniform Deposit Impactor (MOUDI measurements at 18 sites across North America. Size-resolved measurements of particulate SO42−, NO3−, NH4+, Na+, Cl−, Mg2+, Ca2+ and K+ are compared to CMAQ model output for discrete sampling periods between 2002 and 2005. The observation sites were predominantly in remote areas (e.g. National Parks in the United States and Canada, and measurements were typically made for a period of roughly one month. For SO42− and NH4+, model performance was consistent across the US and Canadian sites, with the model slightly overestimating the peak particle diameter and underestimating the peak particle concentration compared to the observations. Na+ and Mg2+ size distributions were generally well represented at coastal sites, indicating reasonable simulation of emissions from sea spray. CMAQ is able to simulate the displacement of Cl− in aged sea spray aerosol, though the extent of Cl− depletion relative to Na+ is often underpredicted. The model performance for NO3− exhibited much more site-to-site variability than that of SO42− and NH4+, with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and accumulation modes resulted in differences in daily averages of up to 1 μg m−3 (10%, while the difference in seasonal and annual model performance compared to observations from the IMPROVE, CSN and AQS networks was very small. Two updates to the CMAQ aerosol model – changes to the assumed size and mode width of emitted particles and the implementation of gravitational settling – resulted in small improvements in modeled size distributions.
Elleman, Robert A.; Covert, David S.
2009-06-01
In order to test Community Multiscale Air Quality (CMAQ) model performance for ultrafine particle concentrations in the Pacific Northwest, CMAQ v4.4 was modified for ternary NH3-H2SO4-H2O nucleation and for atmospheric processing of ultrafine particles. Sulfuric acid from sulfur dioxide oxidation is iteratively partitioned into gaseous sulfuric acid, newly condensed aerosol sulfate, and aerosol sulfuric acid contained in new 1 nm particles. Freshly nucleated particles are either coagulated to larger particles or grown by sulfuric acid condensation to 10 nm at which point they are included in CMAQ's existing Aitken mode. Multiple nucleation parameterizations were implemented into CMAQ, and one other was investigated in a sensitivity analysis. For a case study in the Pacific Northwest where aerosol number concentration and size distributions were measured, standard binary nucleation in CMAQ produces nearly no particles for this case study. Ternary nucleation can produce millions of 1 nm particles per cm3, but few of these particles survive coagulation loss and grow to 10 nm and into the Aitken mode. There are occasions when the additions to CMAQ increase the number of particles to within an order of magnitude of observations, but it is more common for number concentrations to remain underpredicted by, on average, one order of magnitude. Significant particle nucleation in CMAQ successfully produces a distinct Aitken and accumulation mode and an Aitken mode that is more prominent than the accumulation mode, although errors in the size distribution remain. A more recent ternary nucleation scheme including ammonium bisulfate clusters does not nucleate an appreciable number of particles.
Dong, Xinyi; Fu, Joshua S.; Huang, Kan; Tong, Daniel; Zhuang, Guoshun
2016-07-01
The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust. The default parameterization of initial threshold friction velocity constants are revised to correct the double counting of the impact of soil moisture in CMAQ by the reanalysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is also implemented. The improved dust module in the CMAQ is applied over East Asia for March and April from 2006 to 2010. The model evaluation result shows that the simulation bias of PM10 and aerosol optical depth (AOD) is reduced, respectively, from -55.42 and -31.97 % by the original CMAQ to -16.05 and -22.1 % by the revised CMAQ. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry also results in better agreement with observations for sulfur dioxide (SO2), sulfate (SO42-), nitric acid (HNO3), nitrous oxides (NOx), and nitrate (NO3-). The investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variation of dust. The model evaluation also indicates potential uncertainty within the excessive soil moisture used by meteorological simulation. The mass contribution of fine-mode particles in dust emission may be underestimated by 50 %. The revised CMAQ model provides a useful tool for future studies to investigate the emission, transport, and impact of wind-blown dust over East Asia and elsewhere.
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X. Dong
2015-12-01
Full Text Available The Community Multiscale Air Quality (CMAQ model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. The default parameterization of threshold friction velocity constants in the CMAQ are revised to avoid double counting of the impact of soil moisture based on the re-analysis of field experiment data; source-dependent speciation profiles for dust emission are derived based on local measurements for the Gobi and Taklamakan deserts in East Asia; and dust heterogeneous chemistry is implemented to simulate the reactions involving dust aerosol. The improved dust module in the CMAQ was applied over East Asia for March and April from 2006 to 2010. Evaluation against observations has demonstrated that simulation bias of PM10 and aerosol optical depth (AOD is reduced from −55.42 and −31.97 % in the original CMAQ to −16.05 and −22.1 % in the revised CMAQ, respectively. Comparison with observations at the nearby Gobi stations of Duolun and Yulin indicates that applying a source-dependent profile helps reduce simulation bias for trace metals. Implementing heterogeneous chemistry is also found to result in better agreement with observations for sulfur dioxide (SO2, sulfate (SO42-, nitric acid (HNO3, nitrous oxides (NOx, and nitrate (NO3-. Investigation of a severe dust storm episode from 19 to 21 March 2010 suggests that the revised CMAQ is capable of capturing the spatial distribution and temporal variations of dust aerosols. Model evaluation indicates potential uncertainties within the excessive soil moisture fraction used by meteorological simulation. The mass contribution of fine mode aerosol in dust emission may be underestimated by 50 %. The revised revised CMAQ provides a useful tool for future studies to investigate the emission, transport, and impact of wind
Directory of Open Access Journals (Sweden)
K. Wang
2012-11-01
Full Text Available The US Environmental Protection Agency's (EPA Community Multiscale Air Quality (CMAQ modeling system version 4.7 is further developed to enhance its capability in simulating the photochemical cycles in the presence of dust particles. The new model treatments implemented in CMAQ v4.7 in this work include two online dust emission schemes (i.e., the Zender and Westphal schemes, nine dust-related heterogeneous reactions, an updated aerosol inorganic thermodynamic module ISORROPIA II with an explicit treatment of crustal species, and the interface between ISORROPIA II and the new dust treatments. The resulting improved CMAQ (referred to as CMAQ-Dust, offline-coupled with the Weather Research and Forecast model (WRF, is applied to the April 2001 dust storm episode over the trans-Pacific domain to examine the impact of new model treatments and understand associated uncertainties. WRF/CMAQ-Dust produces reasonable spatial distribution of dust emissions and captures the dust outbreak events, with the total dust emissions of ~111 and 223 Tg when using the Zender scheme with an erodible fraction of 0.5 and 1.0, respectively. The model system can reproduce well observed meteorological and chemical concentrations, with significant improvements for suspended particulate matter (PM, PM with aerodynamic diameter of 10 μm, and aerosol optical depth than the default CMAQ v4.7. The sensitivity studies show that the inclusion of crustal species reduces the concentration of PM with aerodynamic diameter of 2.5 μm (PM_{2.5} over polluted areas. The heterogeneous chemistry occurring on dust particles acts as a sink for some species (e.g., as a lower limit estimate, reducing O_{3} by up to 3.8 ppb (~9% and SO_{2} by up to 0.3 ppb (~27% and as a source for some others (e.g., increasing fine-mode SO_{4}^{2−} by up to 1.1 μg m^{−3} (~12% and PM_{2.5} by up to 1.4 μg m^{−3} (~3% over the domain. The
Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi
2014-03-01
The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0
Directory of Open Access Journals (Sweden)
C. G. Nolte
2015-09-01
Full Text Available This work evaluates particle size–composition distributions simulated by the Community Multiscale Air Quality (CMAQ model using micro-orifice uniform deposit impactor (MOUDI measurements at 18 sites across North America. Size-resolved measurements of particulate SO42−, NO3−, NH4+, Na+, Cl−, Mg2+, Ca2+, and K+ are compared to CMAQ model output for discrete sampling periods between 2002 and 2005. The observation sites were predominantly in remote areas (e.g., National Parks in the USA and Canada, and measurements were typically made for a period of roughly 1 month. For SO42− and NH4+, model performance was consistent across the USA and Canadian sites, with the model slightly overestimating the peak particle diameter and underestimating the peak particle concentration compared to the observations. Na+ and Mg2+ size distributions were generally well represented at coastal sites, indicating reasonable simulation of emissions from sea spray. CMAQ is able to simulate the displacement of Cl− in aged sea spray aerosol, though the extent of Cl− depletion relative to Na+ is often underpredicted. The model performance for NO3− exhibited much more site-to-site variability than that of SO42− and NH4+, with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and accumulation modes resulted in differences in daily averages of up to 1 μg m−3 (10 %, while the difference in seasonal and annual model performance compared to observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE, Chemical Speciation Network (CSN, and Air Quality System (AQS networks was very small. Two updates to the CMAQ aerosol model – changes to the assumed size and mode width of emitted particles and the implementation of gravitational settling
2014-09-30
1 Multiscale Data Assimilation Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering, Center for Ocean Science and Engineering...concerned with next-generation multiscale data assimilation , with a focus on shelfbreak regions, including non-hydrostatic effects. Our long-term...goals are to: - Develop and utilize GMM-DO data assimilation schemes for rigorous multiscale inferences, where observations provide information on
Differential geometry based multiscale models.
Wei, Guo-Wei
2010-08-01
Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are
Multiscale Gentlest Ascent Dynamics
Zhou, Xiang
2016-01-01
The gentlest ascent dynamics (E and Zhou in {\\it Nonlinearity} vol 24, p1831, 2011) locally converges to a nearby saddle point with one dimensional unstable manifold. Here we present a multiscale gentlest ascent dynamics for stochastic slow-fast systems in order to compute saddle point associated with the effective dynamics of the slow variable. Such saddle points, as the candidates of transition states, are important in non-equilibrium transitions for the coarse-grained slow variables; they are also helpful to explore free energy surface. We derive the expressions of the gentlest ascent dynamics for the averaged system, and propose the multiscale numerical methods to efficiently solve the multiscale gentlest ascent dynamics for search of saddle point. The examples of stochastic ordinary and partial differential equations are presented to illustrate the performance of this multiscale gentlest ascent dynamics.
Multiscale Computing with the Multiscale Modeling Library and Runtime Environment
Borgdorff, J.; Mamonski, M.; Bosak, B.; Groen, D.; Ben Belgacem, M.; Kurowski, K.; Hoekstra, A.G.
2013-01-01
We introduce a software tool to simulate multiscale models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We pre
Distributed infrastructure for multiscale computing
Zasada, S.J.; Mamonski, M.; Groen, D.; Borgdorff, J.; Saverchenko, I.; Piontek, T.; Kurowski, K.; Coveney, P.V.; Boukerche, A.; Cahill, V.; El-Saddik, A.; Theodoropoulos, G.; Walshe, R.
2012-01-01
Today scientists and engineers are commonly faced with the challenge of modelling, predicting and controlling multiscale systems which cross scientific disciplines and where several processes acting at different scales coexist and interact. Such multidisciplinary multiscale models, when simulated in
Multiscale Simulations Using Particles
DEFF Research Database (Denmark)
Walther, Jens Honore
We are developing particle methods as a general framework for large scale simulations of discrete and continuous systems in science and engineering. The specific application and research areas include: discrete element simulations of granular flow, smoothed particle hydrodynamics and particle vor...... dynamics. Recent work on the thermophoretic motion of water nanodroplets confined inside carbon nanotubes, and multiscale techniques for polar liquids will be discussed in detail at the symposium....... vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...
Towards distributed multiscale computing for the VPH
Hoekstra, A.G.; Coveney, P.
2010-01-01
Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing o
U.S. Environmental Protection Agency — These data were used to generate the figures included in the following manuscript: Fahey, et al. (2017) "A framework for expanding aqueous chemistry in the Community...
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter
2007-01-01
We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....
Multiscale Simulations Using Particles
DEFF Research Database (Denmark)
Walther, Jens Honore
We are developing particle methods as a general framework for large scale simulations of discrete and continuous systems in science and engineering. The specific application and research areas include: discrete element simulations of granular flow, smoothed particle hydrodynamics and particle...... vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...
Bauman, David; Raspé, Olivier; Meerts, Pierre; Degreef, Jérôme; Ilunga Muledi, Jonathan; Drouet, Thomas
2016-10-01
Ectomycorrhizal fungi (EMF) are highly diversified and dominant in a number of forest ecosystems. Nevertheless, their scales of spatial distribution and the underlying ecological processes remain poorly understood. Although most EMF are considered to be generalists regarding host identity, a preference toward functional strategies of host trees has never been tested. Here, the EMF community was characterised by DNA sequencing in a 10-ha tropical dry season forest-referred to as miombo-an understudied ecosystem from a mycorrhizal perspective. We used 36 soil parameters and 21 host functional traits (FTs) as candidate explanatory variables in spatial constrained ordinations for explaining the EMF community assemblage. Results highlighted that the community variability was explained by host FTs related to the 'leaf economics spectrum' (adjusted R(2) = 11%; SLA, leaf area, foliar Mg content), and by soil parameters (adjusted R(2) = 17%), notably total forms of micronutrients or correlated available elements (Al, N, K, P). Both FTs and soil generated patterns in the community at scales ranging from 75 to 375 m. Our results indicate that soil is more important than previously thought for EMF in miombo woodlands, and show that FTs of host species can be better predictors of symbiont distribution than taxonomical identity.
Multiscale Signal Analysis and Modeling
Zayed, Ahmed
2013-01-01
Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...
Multiscale finite-element method for linear elastic geomechanics
Castelletto, Nicola; Hajibeygi, Hadi; Tchelepi, Hamdi A.
2017-02-01
The demand for accurate and efficient simulation of geomechanical effects is widely increasing in the geoscience community. High resolution characterizations of the mechanical properties of subsurface formations are essential for improving modeling predictions. Such detailed descriptions impose severe computational challenges and motivate the development of multiscale solution strategies. We propose a multiscale solution framework for the geomechanical equilibrium problem of heterogeneous porous media based on the finite-element method. After imposing a coarse-scale grid on the given fine-scale problem, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. These basis functions form the restriction and prolongation operators used to obtain the coarse-scale system for the displacement-vector. Then, a two-stage preconditioner that couples the multiscale system with a smoother is derived for the iterative solution of the fine-scale linear system. Various numerical experiments are presented to demonstrate accuracy and robustness of the method.
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
Myers, James D.; Allison, Thomas C.; Bittner, Sandra J.; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David; Oluwole, Luwi; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry A.; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Al; Windus, Theresa L.; Yang, Christine
2005-10-01
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.
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
Myers, James D.; Allison, Thomas C.; Bittner, Sandra; Didier, Brett T.; Frenklach, Michael; Green, William H.; Ho, Yen-Ling; Hewson, John; Koegler, Wendy S.; Lansing, Carina S.; Leahy, David; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; von Laszewski, Gregor; Montoya, David W.; Pancerella, Carmen M.; Pinzon, Reinhardt; Pitz, William; Rahn, Larry; Ruscic, Branko; Schuchardt, Karen L.; Stephan, Eric G.; Wagner, Albert F.; Windus, Theresa L.; Yang, Christine
2004-03-28
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.
A Collaborative Informatics Infrastructure for Multi-scale Science
Energy Technology Data Exchange (ETDEWEB)
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.
2014-01-01
Procesos ecológicos a múltiples escalas que afectan a las dinámicas de comunidades de plantas en los humedales altoandinos de Bolivia Multi-scale ecological processes driving plant community dynamics in high-elevation peatlands of Bolivia Resumen Algunas especies de plantas, dispuestas en forma de cojines, dominan y determinan el funcionamiento y la resiliencia de los humedales altoandinos (bofedales) frente al cambio climático y al derretimiento de los glaciares. Se tiene la hipótesis de que...
2014-01-01
National audience; Procesos ecológicos a múltiples escalas que afectan a las dinámicas de comunidades de plantas en los humedales altoandinos de Bolivia Multi-scale ecological processes driving plant community dynamics in high-elevation peatlands of Bolivia Resumen Algunas especies de plantas, dispuestas en forma de cojines, dominan y determinan el funcionamiento y la resiliencia de los humedales altoandinos (bofedales) frente al cambio climático y al derretimiento de los glaciares. Se tiene ...
Multiscale Cloud System Modeling
Tao, Wei-Kuo; Moncrieff, Mitchell W.
2009-01-01
The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.
Directory of Open Access Journals (Sweden)
Gabriel Medina
2011-03-01
Full Text Available At their most local, initiatives to reduce emissions from deforestation and degradation (REDD will depend on rural people to manage forest resources. Although the design of frameworks, mechanisms and arrangements, to implement REDD programs have received significant attention, it is not yet clear how REDD+ will function on the ground or how the participation of local populations will be assured. Community forest management (CFM could be an option under REDD+ depending on how it is negotiated, largely because of the expectation that CFM could reduce emissions from deforestation and degradation. Examining institutional factors in the emergence of successful CFM systems and local forest enterprises could provide valuable lessons for REDD planners. We examine cases of CFM development in Mexico, Brazil and Bolivia, to assess the role of multi-scaled governance institutions in their development. Comparing and contrasting advanced CFM systems to regions where it is still emerging, we will show how the establishment of a local organizational base for communal resource management is crucial.
Multiscale modeling of proteins.
Tozzini, Valentina
2010-02-16
The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficiency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was
Directory of Open Access Journals (Sweden)
X. Wang
2010-05-01
Full Text Available In this study, the Community Multiscale Air Quality (CMAQ modeling system is used to simulate the ozone (O_{3} episodes during the Program of Regional Integrated Experiments of Air Quality over the Pearl River Delta, China, in October 2004 (PRIDE-PRD2004. The simulation suggests that O_{3} pollution is a regional phenomenon in the Pearl River Delta (PRD. Elevated O_{3} levels often occurred in the southwestern inland PRD, Pearl River estuary (PRE, and southern coastal areas during the 1-month field campaign. Three evolution patterns of simulated surface O_{3} are summarized based on different near-ground flow conditions. More than 75% of days featured interactions between weak synoptic forcing and local sea-land circulation. Integrated process rate (IPR analysis shows that photochemical production is a dominant contributor to O_{3} enhancement from 09:00 to 15:00 local standard time in the atmospheric boundary layer over most areas with elevated O_{3} occurrence in the mid-afternoon. The simulated ozone production efficiency is 2–8 O_{3} molecules per NO_{x} molecule oxidized in areas with high O_{3} chemical production. Precursors of O_{3} originating from different source regions in the central PRD are mixed during the course of transport to downwind rural areas during nighttime and early morning, where they then contribute to the daytime O_{3} photochemical production. The sea-land circulation plays an important role on the regional O_{3} formation and distribution over PRD. Sensitivity studies suggest that O_{3} formation is volatile-organic-compound-limited in the central inland PRD, PRE, and surrounding coastal areas with less chemical aging (NO_{x}/NO_{y}>0.6, but is NO_{x}-limited in the rural southwestern PRD with aged air (NO_{x}/NO_{y}<0.3.
Multiscale spacetimes from first principles
Calcagni, Gianluca
2016-01-01
We formulate a theorem for the general profile of the Hausdorff and the spectral dimension of multiscale geometries, assuming a smooth and slow change of spacetime dimensionality at large scales. Agreement with various scenarios of quantum gravity is found. In particular, we derive uniquely the multiscale measure with log oscillations of theories of multifractional geometry. Predictivity of this class of models and falsifiability of their abundant phenomenology are thus established.
Sensing and Multiscale Structure
Fletcher, John F A
2012-01-01
We introduce a method of estimating parameters associated with a fractal random scattering medium, which utilizes the multiscale properties of the scattered field. The example of ray-density fluctuations beyond a phase screen with fractal slope is considered. An exact solution to the forward problem, in the case of the Brownian fractal, leads to an expression for the volatility of the slope. This expression is invariant under a change of probability measure, a fact which gives rise to the corresponding result for a (stationary) Ornstein-Uhlenbeck slope. We demonstrate that our analytical results are consistent with numerical simulations. Finally, an application to the determination of sea ice thickness via sonar is discussed.
The Magentospheric Multiscale Constellation
Tooley, C. R.; Black, R. K.; Robertson, B. P.; Stone, J. M.; Pope, S. E.; Davis, G. T.
2015-01-01
The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.
The Magnetospheric Multiscale Constellation
Tooley, C. R.; Black, R. K.; Robertson, B. P.; Stone, J. M.; Pope, S. E.; Davis, G. T.
2016-03-01
The Magnetospheric Multiscale (MMS) mission is the fourth mission of the Solar Terrestrial Probe (STP) program of the National Aeronautics and Space Administration (NASA). The MMS mission was launched on March 12, 2015. The MMS mission consists of four identically instrumented spin-stabilized observatories which are flown in formation to perform the first definitive study of magnetic reconnection in space. The MMS mission was presented with numerous technical challenges, including the simultaneous construction and launch of four identical large spacecraft with 100 instruments total, stringent electromagnetic cleanliness requirements, closed-loop precision maneuvering and pointing of spinning flexible spacecraft, on-board GPS based orbit determination far above the GPS constellation, and a flight dynamics design that enables formation flying with separation distances as small as 10 km. This paper describes the overall mission design and presents an overview of the design, testing, and early on-orbit operation of the spacecraft systems and instrument suite.
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T.A. Buscheck
2001-12-21
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M&O 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports.
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T.A. Buscheck
2001-12-21
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M&O 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports.
A Multiscale Model for Virus Capsid Dynamics
Directory of Open Access Journals (Sweden)
Changjun Chen
2010-01-01
Full Text Available Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.
Multiscale modeling in nanomaterials science
Energy Technology Data Exchange (ETDEWEB)
Karakasidis, T.E. [Department of Civil Engineering, University of Thessaly, Pedion Areos, GR-38834 Volos (Greece)], E-mail: thkarak@uth.gr; Charitidis, C.A. [National Technical University of Athens, School of Chemical Engineering, 9 Heroon, Polytechniou st., Zografos, GR-157 80 Athens (Greece)
2007-09-15
Nanoscience is an area with increasing interest both in the physicochemical phenomena involved and the potential applications such as silicon carbide films, carbon nanotubes, quantum dots, MEMS etc. These materials exhibit very interesting properties (electronic, optical, mechanical) at various length/time scales necessitating better insight. Modern fabrication techniques, such as CVD, also require better understanding in a wide range of length/time scales, in order to achieve better process control. Multiscale modeling is a new, fast developing and challenging scientific field with contributions from many scientific disciplines in an effort to assure materials simulation across length/time scales. In this paper we present a brief review of recent advances in multiscale materials modeling. First, a classification of existing simulation methods based on time and length scales is presented along with basic principles of the multiscale approach. More specifically, we focus on electronic structure calculations, classical atomistic simulation with molecular dynamics or monte carlo methods at the nano/micro scale, Kinetic Monte Carlo for larger system/time scales and finite elements for very large scales. Then, we present the hierarchical and the hybrid strategies of multiscale modeling to couple these methods. Finally, we deal with selected applications concerning thin film CVD deposition and mechanical behavior of carbon nanotubes and we conclude presenting an overview of future trends of multiscale modeling.
The Magnetospheric Multiscale Magnetometers
Russell, C. T.; Anderson, B. J.; Baumjohann, W.; Bromund, K. R.; Dearborn, D.; Fischer, D.; Le, G.; Leinweber, H. K.; Leneman, D.; Magnes, W.; Means, J. D.; Moldwin, M. B.; Nakamura, R.; Pierce, D.; Plaschke, F.; Rowe, K. M.; Slavin, J. A.; Strangeway, R. J.; Torbert, R.; Hagen, C.; Jernej, I.; Valavanoglou, A.; Richter, I.
2016-03-01
The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University's Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored on board so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.
Multiscale coupling:challenges and opportunities
Institute of Scientific and Technical Information of China (English)
HE Guowei; XIA Mengfen; KE Fuju; BAI Yilong
2004-01-01
Multiscale coupling is ubiquitous in nature and attracts broad interests of scientists from mathematicians, physicists, machinists, chemists to biologists. However, much less attention has been paid to its intrinsic implication. In this paper, multiscale coupling is introduced by studying two typical examples in classic mechanics: fluid turbulence and solid failure. The nature of multiscale coupling in the two examples lies in their physical diversities and strong coupling over wide-range scales. The theories of dynamical system and statistical mechanics provide fundamental methods for the multiscale coupling problems. The diverse multiscale couplings call for unified approaches and might expedite new concepts, theories and disciplines.
3D surface reconstruction multi-scale hierarchical approaches
Bellocchio, Francesco; Ferrari, Stefano; Piuri, Vincenzo
2012-01-01
3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. The configuration of the model parameters, the rationale and solutions are described and discussed in detail so the reader has a strong understanding of the methodology. Modeling starts from data captured by 3D digitizers and makes the process even more clear and engaging. Innovative approaches, based on two popular machine learning paradigms, namely Radial Basis Functions and the Support Vector Machines, are also introduced
Reduced basis heterogeneous multiscale methods
Abdulle, Assyr
2015-01-01
Numerical methods for partial differential equations with multiple scales that combine numerical homogenization methods with reduced order modeling techniques are discussed. These numerical methods can be applied to a variety of problems including multiscale nonlinear elliptic and parabolic problems or Stokes flow in heterogenenous media.
Multiscale Image Based Flow Visualization
Telea, Alexandru; Strzodka, Robert
2006-01-01
We present MIBFV, a method to produce real-time, multiscale animations of flow datasets. MIBFV extends the attractive features of the Image-Based Flow Visualization (IBFV) method, i.e. dense flow domain coverage with flow-aligned noise, real-time animation, implementation simplicity, and few (or no)
Multiscale Thermohydrologic Model
Energy Technology Data Exchange (ETDEWEB)
T. Buscheck
2004-10-12
The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers
Multiscale modeling methods in biomechanics.
Bhattacharya, Pinaki; Viceconti, Marco
2017-01-19
More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. For further resources related to this article, please visit the WIREs website.
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T. Buscheck
2005-07-07
The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting
Multiscale Modelling and Inverse Problems
Nolen, J; Stuart, A M
2010-01-01
The need to blend observational data and mathematical models arises in many applications and leads naturally to inverse problems. Parameters appearing in the model, such as constitutive tensors, initial conditions, boundary conditions, and forcing can be estimated on the basis of observed data. The resulting inverse problems are often ill-posed and some form of regularization is required. These notes discuss parameter estimation in situations where the unknown parameters vary across multiple scales. We illustrate the main ideas using a simple model for groundwater flow. We will highlight various approaches to regularization for inverse problems, including Tikhonov and Bayesian methods. We illustrate three ideas that arise when considering inverse problems in the multiscale context. The first idea is that the choice of space or set in which to seek the solution to the inverse problem is intimately related to whether a homogenized or full multiscale solution is required. This is a choice of regularization. The ...
Multiscale expansions in discrete world
Indian Academy of Sciences (India)
Ömer Ünsal; Filiz Taşcan; Mehmet Naci Özer
2014-07-01
In this paper, we show the attainability of KdV equation from some types of nonlinear Schrödinger equation by using multiscale expansions discretely. The power of this manageable method is confirmed by applying it to two selected nonlinear Schrödinger evolution equations. This approach can also be applied to other nonlinear discrete evolution equations. All the computations have been made with Maple computer packet program.
Numerical Analysis of Multiscale Computations
Engquist, Björn; Tsai, Yen-Hsi R
2012-01-01
This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.
Multiscale mechanobiology modeling for surgery assessment
Institute of Scientific and Technical Information of China (English)
M. Garbey; B. L. Bass; S. Berceli
2012-01-01
This paper discusses some of the concept of modeling surgery outcome.It is also an attempt to offer a road map for progress.This paper may serve as a common ground of discussion for both communities i.e surgeons and computational scientist in its broadest sense.Predicting surgery outcome is a very difficult task.All patients are different,and multiple factors such as genetic,or environment conditions plays a role.The difficulty is to construct models that are complex enough to address some of these significant multiscale elements and simple enough to be used in clinical conditions and calibrated on patient data.We will provide a multilevel progressive approach inspired by two applications in surgery that we have been working on.One is about vein graft adaptation after a transplantation,the other is the recovery of cosmesis outcome after a breast lumpectomy.This work,that is still very much in progress,may teach us some lessons.We are convinced that the digital revolution that is transforming the working environment of the surgeon makes closer collaboration between surgeons and computational scientist unavoidable.We believe that "computational surgery" will allow the community to develop predictive model of the surgery outcome and greatprogresses in surgery procedures that goes far beyond the operating room procedural aspect.
Multiscale modeling and synaptic plasticity.
Bhalla, Upinder S
2014-01-01
Synaptic plasticity is a major convergence point for theory and computation, and the process of plasticity engages physiology, cell, and molecular biology. In its many manifestations, plasticity is at the hub of basic neuroscience questions about memory and development, as well as more medically themed questions of neural damage and recovery. As an important cellular locus of memory, synaptic plasticity has received a huge amount of experimental and theoretical attention. If computational models have tended to pick specific aspects of plasticity, such as STDP, and reduce them to an equation, some experimental studies are equally guilty of oversimplification each time they identify a new molecule and declare it to be the last word in plasticity and learning. Multiscale modeling begins with the acknowledgment that synaptic function spans many levels of signaling, and these are so tightly coupled that we risk losing essential features of plasticity if we focus exclusively on any one level. Despite the technical challenges and gaps in data for model specification, an increasing number of multiscale modeling studies have taken on key questions in plasticity. These have provided new insights, but importantly, they have opened new avenues for questioning. This review discusses a wide range of multiscale models in plasticity, including their technical landscape and their implications.
The Adaptive Multi-scale Simulation Infrastructure
Energy Technology Data Exchange (ETDEWEB)
Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)
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.
Statistics of Multiscale Fluctuations in Macromolecular Systems
Yukalov, V I
2012-01-01
An approach is suggested for treating multiscale fluctuations in macromolecular systems. The emphasis is on the statistical properties of such fluctuations. The approach is illustrated by a macromolecular system with mesoscopic fluctuations between the states of atomic orbitals. Strong-orbital and weak-orbital couplings fluctuationally arise, being multiscale in space and time. Statistical properties of the system are obtained by averaging over the multiscale fluctuations. The existence of such multiscale fluctuations causes phase transitions between strong-coupling and weak-coupling states. These transitions are connected with structure and size transformations of macromolecules. An approach for treating density and size multiscale fluctuations by means of classical statistical mechanics is also advanced.
DMS: A Package for Multiscale Molecular Dynamics
Somogyi, Endre; Ortoleva, Peter J
2013-01-01
Advances in multiscale theory and computation provide a novel paradigm for simulating many-classical particle systems. The Deductive Multiscale Simulator (DMS) is a multiscale molecular dynamics (MD) program built on two of these advances, i.e., multiscale Langevin (ML) and multiscale factorization (MF). Both capture the coevolution of the the coarse-grained (CG) state and the microstate. This provides these methods with great efficiency over conventional MD. Neither involve the introduction of phenomenological governing equations for the CG state with attendant uncertainty in both their form of the governing equations and the data needed to calibrate them. The design and implementation of DMS as an open source computational platform is presented here. DMS is written in Python, uses Gromacs to achieve the microphase, and then advances the microstate via a CG-guided evolution. DMS uses MDAnalysis, a Python library for analyzing MD trajectories, to perform computations required to construct CG-related variables...
Many-Task Computing Tools for Multiscale Modeling
Katz, Daniel S.; Ripeanu, Matei; Wilde, Michael
2011-01-01
This paper discusses the use of many-task computing tools for multiscale modeling. It defines multiscale modeling and places different examples of it on a coupling spectrum, discusses the Swift parallel scripting language, describes three multiscale modeling applications that could use Swift, and then talks about how the Swift model is being extended to cover more of the multiscale modeling coupling spectrum.
Multiscale empirical interpolation for solving nonlinear PDEs
Calo, Victor M.
2014-12-01
In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM). To solve nonlinear equations, the GMsFEM is used to represent the solution on a coarse grid with multiscale basis functions computed offline. Computing the GMsFEM solution involves calculating the system residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully-resolved fine scale one. The empirical interpolation method uses basis functions which are built by sampling the nonlinear function we want to approximate a limited number of times. The coefficients needed for this approximation are computed in the offline stage by inverting an inexpensive linear system. The proposed multiscale empirical interpolation techniques: (1) divide computing the nonlinear function into coarse regions; (2) evaluate contributions of nonlinear functions in each coarse region taking advantage of a reduced-order representation of the solution; and (3) introduce multiscale proper-orthogonal-decomposition techniques to find appropriate interpolation vectors. We demonstrate the effectiveness of the proposed methods on several nonlinear multiscale PDEs that are solved with Newton\\'s methods and fully-implicit time marching schemes. Our numerical results show that the proposed methods provide a robust framework for solving nonlinear multiscale PDEs on a coarse grid with bounded error and significant computational cost reduction.
Bhattacharjee, Satyaki; Matouš, Karel
2016-05-01
A new manifold-based reduced order model for nonlinear problems in multiscale modeling of heterogeneous hyperelastic materials is presented. The model relies on a global geometric framework for nonlinear dimensionality reduction (Isomap), and the macroscopic loading parameters are linked to the reduced space using a Neural Network. The proposed model provides both homogenization and localization of the multiscale solution in the context of computational homogenization. To construct the manifold, we perform a number of large three-dimensional simulations of a statistically representative unit cell using a parallel finite strain finite element solver. The manifold-based reduced order model is verified using common principles from the machine-learning community. Both homogenization and localization of the multiscale solution are demonstrated on a large three-dimensional example and the local microscopic fields as well as the homogenized macroscopic potential are obtained with acceptable engineering accuracy.
Peridynamic Multiscale Finite Element Methods
Energy Technology Data Exchange (ETDEWEB)
Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-12-01
The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic and local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the
Multiscale Drivers of Global Environmental Health
Desai, Manish Anil
In this dissertation, I motivate, develop, and demonstrate three such approaches for investigating multiscale drivers of global environmental health: (1) a metric for analyzing contributions and responses to climate change from global to sectoral scales, (2) a framework for unraveling the influence of environmental change on infectious diseases at regional to local scales, and (3) a model for informing the design and evaluation of clean cooking interventions at community to household scales. The full utility of climate debt as an analytical perspective will remain untapped without tools that can be manipulated by a wide range of analysts, including global environmental health researchers. Chapter 2 explains how international natural debt (IND) apportions global radiative forcing from fossil fuel carbon dioxide and methane, the two most significant climate altering pollutants, to individual entities -- primarily countries but also subnational states and economic sectors, with even finer scales possible -- as a function of unique trajectories of historical emissions, taking into account the quite different radiative efficiencies and atmospheric lifetimes of each pollutant. Owing to its straightforward and transparent derivation, IND can readily operationalize climate debt to consider issues of equity and efficiency and drive scenario exercises that explore the response to climate change at multiple scales. Collectively, the analyses presented in this chapter demonstrate how IND can inform a range of key question on climate change mitigation at multiple scales, compelling environmental health towards an appraisal of the causes and not just the consequences of climate change. The environmental change and infectious disease (EnvID) conceptual framework of Chapter 3 builds on a rich history of prior efforts in epidemiologic theory, environmental science, and mathematical modeling by: (1) articulating a flexible and logical system specification; (2) incorporating
Multiscale analysis of neural spike trains.
Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin
2014-01-30
This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code.
Towards a Multiscale Approach to Cybersecurity Modeling
Energy Technology Data Exchange (ETDEWEB)
Hogan, Emilie A.; Hui, Peter SY; Choudhury, Sutanay; Halappanavar, Mahantesh; Oler, Kiri J.; Joslyn, Cliff A.
2013-11-12
We propose a multiscale approach to modeling cyber networks, with the goal of capturing a view of the network and overall situational awareness with respect to a few key properties--- connectivity, distance, and centrality--- for a system under an active attack. We focus on theoretical and algorithmic foundations of multiscale graphs, coming from an algorithmic perspective, with the goal of modeling cyber system defense as a specific use case scenario. We first define a notion of \\emph{multiscale} graphs, in contrast with their well-studied single-scale counterparts. We develop multiscale analogs of paths and distance metrics. As a simple, motivating example of a common metric, we present a multiscale analog of the all-pairs shortest-path problem, along with a multiscale analog of a well-known algorithm which solves it. From a cyber defense perspective, this metric might be used to model the distance from an attacker's position in the network to a sensitive machine. In addition, we investigate probabilistic models of connectivity. These models exploit the hierarchy to quantify the likelihood that sensitive targets might be reachable from compromised nodes. We believe that our novel multiscale approach to modeling cyber-physical systems will advance several aspects of cyber defense, specifically allowing for a more efficient and agile approach to defending these systems.
Metadata in the Collaboratory for Multi-Scale Chemical Science
Energy Technology Data Exchange (ETDEWEB)
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
Collaborating for Multi-Scale Chemical Science
Energy Technology Data Exchange (ETDEWEB)
William H. Green
2006-07-14
Advanced model reduction methods were developed and integrated into the CMCS multiscale chemical science simulation software. The new technologies were used to simulate HCCI engines and burner flames with exceptional fidelity.
Multiscale modelling in immunology: a review.
Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo
2016-05-01
One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases.
Multiscale soil-landscape process modeling
Schoorl, J.M.; Veldkamp, A.
2006-01-01
The general objective of this chapter is to illustrate the role of soils and geomorphological processes in the multiscale soil-lanscape context. Included in this context is the fourth dimension (temporal dimension) and the human role (fifth dimension)
Multiscale Modeling of Hall Thrusters Project
National Aeronautics and Space Administration — New multiscale modeling capability for analyzing advanced Hall thrusters is proposed. This technology offers NASA the ability to reduce development effort of new...
Multiscale Model Approach for Magnetization Dynamics Simulations
De Lucia, Andrea; Tretiakov, Oleg A; Kläui, Mathias
2016-01-01
Simulations of magnetization dynamics in a multiscale environment enable rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with f...
Multiscale modeling of pedestrian dynamics
Cristiani, Emiliano; Tosin, Andrea
2014-01-01
This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.
Multiscale modelling of DNA mechanics
Dršata, Tomáš; Lankaš, Filip
2015-08-01
Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed.
Multiscale dynamics in relaxor ferroelectrics
Energy Technology Data Exchange (ETDEWEB)
Toulouse, J. [Lehigh University, Bethlehem, PA; Cai, L [Lehigh University, Bethlehem, PA; Pattnaik, R. K. [Lehigh University, Bethlehem, PA; Boatner, Lynn A [ORNL
2014-01-01
The multiscale dynamics of complex oxides is illustrated by pairs of mechanical resonances that are excited in the relaxor ferroelectric K1 xLixTaO3 (KLT). These macroscopic resonances are shown to originate in the collective dynamics of piezoelectric polar nanodomains (PND) interacting with the surrounding lattice. Their characteristic Fano lineshapes and rapid evolution with temperature reveal the coherent interplay between the piezoelectric oscillations and orientational relaxations of the PNDs at higher temperature and the contribution of heterophase oscillations near the phase transition. A theoretical model is presented, that describes the evolution of the resonances over the entire temperature range. Similar resonances are observed in other relaxors and must therefore be a common characteristics of these systems.
Multiscale Theory of Dislocation Climb.
Geslin, Pierre-Antoine; Appolaire, Benoît; Finel, Alphonse
2015-12-31
Dislocation climb is a ubiquitous mechanism playing a major role in the plastic deformation of crystals at high temperature. We propose a multiscale approach to model quantitatively this mechanism at mesoscopic length and time scales. First, we analyze climb at a nanoscopic scale and derive an analytical expression of the climb rate of a jogged dislocation. Next, we deduce from this expression the activation energy of the process, bringing valuable insights to experimental studies. Finally, we show how to rigorously upscale the climb rate to a mesoscopic phase-field model of dislocation climb. This upscaling procedure opens the way to large scale simulations where climb processes are quantitatively reproduced even though the mesoscopic length scale of the simulation is orders of magnitude larger than the atomic one.
Wavelets and multiscale signal processing
Cohen, Albert
1995-01-01
Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2014-01-06
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2016-01-06
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Multiscale Modeling of Wear Degradation
Moraes, Alvaro
2015-01-07
Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.
Carbon nanotube integrated multifunctional multiscale composites
Energy Technology Data Exchange (ETDEWEB)
Qiu Jingjing; Zhang, Chuck; Wang, Ben; Liang, Richard [High-Performance Materials Institute, Department of Industrial and Manufacturing Engineering, Florida A and M University-Florida State University College of Engineering, 2525 Pottsdamer Street, Tallahassee, FL 32310-6046 (United States)
2007-07-11
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer composites and enabling functionality, but current manufacturing challenges hinder the realization of their potential. This paper presents a method to fabricate multifunctional multiscale composites through an effective infiltration-based vacuum-assisted resin transfer moulding (VARTM) process. Multi-walled carbon nanotubes (MWNTs) were infused through and between glass-fibre tows along the through-thickness direction. Both pristine and functionalized MWNTs were used in fabricating multiscale glass-fibre-reinforced epoxy composites. It was demonstrated that the mechanical properties of multiscale composites were remarkably enhanced, especially in the functionalized MWNT multiscale composites. With only 1 wt% loading of functionalized MWNTs, tensile strength was increased by 14% and Young's modulus by 20%, in comparison with conventional fibre-reinforced composites. Moreover, the shear strength and short-beam modulus were increased by 5% and 8%, respectively, indicating the improved inter-laminar properties. The strain-stress tests also suggested noticeable enhancement in toughness. Scanning electron microscopy (SEM) characterization confirmed an enhanced interfacial bonding when functionalized MWNTs were integrated into epoxy/glass-fibre composites. The coefficient thermal expansion (CTE) of functionalized nanocomposites indicated a reduction of 25.2% compared with epoxy/glass-fibre composites. The desired improvement of electrical conductivities was also achieved. The multiscale composites indicated a way to leverage the benefits of CNTs and opened up new opportunities for high-performance multifunctional multiscale composites.
Carbon nanotube integrated multifunctional multiscale composites
Qiu, Jingjing; Zhang, Chuck; Wang, Ben; Liang, Richard
2007-07-01
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer composites and enabling functionality, but current manufacturing challenges hinder the realization of their potential. This paper presents a method to fabricate multifunctional multiscale composites through an effective infiltration-based vacuum-assisted resin transfer moulding (VARTM) process. Multi-walled carbon nanotubes (MWNTs) were infused through and between glass-fibre tows along the through-thickness direction. Both pristine and functionalized MWNTs were used in fabricating multiscale glass-fibre-reinforced epoxy composites. It was demonstrated that the mechanical properties of multiscale composites were remarkably enhanced, especially in the functionalized MWNT multiscale composites. With only 1 wt% loading of functionalized MWNTs, tensile strength was increased by 14% and Young's modulus by 20%, in comparison with conventional fibre-reinforced composites. Moreover, the shear strength and short-beam modulus were increased by 5% and 8%, respectively, indicating the improved inter-laminar properties. The strain-stress tests also suggested noticeable enhancement in toughness. Scanning electron microscopy (SEM) characterization confirmed an enhanced interfacial bonding when functionalized MWNTs were integrated into epoxy/glass-fibre composites. The coefficient thermal expansion (CTE) of functionalized nanocomposites indicated a reduction of 25.2% compared with epoxy/glass-fibre composites. The desired improvement of electrical conductivities was also achieved. The multiscale composites indicated a way to leverage the benefits of CNTs and opened up new opportunities for high-performance multifunctional multiscale composites.
Multiscale coupling of molecular dynamics and peridynamics
Tong, Qi; Li, Shaofan
2016-10-01
We propose a multiscale computational model to couple molecular dynamics and peridynamics. The multiscale coupling model is based on a previously developed multiscale micromorphic molecular dynamics (MMMD) theory, which has three dynamics equations at three different scales, namely, microscale, mesoscale, and macroscale. In the proposed multiscale coupling approach, we divide the simulation domain into atomistic region and macroscale region. Molecular dynamics is used to simulate atom motions in atomistic region, and peridynamics is used to simulate macroscale material point motions in macroscale region, and both methods are nonlocal particle methods. A transition zone is introduced as a messenger to pass the information between the two regions or scales. We employ the "supercell" developed in the MMMD theory as the transition element, which is named as the adaptive multiscale element due to its ability of passing information from different scales, because the adaptive multiscale element can realize both top-down and bottom-up communications. We introduce the Cauchy-Born rule based stress evaluation into state-based peridynamics formulation to formulate atomistic-enriched constitutive relations. To mitigate the issue of wave reflection on the interface, a filter is constructed by switching on and off the MMMD dynamic equations at different scales. Benchmark tests of one-dimensional (1-D) and two-dimensional (2-D) wave propagations from atomistic region to macro region are presented. The mechanical wave can transit through the interface smoothly without spurious wave deflections, and the filtering process is proven to be efficient.
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
Efendiev, Yalchin R.
2015-09-02
In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.
A Dimensionality Reduction Framework for Detection of Multiscale Structure in Heterogeneous Networks
Institute of Scientific and Technical Information of China (English)
Hua-Wei Shen; Xue-Qi Cheng; Yuan-Zhuo Wang; Yi-xin Chen
2012-01-01
Graph clustering has been widely applied in exploring regularities emerging in relational data.Recently,the rapid development of network theory correlates graph clustering with the detection of community structure,a common and important topological characteristic of networks.Most existing methods investigate the community structure at a single topological scale.However,as shown by empirical studies,the community structure of real world networks often exhibits multiple topological descriptions,corresponding to the clustering at different resolutions.Furthermore,the detection of multiscale community structure is heavily affected by the heterogeneous distribution of node degree.It is very challenging to detect multiscale community structure in heterogeneous networks.In this paper,we propose a novel,unified framework for detecting community structure from the perspective of dimensionality reduction.Based on the framework,we first prove that the well-known Laplacian matrix for network partition and the widely-used modularity matrix for community detection are two kinds of covariaace matrices used in dimensionality reduction. We then propose a novel method to detect communities at multiple topological scales within our framework.We further show that existing algorithms fail to deal with heterogeneous node degrees.We develop a novel method to handle heterogeneity of networks by introducing a rescaling transformation into the covariance matrices in our framework.Extensive tests on real world and artificial networks demonstrate that the proposed correlation matrices significantly outperform Laplacian and modularity matrices in terms of their ability to identify multiscale community structure in heterogeneous networks.
Energy Technology Data Exchange (ETDEWEB)
Wagner, Gregory John (Sandia National Laboratories, Livermore, CA); Collis, Samuel Scott; Templeton, Jeremy Alan (Sandia National Laboratories, Livermore, CA); Lehoucq, Richard B.; Parks, Michael L.; Jones, Reese E. (Sandia National Laboratories, Livermore, CA); Silling, Stewart Andrew; Scovazzi, Guglielmo; Bochev, Pavel B.
2007-10-01
This report is a collection of documents written as part of the Laboratory Directed Research and Development (LDRD) project A Mathematical Framework for Multiscale Science and Engineering: The Variational Multiscale Method and Interscale Transfer Operators. We present developments in two categories of multiscale mathematics and analysis. The first, continuum-to-continuum (CtC) multiscale, includes problems that allow application of the same continuum model at all scales with the primary barrier to simulation being computing resources. The second, atomistic-to-continuum (AtC) multiscale, represents applications where detailed physics at the atomistic or molecular level must be simulated to resolve the small scales, but the effect on and coupling to the continuum level is frequently unclear.
Foundations of distributed multiscale computing: formalization, specification, and analysis
Borgdorff, J.; Falcone, J.-L.; Lorenz, E.; Bona-Casas, C.; Chopard, B.; Hoekstra, A.G.
2013-01-01
Inherently complex problems from many scientific disciplines require a multiscale modeling approach. Yet its practical contents remain unclear and inconsistent. Moreover, multiscale models can be very computationally expensive, and may have potential to be executed on distributed infrastructure. In
Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation
Energy Technology Data Exchange (ETDEWEB)
Hou, Thomas [California Inst. of Technology (CalTech), Pasadena, CA (United States); Efendiev, Yalchin [Stanford Univ., CA (United States); Tchelepi, Hamdi [Texas A & M Univ., College Station, TX (United States); Durlofsky, Louis [Stanford Univ., CA (United States)
2016-05-24
Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.
Multiscale analysis and computation for flows in heterogeneous media
Energy Technology Data Exchange (ETDEWEB)
Efendiev, Yalchin [Texas A & M Univ., College Station, TX (United States); Hou, T. Y. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Durlofsky, L. J. [Stanford Univ., CA (United States); Tchelepi, H. [Stanford Univ., CA (United States)
2016-08-04
Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.
'Islands' in an island: multiscale effects of forest fragmentation on lowland forest birds in Taiwan
Lin, Fang-yee
2013-01-01
Intensive agricultural developments and increasing human population has caused severe lowland-forest loss and fragmentation in the western coastal plain in Taiwan over the past centuries. The goal of this study is to explore the multiscale impacts of forest fragmentation on species richness and community composition of lowland-forest birds in Taiwan. At a regional scale, Island Biogeography Theory was applied to examine area and isolation effects on species richness of lowland-forest birds us...
Multi-Scale Hierarchical and Topological Design of Structures for Failure Resistance
2013-10-04
Molecular mechanics of mineralized collagen fibrils in bone, Nature Communications, (04 2013): 0. doi: 10.1038/ncomms2720 TOTAL: 14 (b) Papers published in...multiscale modeling and applications of collagen materials – MURI project funded (start date end of 2009), focused on the design of disruptive fibers...and mats of carbon nanotubes – Keynote/plenary speaker at many conferences and workshops, enabled outreach to academic and technical community
Multi-Scale Porous Ultra High Temperature Ceramics
2015-01-08
Final 3. DATES COVERED (From - To) 28-Mar-2013 - 27-Sep-2015 4. TITLE AND SUBTITLE Multi-Scale Porous Ultra High Temperature Ceramics ...report summarizes the main outcomes of research to develop multi-scale porosity Ultra High Temperature Ceramic materials. Processing conditions were...flights. 15. SUBJECT TERMS Ultra High Temperature Ceramics , Colloidal Powder Processing, Multi-scale Porous Materials, Lattice Monte
Efendiev, Yalchin R.
2015-06-05
In this paper, we develop a multiscale finite element method for solving flows in fractured media. Our approach is based on generalized multiscale finite element method (GMsFEM), where we represent the fracture effects on a coarse grid via multiscale basis functions. These multiscale basis functions are constructed in the offline stage via local spectral problems following GMsFEM. To represent the fractures on the fine grid, we consider two approaches (1) discrete fracture model (DFM) (2) embedded fracture model (EFM) and their combination. In DFM, the fractures are resolved via the fine grid, while in EFM the fracture and the fine grid block interaction is represented as a source term. In the proposed multiscale method, additional multiscale basis functions are used to represent the long fractures, while short-size fractures are collectively represented by a single basis functions. The procedure is automatically done via local spectral problems. In this regard, our approach shares common concepts with several approaches proposed in the literature as we discuss. We would like to emphasize that our goal is not to compare DFM with EFM, but rather to develop GMsFEM framework which uses these (DFM or EFM) fine-grid discretization techniques. Numerical results are presented, where we demonstrate how one can adaptively add basis functions in the regions of interest based on error indicators. We also discuss the use of randomized snapshots (Calo et al. Randomized oversampling for generalized multiscale finite element methods, 2014), which reduces the offline computational cost.
Multiscale modelling of saliva secretion.
Sneyd, James; Crampin, Edmund; Yule, David
2014-11-01
We review a multiscale model of saliva secretion, describing in brief how the model is constructed and what we have so far learned from it. The model begins at the level of inositol trisphosphate receptors (IPR), and proceeds through the cellular level (with a model of acinar cell calcium dynamics) to the multicellular level (with a model of the acinus), finally to a model of a saliva production unit that includes an acinus and associated duct. The model at the level of the entire salivary gland is not yet completed. Particular results from the model so far include (i) the importance of modal behaviour of IPR, (ii) the relative unimportance of Ca(2+) oscillation frequency as a controller of saliva secretion, (iii) the need for the periodic Ca(2+) waves to be as fast as possible in order to maximise water transport, (iv) the presence of functional K(+) channels in the apical membrane increases saliva secretion, (v) the relative unimportance of acinar spatial structure for isotonic water transport, (vi) the prediction that duct cells are highly depolarised, (vii) the prediction that the secondary saliva takes at least 1mm (from the acinus) to reach ionic equilibrium. We end with a brief discussion of future directions for the model, both in construction and in the study of scientific questions.
Multiscale modelling of evolving foams
Saye, R. I.; Sethian, J. A.
2016-06-01
We present a set of multi-scale interlinked algorithms to model the dynamics of evolving foams. These algorithms couple the key effects of macroscopic bubble rearrangement, thin film drainage, and membrane rupture. For each of the mechanisms, we construct consistent and accurate algorithms, and couple them together to work across the wide range of space and time scales that occur in foam dynamics. These algorithms include second order finite difference projection methods for computing incompressible fluid flow on the macroscale, second order finite element methods to solve thin film drainage equations in the lamellae and Plateau borders, multiphase Voronoi Implicit Interface Methods to track interconnected membrane boundaries and capture topological changes, and Lagrangian particle methods for conservative liquid redistribution during rearrangement and rupture. We derive a full set of numerical approximations that are coupled via interface jump conditions and flux boundary conditions, and show convergence for the individual mechanisms. We demonstrate our approach by computing a variety of foam dynamics, including coupled evolution of three-dimensional bubble clusters attached to an anchored membrane and collapse of a foam cluster.
Multiscale Bone Remodelling with Spatial P Systems
Cacciagrano, Diletta; Merelli, Emanuela; Tesei, Luca; 10.4204/EPTCS.40.6
2010-01-01
Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integration schemas. Spatial P systems, a variant of P systems in which a more geometric concept of space has been added, have several characteristics in common with Cellular Automata. We propose such a formalism as a basis to rephrase the Complex Automata multiscaling approach and, in this perspective, provide a 2-scale Spatial P system describing bone remodelling. The proposed model not only results to be highly faithful and expressive in a multiscale scenario, but also highlights the need of a deep and formal expressiveness study involving Complex Automata, Spatial P systems and other promising multiscale approaches, such as ...
The Center for Multiscale Plasma Dynamics
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Yannis G
2015-01-20
This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.
Generalized multiscale radial basis function networks.
Billings, Stephen A; Wei, Hua-Liang; Balikhin, Michael A
2007-12-01
A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.
Multiscale modeling in biomechanics and mechanobiology
Hwang, Wonmuk; Kuhl, Ellen
2015-01-01
Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models. Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these...
The center for multiscale plasma dynamics
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Yannis G [Princeton Univ., Princeton, NJ (United States)
2015-01-20
This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.
A multiscale soil loss evaluation index
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Exploring the relationships between land use and soil erosion at different scales is a frontier research field and a hot spot topic in contemporary physical geography. Based on the scale-pattern-process theory in landscape ecology and with consideration of such influential factors as land use, topography, soil and rainfall, this paper applies the scale transition method to establishing a soil loss evaluation index at different scales and puts forward a research path and methodology for multiscale soil loss evaluation indices. The multiscale soil loss evaluation index is applied to the evaluation of relationships between land use and soil erosion and the research of soil erosion evaluation at multiple scales. It provides a new method for optimizing the design of regional land use patterns and integrated multiscale research.
Filtering multiscale dynamical systems in the presence of model error
Harlim, John
2013-01-01
In this review article, we report two important competing data assimilation schemes that were developed in the past 20 years, discuss the current methods that are operationally used in weather forecasting applications, and point out one major challenge in data assimilation community: "utilize these existing schemes in the presence of model error". The aim of this paper is to provide theoretical guidelines to mitigate model error in practical applications of filtering multiscale dynamical systems with reduced models. This is a prototypical situation in many applications due to limited ability to resolve the smaller scale processes as well as the difficulty to model the interaction across scales. We present simple examples to point out the importance of accounting for model error when the separation of scales are not apparent. These examples also elucidate the necessity of treating model error as a stochastic process in a nontrivial fashion for optimal filtering, in the sense that the mean and covariance estima...
Deductive multiscale simulation using order parameters
Energy Technology Data Exchange (ETDEWEB)
Ortoleva, Peter J.
2017-05-16
Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.
Multiscale Modeling of Ceramic Matrix Composites
Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.
2015-01-01
Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.
Multiscale Methods for Nuclear Reactor Analysis
Collins, Benjamin S.
The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly
Discrete Multiscale Analysis: A Biatomic Lattice System
Contra, G A Cassatella; 10.1142/S1402925110000957
2010-01-01
We discuss a discrete approach to the multiscale reductive perturbative method and apply it to a biatomic chain with a nonlinear interaction between the atoms. This system is important to describe the time evolution of localized solitonic excitations. We require that also the reduced equation be discrete. To do so coherently we need to discretize the time variable to be able to get asymptotic discrete waves and carry out a discrete multiscale expansion around them. Our resulting nonlinear equation will be a kind of discrete Nonlinear Schr\\"odinger equation. If we make its continuum limit, we obtain the standard Nonlinear Schr\\"odinger differential equation.
Multiscale phase inversion of seismic marine data
Fu, Lei
2017-08-17
We test the feasibility of applying multiscale phase inversion (MPI) to seismic marine data. To avoid cycle-skipping, the multiscale strategy temporally integrates the traces several times, i.e. high-order integration, to produce low-boost seismograms that are used as input data for the initial iterations of MPI. As the iterations proceed, higher frequencies in the data are boosted by using integrated traces of lower order as the input data. Results with synthetic data and field data from the Gulf of Mexico produce robust and accurate results if the model does not contain strong velocity contrasts such as salt-sediment interfaces.
Multivariate Generalized Multiscale Entropy Analysis
Directory of Open Access Journals (Sweden)
Anne Humeau-Heurtier
2016-11-01
Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.
Zewail, R.; Elsafi, A.; Durdle, N.
2009-02-01
Medical experts often examine hundreds of spine x-rays to determine existence of diseases like osteoarthritis, osteoporoses, and osteophites. Accurate vertebrae segmentation plays a great role in the proper assessment of various vertebral abnormalities. Manual segmentation methods are both time consuming and non-reproducible, hence, developing efficient computer-assisted segmentation methods has been a long standing goal. Over the past decade, segmentation methods that utilize statistical models of shape and appearance have drawn much interest within the medical imaging community. However, despite being a promising approach, they are always faced with a number of challenges such as: poor image quality, and the ability to generalize well to unseen vertebral deformities. This paper presents a novel vertebral segmentation method using Contourlet-based salient point matching and a localized multi-scale shape prior. We employ a multi-scale directional analysis tool, namely contourlets, to build local appearance profiles at salient points of the vertebra's body. The contourlet-based local appearance model is used to detect the vertebral bodies in the test x-ray image. A novel localized multi-scale shape prior is used to drive the segmentation process. Within a best-basis selection framework, the proposed shape prior benefits from the multi-scale nature of wavelet packets, and the capability of ICA to capture hidden independent modes of variations. Experiments were conducted using a set of 100 digital x-ray images of lumbar spines. The contourlet-based appearance profiles and the localized multi-scale shape prior were constructed using a training subset of images, and then matched to unseen images. Promising results were obtained compared to related work in the literature with an average segmentation error of 1.1997 mm.
Directory of Open Access Journals (Sweden)
Stephen Pankavich
2015-02-01
Full Text Available Many mesoscopic N-atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. That is, they simultaneously deform or display collective behaviors, while experiencing atomic scale vibrations and collisions. Due to the large number of atoms involved and the need to simulate over long time periods of biological interest, traditional computational tools, like molecular dynamics, are often infeasible for such systems. Hence, in the current review article, we present and discuss two recent multiscale methods, stemming from the N-atom formulation and an underlying scale separation, that can be used to study such systems in a friction-dominated regime: multiscale perturbation theory and multiscale factorization. These novel analytic foundations provide a self-consistent approach to yield accurate and feasible long-time simulations with atomic detail for a variety of multiscale phenomena, such as viral structural transitions and macromolecular self-assembly. As such, the accuracy and efficiency of the associated algorithms are demonstrated for a few representative biological systems, including satellite tobacco mosaic virus (STMV and lactoferrin.
Foundations for a multiscale collaborative Earth model
Afanasiev, M.
2015-11-11
of the CSEM development, the broad global updates mostly act to remove artefacts from the assembly of the initial CSEM. During the future evolution of the CSEM, the reference data set will be used to account for the influence of small-scale refinements on large-scale global structure. The CSEM as a computational framework is intended to help bridging the gap between local, regional and global tomography, and to contribute to the development of a global multiscale Earth model. While the current construction serves as a first proof of concept, future refinements and additions will require community involvement, which is welcome at this stage already.
Objective multiscale analysis of random heterogeneous materials
Lloberas Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.
2013-01-01
The multiscale framework presented in [1, 2] is assessed in this contribution for a study of random heterogeneous materials. Results are compared to direct numerical simulations (DNS) and the sensitivity to user-defined parameters such as the domain decomposition type and initial coarse scale resolu
Collaboratory for Multiscale Chemical Science (CMCS)
Energy Technology Data Exchange (ETDEWEB)
Allison, Thomas C [NIST
2012-07-03
This document provides details of the contributions made by NIST to the Collaboratory for Multiscale Chemical Science (CMCS) project. In particular, efforts related to the provision of data (and software in support of that data) relevant to the combustion pilot project are described.
Multiscale phenomenology of the cosmic web
Aragón-Calvo, Miguel A.; van de Weygaert, Rien; Jones, Bernard J. T.
2010-01-01
We analyse the structure and connectivity of the distinct morphologies that define the cosmic web. With the help of our multiscale morphology filter (MMF), we dissect the matter distribution of a cosmological Lambda cold dark matter N-body computer simulation into cluster, filaments and walls. The M
Multiscale phenomenology of the cosmic web
Aragón-Calvo, Miguel A.; van de Weygaert, Rien; Jones, Bernard J. T.
2010-01-01
We analyse the structure and connectivity of the distinct morphologies that define the cosmic web. With the help of our multiscale morphology filter (MMF), we dissect the matter distribution of a cosmological Lambda cold dark matter N-body computer simulation into cluster, filaments and walls. The
Multiscale information modelling for heart morphogenesis
Abdulla, T.; Imms, R.; Schleich, J. M.; Summers, R.
2010-07-01
Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.
Multiscale degradations of storage ring FEL optics
Gatto, A; Amra, C; Boccara, C; Couprie, Marie Emmanuelle; De Ninno, G; Feigl, T; Garzella, D; Grewe, M; Kaiser, N; Marsi, M; Paoloni, S; Reita, V; Roger, J P; Torchio, P; Trovò, M; Walker, R; Wille, K
2002-01-01
The advanced understanding of the complete degradation phenomena is crucial in order to develop robust optics for FEL. Under very harsh Synchrotron Radiation conditions, results show that multiscale wavelength damages could be observed, inducing local crystalline structure modifications of the high optical index material with a severe increase of the surface roughness.
Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.
Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang
2017-01-01
Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.
Generalized multiscale finite element methods: Oversampling strategies
Efendiev, Yalchin R.
2014-01-01
In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local
Davit, Yohan
2013-12-01
A wide variety of techniques have been developed to homogenize transport equations in multiscale and multiphase systems. This has yielded a rich and diverse field, but has also resulted in the emergence of isolated scientific communities and disconnected bodies of literature. Here, our goal is to bridge the gap between formal multiscale asymptotics and the volume averaging theory. We illustrate the methodologies via a simple example application describing a parabolic transport problem and, in so doing, compare their respective advantages/disadvantages from a practical point of view. This paper is also intended as a pedagogical guide and may be viewed as a tutorial for graduate students as we provide historical context, detail subtle points with great care, and reference many fundamental works. © 2013 Elsevier Ltd.
Scheibe, Timothy D; Murphy, Ellyn M; Chen, Xingyuan; Rice, Amy K; Carroll, Kenneth C; Palmer, Bruce J; Tartakovsky, Alexandre M; Battiato, Ilenia; Wood, Brian D
2015-01-01
One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve
Nonhydrostatic adaptive mesh dynamics for multiscale climate models (Invited)
Collins, W.; Johansen, H.; McCorquodale, P.; Colella, P.; Ullrich, P. A.
2013-12-01
Many of the atmospheric phenomena with the greatest potential impact in future warmer climates are inherently multiscale. Such meteorological systems include hurricanes and tropical cyclones, atmospheric rivers, and other types of hydrometeorological extremes. These phenomena are challenging to simulate in conventional climate models due to the relatively coarse uniform model resolutions relative to the native nonhydrostatic scales of the phenomonological dynamics. To enable studies of these systems with sufficient local resolution for the multiscale dynamics yet with sufficient speed for climate-change studies, we have adapted existing adaptive mesh dynamics for the DOE-NSF Community Atmosphere Model (CAM). In this talk, we present an adaptive, conservative finite volume approach for moist non-hydrostatic atmospheric dynamics. The approach is based on the compressible Euler equations on 3D thin spherical shells, where the radial direction is treated implicitly (using a fourth-order Runga-Kutta IMEX scheme) to eliminate time step constraints from vertical acoustic waves. Refinement is performed only in the horizontal directions. The spatial discretization is the equiangular cubed-sphere mapping, with a fourth-order accurate discretization to compute flux averages on faces. By using both space-and time-adaptive mesh refinement, the solver allocates computational effort only where greater accuracy is needed. The resulting method is demonstrated to be fourth-order accurate for model problems, and robust at solution discontinuities and stable for large aspect ratios. We present comparisons using a simplified physics package for dycore comparisons of moist physics. Hadley cell lifting an advected tracer into upper atmosphere, with horizontal adaptivity
Multiscale modeling of polymer nanocomposites
Sheidaei, Azadeh
In recent years, polymer nano-composites (PNCs) have increasingly gained more attention due to their improved mechanical, barrier, thermal, optical, electrical and biodegradable properties in comparison with the conventional micro-composites or pristine polymer. With a modest addition of nanoparticles (usually less than 5wt. %), PNCs offer a wide range of improvements in moduli, strength, heat resistance, biodegradability, as well as decrease in gas permeability and flammability. Although PNCs offer enormous opportunities to design novel material systems, development of an effective numerical modeling approach to predict their properties based on their complex multi-phase and multiscale structure is still at an early stage. Developing a computational framework to predict the mechanical properties of PNC is the focus of this dissertation. A computational framework has been developed to predict mechanical properties of polymer nano-composites. In chapter 1, a microstructure inspired material model has been developed based on statistical technique and this technique has been used to reconstruct the microstructure of Halloysite nanotube (HNT) polypropylene composite. This technique also has been used to reconstruct exfoliated Graphene nanoplatelet (xGnP) polymer composite. The model was able to successfully predict the material behavior obtained from experiment. Chapter 2 is the summary of the experimental work to support the numerical work. First, different processing techniques to make the polymer nanocomposites have been reviewed. Among them, melt extrusion followed by injection molding was used to manufacture high density polyethylene (HDPE)---xGnP nanocomposties. Scanning electron microscopy (SEM) also was performed to determine particle size and distribution and to examine fracture surfaces. Particle size was measured from these images and has been used for calculating the probability density function for GNPs in chapter 1. A series of nanoindentation tests have
Directory of Open Access Journals (Sweden)
Eric T. Chung
2015-12-01
Full Text Available In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1 the development of a mass conservative GMsFEM for the coupled flow and transport; (2 the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.
Chung, Eric
2015-12-11
In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.
Energy Technology Data Exchange (ETDEWEB)
Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John
2004-05-01
Existing approaches in multiscale science and engineering have evolved from a range of ideas and solutions that are reflective of their original problem domains. As a result, research in multiscale science has followed widely diverse and disjoint paths, which presents a barrier to cross pollination of ideas and application of methods outside their application domains. The status of the research environment calls for an abstract mathematical framework that can provide a common language to formulate and analyze multiscale problems across a range of scientific and engineering disciplines. In such a framework, critical common issues arising in multiscale problems can be identified, explored and characterized in an abstract setting. This type of overarching approach would allow categorization and clarification of existing models and approximations in a landscape of seemingly disjoint, mutually exclusive and ad hoc methods. More importantly, such an approach can provide context for both the development of new techniques and their critical examination. As with any new mathematical framework, it is necessary to demonstrate its viability on problems of practical importance. At Sandia, lab-centric, prototype application problems in fluid mechanics, reacting flows, magnetohydrodynamics (MHD), shock hydrodynamics and materials science span an important subset of DOE Office of Science applications and form an ideal proving ground for new approaches in multiscale science.
Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites
2016-03-09
AFRL-AFOSR-VA-TR-2016-0154 Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Gregory Odegard MICHIGAN TECHNOLOGICAL UNIVERSITY Final Report...SUBTITLE Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0030 5c. PROGRAM ELEMENT NUMBER...DISTRIBUTION A: Distribution approved for public release. Final Report Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Grant FA9550-13-1-0030 PI
International Conference on Multiscale Methods and Partial Differential Equations.
Energy Technology Data Exchange (ETDEWEB)
Thomas Hou
2006-12-12
The International Conference on Multiscale Methods and Partial Differential Equations (ICMMPDE for short) was held at IPAM, UCLA on August 26-27, 2005. The conference brought together researchers, students and practitioners with interest in the theoretical, computational and practical aspects of multiscale problems and related partial differential equations. The conference provided a forum to exchange and stimulate new ideas from different disciplines, and to formulate new challenging multiscale problems that will have impact in applications.
Multiscale mathematical modeling and simulation of cellular dynamical process.
Nakaoka, Shinji
2014-01-01
Epidermal homeostasis is maintained by dynamic interactions among molecules and cells at different spatiotemporal scales. Mathematical modeling and simulation is expected to provide clear understanding and precise description of multiscaleness in tissue homeostasis under systems perspective. We introduce a stochastic process-based description of multiscale dynamics. Agent-based modeling as a framework of multiscale modeling to achieve consistent integration of definitive subsystems is proposed. A newly developed algorithm that particularly aims to perform stochastic simulations of cellular dynamical process is introduced. Finally we review applications of multiscale modeling and quantitative study to important aspects of epidermal and epithelial homeostasis.
Multiscale Phenomenology of the Cosmic Web
Aragon-Calvo, Miguel A; Jones, Bernard J T
2010-01-01
We analyze the structure and connectivity of the distinct morphologies that define the Cosmic Web. With the help of our Multiscale Morphology Filter (MMF), we dissect the matter distribution of a cosmological $\\Lambda$CDM N-body computer simulation into cluster, filaments and walls. The MMF is ideally suited to adress both the anisotropic morphological character of filaments and sheets, as well as the multiscale nature of the hierarchically evolved cosmic matter distribution. The results of our study may be summarized as follows: i).- While all morphologies occupy a roughly well defined range in density, this alone is not sufficient to differentiate between them given their overlap. Environment defined only in terms of density fails to incorporate the intrinsic dynamics of each morphology. This plays an important role in both linear and non linear interactions between haloes. ii).- Most of the mass in the Universe is concentrated in filaments, narrowly followed by clusters. In terms of volume, clusters only r...
Using Multiscale Product for ECG Characterization
Directory of Open Access Journals (Sweden)
Rym Besrour
2009-01-01
Full Text Available This paper introduces a new method for R wave's locations using the multiscale wavelet analysis, that is based on Mallat's and Hwang's approach for singularity detection via local maxima of the wavelet coefficients signals. Using a first derivative Gaussian function as prototype wavelet, we apply the pointwise product of the wavelet coefficients (PWCs over some successive scales, in order to enhance the peak amplitude of the modulus maxima line and to reduce noise. The R wave corresponds to two modulus maximum lines with opposite signs (min-max of multi-scale product. The proposed algorithm does not include regularity analysis but only amplitude-based criteria. We evaluated the algorithm on two manually annotated databases, such as MIT-BIH Arrhythmia and QT.
Towards multiscale modeling of influenza infection.
Murillo, Lisa N; Murillo, Michael S; Perelson, Alan S
2013-09-07
Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been developed in this emerging field. In addition to discussing modeling approaches, we also survey biological data on influenza infection and transmission that is relevant for constructing influenza infection models. We envision that, in the future, multiscale models that capitalize on technical advances in experimental biology and high performance computing could be used to describe the large spatial scale epidemiology of influenza infection, evolution of the virus, and transmission between hosts more accurately.
MULTI-SCALE GAUSSIAN PROCESSES MODEL
Institute of Scientific and Technical Information of China (English)
Zhou Yatong; Zhang Taiyi; Li Xiaohe
2006-01-01
A novel model named Multi-scale Gaussian Processes (MGP) is proposed. Motivated by the ideas of multi-scale representations in the wavelet theory, in the new model, a Gaussian process is represented at a scale by a linear basis that is composed of a scale function and its different translations. Finally the distribution of the targets of the given samples can be obtained at different scales. Compared with the standard Gaussian Processes (GP) model, the MGP model can control its complexity conveniently just by adjusting the scale parameter. So it can trade-off the generalization ability and the empirical risk rapidly. Experiments verify the feasibility of the MGP model, and exhibit that its performance is superior to the GP model if appropriate scales are chosen.
Tracking magnetogram proper motions by multiscale regularization
Jones, Harrison P.
1995-01-01
Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.
Multiscale Investigation of Chemical Interference in Proteins
Samiotakis, Antonios; Cheung, Margaret S
2010-01-01
We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation...
Multiscale Models of Melting Arctic Sea Ice
2014-09-30
1 Multiscale Models of Melting Arctic Sea Ice Kenneth M. Golden University of Utah, Department of Mathematics phone: (801) 581-6851...feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding the evolution of melt ponds and sea...Models of Melting Arctic Sea Ice 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER
Bayesian learning of sparse multiscale image representations.
Hughes, James Michael; Rockmore, Daniel N; Wang, Yang
2013-12-01
Multiscale representations of images have become a standard tool in image analysis. Such representations offer a number of advantages over fixed-scale methods, including the potential for improved performance in denoising, compression, and the ability to represent distinct but complementary information that exists at various scales. A variety of multiresolution transforms exist, including both orthogonal decompositions such as wavelets as well as nonorthogonal, overcomplete representations. Recently, techniques for finding adaptive, sparse representations have yielded state-of-the-art results when applied to traditional image processing problems. Attempts at developing multiscale versions of these so-called dictionary learning models have yielded modest but encouraging results. However, none of these techniques has sought to combine a rigorous statistical formulation of the multiscale dictionary learning problem and the ability to share atoms across scales. We present a model for multiscale dictionary learning that overcomes some of the drawbacks of previous approaches by first decomposing an input into a pyramid of distinct frequency bands using a recursive filtering scheme, after which we perform dictionary learning and sparse coding on the individual levels of the resulting pyramid. The associated image model allows us to use a single set of adapted dictionary atoms that is shared--and learned--across all scales in the model. The underlying statistical model of our proposed method is fully Bayesian and allows for efficient inference of parameters, including the level of additive noise for denoising applications. We apply the proposed model to several common image processing problems including non-Gaussian and nonstationary denoising of real-world color images.
Multiscale simulation of microbe structure and dynamics.
Joshi, Harshad; Singharoy, Abhishek; Sereda, Yuriy V; Cheluvaraja, Srinath C; Ortoleva, Peter J
2011-10-01
A multiscale mathematical and computational approach is developed that captures the hierarchical organization of a microbe. It is found that a natural perspective for understanding a microbe is in terms of a hierarchy of variables at various levels of resolution. This hierarchy starts with the N -atom description and terminates with order parameters characterizing a whole microbe. This conceptual framework is used to guide the analysis of the Liouville equation for the probability density of the positions and momenta of the N atoms constituting the microbe and its environment. Using multiscale mathematical techniques, we derive equations for the co-evolution of the order parameters and the probability density of the N-atom state. This approach yields a rigorous way to transfer information between variables on different space-time scales. It elucidates the interplay between equilibrium and far-from-equilibrium processes underlying microbial behavior. It also provides framework for using coarse-grained nanocharacterization data to guide microbial simulation. It enables a methodical search for free-energy minimizing structures, many of which are typically supported by the set of macromolecules and membranes constituting a given microbe. This suite of capabilities provides a natural framework for arriving at a fundamental understanding of microbial behavior, the analysis of nanocharacterization data, and the computer-aided design of nanostructures for biotechnical and medical purposes. Selected features of the methodology are demonstrated using our multiscale bionanosystem simulator DeductiveMultiscaleSimulator. Systems used to demonstrate the approach are structural transitions in the cowpea chlorotic mosaic virus, RNA of satellite tobacco mosaic virus, virus-like particles related to human papillomavirus, and iron-binding protein lactoferrin.
Multiscale modeling with smoothed dissipative particle dynamics.
Kulkarni, Pandurang M; Fu, Chia-Chun; Shell, M Scott; Leal, L Gary
2013-06-21
In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow.
Multiscale macromolecular simulation: role of evolving ensembles.
Singharoy, A; Joshi, H; Ortoleva, P J
2012-10-22
Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers.
Engineering Digestion: Multiscale Processes of Food Digestion.
Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim
2016-03-01
Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process. © 2016 Institute of Food Technologists®
Multiscale computation from a chemical engineering perspective
Institute of Scientific and Technical Information of China (English)
Li Jinghai
2014-01-01
This-paper-mainly-discusses-the-multiscale-computation-from-a-chemical-engineering-perspective.-From-the-application-designer’s-perspective,we-propose-a-new-approach-to-investigate-and-develop-both-flexi-ble-and-efficient-computer-architectures.-Based-on-the-requirements-of-applications-within-one-category,we-first-induce-and-extract-some-inherent-computing-patterns-or-core-computing-kernels-from-the-applications.-Some-computing-models-and-innovative-computing-architectures-will-then-be-developed-for-these-patterns-or-kernels,as-well-as-the-software-mapping-techniques.-Finally-those-applications-which-can-share-and-utilize-those-computing-patterns-or-kernels-can-be-executed-very-efficiently-on-those-novel-computing-architectures.-We-think-that-the-proposed-approach-may-not-be-achievable-within-the-existing-technology.-However,we-believe-that-it-will-be-available-in-the-near-future.-Hence,we-will-describe-this-approach-from-the-following-four-as-pects:multiscale-environment-in-the-world,-mesoscale-as-a-key-scale,-energy-minimization-multiscale-(EMMS)paradigm-and-our-perspective.
Multiscale phenomena in the Earth's Magnetosphere
Surjalal Sharma, A.
The multiscale phenomena in the Earth's magnetosphere have been studied using data from ground-based and space-borne measurements. The ground-based observations provide data over decades and are suitable for characterizing the inherent nature of the multiscale behavior and for studying the dynamical and statistical features. On the other hand, the spacecraft data provide in-situ observations of the processes. The multipoint measurements by Cluster have provided a new understanding of the plasma processes at microand meso-scales and the cross-scale coupling among them. The role of cross-scale coupling is evident in phenomena such as bursty bulk flows, flux ropes, and reconnection. The characteristic scales of the processes range from electron skin depth to MHD scales and the modeling of these processes need different physical models, such as kinetic, EMHD, Hall MHD, and MHD. The ground-based data have been used to develop models based on techniques of nonlinear science and yield predictive models which can be used for forecasting. These models characterize the magnetospheric dynaics and yield its global and multiscale aspects. The distribution of scales in the magnetosphere is studied using an extensive database of the solar wind and the magnetosphere. The distributions of the waiting times deviate significantly from a power law as well as stretched exponential distributions, and show a scaling with respect to the mean, indicating a limited role of long-term correlations in the magnetospheric dynamics.
Finite Dimensional Approximations for Continuum Multiscale Problems
Energy Technology Data Exchange (ETDEWEB)
Berlyand, Leonid [Pennsylvania State Univ., University Park, PA (United States)
2017-01-24
The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed research was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.
Multiscale experimental characterization of solar cell defects
Škarvada, Pavel; Škvarenina, Lubomír.; Tománek, Pavel; Sobola, Dinara; Macků, Robert; Brüstlová, Jitka; Grmela, Lubomír.; Smith, Steve
2016-12-01
The search for alternative sources of renewable energy, including novel photovoltaics structures, is one of the principal tasks of 21th century development. In the field of photovoltaics there are three generations of solar cells of different structures going from monocrystalline silicon through thin-films to hybrid and organic cells, moreover using nanostructure details. Due to the diversity of these structures, their complex study requires the multiscale interpretations which common core includes an integrated approach bridging not only the length scales from macroscale to the atomistic, but also multispectral investigation under different working temperatures. The multiscale study is generally applied to theoretical aspects, but is also applied to experimental characterization. We investigate multiscale aspects of electrical, optical and thermal properties of solar cells under illumination and in dark conditions when an external bias is applied. We present the results of a research of the micron and sub-micron defects in a crystalline solar cell structure utilizing scanning probe microscopy and electric noise measurement.
The multiscale importance of road segments in a network disruption scenario: a risk-based approach.
Freiria, Susana; Tavares, Alexandre O; Pedro Julião, Rui
2015-03-01
This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real-world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.
What is a Multiscale Problem in Molecular Dynamics?
Directory of Open Access Journals (Sweden)
Luigi Delle Site
2013-12-01
Full Text Available In this work, we make an attempt to answer the question of what a multiscale problem is in Molecular Dynamics (MD, or, more in general, in Molecular Simulation (MS. By introducing the criterion of separability of scales, we identify three major (reference categories of multiscale problems and discuss their corresponding computational strategies by making explicit examples of applications.
Development of Improved Algorithms and Multiscale Modeling Capability with SUNTANS
2015-09-30
High-resolution simulations using nonhydrostatic models like SUNTANS are crucial for understanding multiscale processes that are unresolved, and...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Development of Improved Algorithms and Multiscale ... Modeling Capability with SUNTANS Oliver B. Fringer 473 Via Ortega, Room 187 Dept. of Civil and Environmental Engineering Stanford University
Transitions of the Multi-Scale Singularity Trees
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven
2005-01-01
Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure o...
Addressing the Multi-scale lapsus of landscape
Schoorl, J.M.
2002-01-01
"Addressing the Multi-scale Lapsus of Landscape" with the sub-title "Multi-scale landscape process modelling to support sustainable land use: A case study for the Lower Guadalhorce valley South Spain" focuses on the role of landscape as the main driving factor behind many geo-environm
Multiscale Analysis of Heterogeneous Media in the Peridynamic Formulation
2009-10-28
Bond Model 41 6.1 Existence and Uniqueness Results . . . . . . . . . . . . . . . . . . . . . . . . 43 6.2 Multiscale Analysis Using the Semigroups ... Semigroup theory provides a strong approximation for capturing the mirco-level fluctuations about the macroscopic displacement field. The multiscale...third model, the Semigroup theory of linear operators [12, 13] is utilized to identify both the macroscopic and microscopic dynamics of the composite
Transitions of the Multi-Scale Singularity Trees
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven
2005-01-01
Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure...
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education
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…
Homogenization-based multi-scale damage theory
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The research of modern mechanics reveals that the damage and failure of structures should be considered on different scales. The present paper is dedicated to establishing the multi-scale damage theory for the nonlinear structural analysis. Starting from the asymptotic expansion based homogenization theory, the multi-scale energy integration is proposed to bridge the gap between the micro and macro scales. By recalling the Helmholtz free energy based damage definition, the damage variable is represented by the multi-scale energy integration. Hence the damage evolution could be numerically simulated on the basis of the unit cell analysis rather than the experimental data identification. Finally the framework of the multi-scale damage theory is established by transforming the multi-scale damage evolution into the conventional continuum damage mechanics. The agree- ment between the simulated results and the benchmark results indicates the validity and effectiveness of the proposed theory.
Multicomponent and multiscale systems theory, methods, and applications in engineering
Geiser, Juergen
2016-01-01
This book examines the latest research results from combined multi-component and multi-scale explorations. It provides theory, considers underlying numerical methods, and presents brilliant computational experimentation. Engineering computations featured in this monograph further offer particular interest to many researchers, engineers, and computational scientists working in frontier modeling and applications of multicomponent and multiscale problems. Professor Geiser gives specific attention to the aspects of decomposing and splitting delicate structures and controlling decomposition and the rationale behind many important applications of multi-component and multi-scale analysis. Multicomponent and Multiscale Systems: Theory, Methods, and Applications in Engineering also considers the question of why iterative methods can be powerful and more appropriate for well-balanced multiscale and multicomponent coupled nonlinear problems. The book is ideal for engineers and scientists working in theoretical and a...
Multiscale flat norm signatures for shapes and images
Energy Technology Data Exchange (ETDEWEB)
Sandine, Gary [Los Alamos National Laboratory; Morgan, Simon P [Los Alamos National Laboratory; Vixie, Kevin R [WASHINGTON STATE UNIV.; Clawson, Keth [WASHINGTON STATE UNIV.; Asaki, Thomas J [WASHINGTON STATE UNIV.; Price, Brandon [WALLA WALLA UNIV.
2009-01-01
In this paper we begin to explore the application of the multiscale flat norm introduced in Morgan and Vixie to shape and image analysis. In particular, we look at the use of the multiscale flat norm signature for the identification of shapes. After briefly reviewing the multiscale flat norm, the L{sup 1}TV functional and the relation between these two, we introduce multiscale signatures that naturally follow from the multiscale flat norm and its components. A numerical method based on the min-cut, max-flow graph-cut is briefly recalled. We suggest using L{sup 2} minimization, rather than the usual Crofton's formula based approximation, for choosing the required weights. The resulting weights have the dual benefits of being analytically computable and of giving more accurate approximations to the anisotropic TV energy. Finally, we demonstrate the usefulness of the signatures on simple shape classification tasks.
Efficient algorithms for multiscale modeling in porous media
Wheeler, Mary F.
2010-09-26
We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.
Multiscale approaches to high efficiency photovoltaics
Directory of Open Access Journals (Sweden)
Connolly James Patrick
2016-01-01
Full Text Available While renewable energies are achieving parity around the globe, efforts to reach higher solar cell efficiencies becomes ever more difficult as they approach the limiting efficiency. The so-called third generation concepts attempt to break this limit through a combination of novel physical processes and new materials and concepts in organic and inorganic systems. Some examples of semi-empirical modelling in the field are reviewed, in particular for multispectral solar cells on silicon (French ANR project MultiSolSi. Their achievements are outlined, and the limits of these approaches shown. This introduces the main topic of this contribution, which is the use of multiscale experimental and theoretical techniques to go beyond the semi-empirical understanding of these systems. This approach has already led to great advances at modelling which have led to modelling software, which is widely known. Yet, a survey of the topic reveals a fragmentation of efforts across disciplines, firstly, such as organic and inorganic fields, but also between the high efficiency concepts such as hot carrier cells and intermediate band concepts. We show how this obstacle to the resolution of practical research obstacles may be lifted by inter-disciplinary cooperation across length scales, and across experimental and theoretical fields, and finally across materials systems. We present a European COST Action “MultiscaleSolar” kicking off in early 2015, which brings together experimental and theoretical partners in order to develop multiscale research in organic and inorganic materials. The goal of this defragmentation and interdisciplinary collaboration is to develop understanding across length scales, which will enable the full potential of third generation concepts to be evaluated in practise, for societal and industrial applications.
Multiscale-multiphysics approaches for engineering applications
Pozzetti, Gabriele; Peters, Bernhard
2017-07-01
Engineering applications often require the study of complex Multiphysics systems. In order to provide solutions for problems of industrial-environmental interest, methods that can capture the influence of all the different scales of composite phenomena must be developed. Due to these necessities multiscale and multiphysics approaches are rapidly becoming a standard in the mathematical-numerical description of engineering systems. The goal of the symposium is to bring together industrial and environmental researcher and practitioners, in order to discuss techniques that aim to solve this kind of heterogeneous problem in an highly efficient way.
Multi-scale Regions from Edge Fragments
DEFF Research Database (Denmark)
Kazmi, Wajahat; Andersen, Hans Jørgen
2014-01-01
In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image...... is inherent in the areas of the triangles and tree depth. We introduce twin leaves as nodes whose sibling share the same characteristics. Triangles corresponding to the twin leaves are filtered out from the binary tree. Graph connectivity is exploited to get clusters of triangles followed by ellipse fitting...
Multiscale statistical analysis of coronal solar activity
Gamborino, Diana; Martinell, Julio J
2016-01-01
Multi-filter images from the solar corona are used to obtain temperature maps which 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 multiscale 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 be extracted from the analysis.
Engineering Digestion: Multiscale Processes of Food Digestion
Bornhorst, GM; Gouseti, O.; Wickham, MSJ; Bakalis, S.
2016-01-01
© 2016 Institute of Food Technologists®. Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digest...
Time-parallel multiscale/multiphysics framework
Energy Technology Data Exchange (ETDEWEB)
Frantziskonis, G. [University of Arizona; Muralidharan, Krishna [University of Arizona; Deymier, Pierre [University of Arizona; Simunovic, Srdjan [ORNL; Nukala, Phani K [ORNL; Pannala, Sreekanth [ORNL
2009-01-01
We introduce the time-parallel compound wavelet matrix method (tpCWM) for modeling the temporal evolution of multiscale and multiphysics systems. The method couples time parallel (TP) and CWM methods operating at different spatial and temporal scales. We demonstrate the efficiency of our approach on two examples: a chemical reaction kinetic system and a non-linear predator prey system. Our results indicate that the tpCWM technique is capable of accelerating time-to-solution by 2 3-orders of magnitude and is amenable to efficient parallel implementation.
Entropic Approach to Multiscale Clustering Analysis
Directory of Open Access Journals (Sweden)
Antonio Insolia
2012-05-01
Full Text Available Recently, a novel method has been introduced to estimate the statistical significance of clustering in the direction distribution of objects. The method involves a multiscale procedure, based on the Kullback–Leibler divergence and the Gumbel statistics of extreme values, providing high discrimination power, even in presence of strong background isotropic contamination. It is shown that the method is: (i semi-analytical, drastically reducing computation time; (ii very sensitive to small, medium and large scale clustering; (iii not biased against the null hypothesis. Applications to the physics of ultra-high energy cosmic rays, as a cosmological probe, are presented and discussed.
Structure and multiscale mechanics of carbon nanomaterials
2016-01-01
This book aims at providing a broad overview on the relationship between structure and mechanical properties of carbon nanomaterials from world-leading scientists in the field. The main aim is to get an in-depth understanding of the broad range of mechanical properties of carbon materials based on their unique nanostructure and on defects of several types and at different length scales. Besides experimental work mainly based on the use of (in-situ) Raman and X-ray scattering and on nanoindentation, the book also covers some aspects of multiscale modeling of the mechanics of carbon nanomaterials.
Magnetospheric Multiscale Instrument Suite Operations and Data System
Baker, D. N.; Riesberg, L.; Pankratz, C. K.; Panneton, R. S.; Giles, B. L.; Wilder, F. D.; Ergun, R. E.
2016-03-01
The four Magnetospheric Multiscale (MMS) spacecraft will collect a combined volume of ˜100 gigabits per day of particle and field data. On average, only 4 gigabits of that volume can be transmitted to the ground. To maximize the scientific value of each transmitted data segment, MMS has developed the Science Operations Center (SOC) to manage science operations, instrument operations, and selection, downlink, distribution, and archiving of MMS science data sets. The SOC is managed by the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado and serves as the primary point of contact for community participation in the mission. MMS instrument teams conduct their operations through the SOC, and utilize the SOC's Science Data Center (SDC) for data management and distribution. The SOC provides a single mission data archive for the housekeeping and science data, calibration data, ephemerides, attitude and other ancillary data needed to support the scientific use and interpretation. All levels of data products will reside at and be publicly disseminated from the SDC. Documentation and metadata describing data products, algorithms, instrument calibrations, validation, and data quality will be provided. Arguably, the most important innovation developed by the SOC is the MMS burst data management and selection system. With nested automation and "Scientist-in-the-Loop" (SITL) processes, these systems are designed to maximize the value of the burst data by prioritizing the data segments selected for transmission to the ground. This paper describes the MMS science operations approach, processes and data systems, including the burst system and the SITL concept.
Magnetospheric Multiscale Instrument Suite Operations and Data System
Baker, D. N.; Riesberg, L.; Pankratz, C. K.; Panneton, R. S.; Giles, B. L.; Wilder, F. D.; Ergun, R. E.
2015-01-01
The four Magnetospheric Multiscale (MMS) spacecraft will collect a combined volume of approximately 100 gigabits per day of particle and field data. On average, only 4 gigabits of that volume can be transmitted to the ground. To maximize the scientific value of each transmitted data segment, MMS has developed the Science Operations Center (SOC) to manage science operations, instrument operations, and selection, downlink, distribution, and archiving of MMS science data sets. The SOC is managed by the Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado and serves as the primary point of contact for community participation in the mission. MMS instrument teams conduct their operations through the SOC, and utilize the SOC's Science Data Center (SOC) for data management and distribution. The SOC provides a single mission data archive for the housekeeping and science data, calibration data, ephemerides, attitude and other ancillary data needed to support the scientific use and interpretation. All levels of data products will reside at and be publicly disseminated from the SDC. Documentation and metadata describing data products, algorithms, instrument calibrations, validation, and data quality will be provided. Arguably, the most important innovation developed by the SOC is the MMS burst data management and selection system. With nested automation and 'Scientist-in-the-Loop' (SITL) processes, these systems are designed to maximize the value of the burst data by prioritizing the data segments selected for transmission to the ground. This paper describes the MMS science operations approach, processes and data systems, including the burst system and the SITL concept.
Multiscale Analysis of Head Impacts in Contact Sports
Guttag, Mark; Sett, Subham; Franck, Jennifer; McNamara, Kyle; Bar-Kochba, Eyal; Crisco, Joseph; Blume, Janet; Franck, Christian
2012-02-01
Traumatic brain injury (TBI) is one of the world's major causes of death and disability. To aid companies in designing safer and improved protective gear and to aid the medical community in producing improved quantitative TBI diagnosis and assessment tools, a multiscale finite element model of the human brain, head and neck is being developed. Recorded impact data from football and hockey helmets instrumented with accelerometers are compared to simulated impact data in the laboratory. Using data from these carefully constructed laboratory experiments, we can quantify impact location, magnitude, and linear and angular accelerations of the head. The resultant forces and accelerations are applied to a fully meshed head-form created from MRI data by Simpleware. With appropriate material properties for each region of the head-form, the Abaqus finite element model can determine the stresses, strains, and deformations in the brain. Simultaneously, an in-vitro cellular TBI criterion is being developed to be incorporated into Abaqus models for the brain. The cell-based injury criterion functions the same way that damage criteria for metals and other materials are used to predict failure in structural materials.
Using CellML with OpenCMISS to simulate multi-scale physiology
Directory of Open Access Journals (Sweden)
David Phillip Nickerson
2015-01-01
Full Text Available 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 visualisation 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 aide 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 customised 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; 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 will also be described, including specific examples exemplifying the extensibility and usability these tools provide the physiological modelling and simulation community. We conclude with some thoughts on future extension of OpenCMISS to make use other community developed information standards, such as FieldML, SED-ML, and BioSignalML. Plans for the integration of accelerator code (GPU and FPGA generated from CellML models is also discussed.
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
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates.
Multiscale Convolutional Neural Networks for Hand Detection
Directory of Open Access Journals (Sweden)
Shiyang Yan
2017-01-01
Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.
PDF-based heterogeneous multiscale filtration model.
Gong, Jian; Rutland, Christopher J
2015-04-21
Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.
Bayesian Integration of multiscale environmental data
Energy Technology Data Exchange (ETDEWEB)
2016-08-22
The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.
Concurrent multiscale modeling of amorphous materials
Tan, Vincent
2013-03-01
An approach to multiscale modeling of amorphous materials is presented whereby atomistic scale domains coexist with continuum-like domains. The atomistic domains faithfully predict severe deformation while the continuum domains allow the computation to scale up the size of the model without incurring excessive computational costs associated with fully atomistic models and without the introduction of spurious forces across the boundary of atomistic and continuum-like domains. The material domain is firstly constructed as a tessellation of Amorphous Cells (AC). For regions of small deformation, the number of degrees of freedom is then reduced by computing the displacements of only the vertices of the ACs instead of the atoms within. This is achieved by determining, a priori, the atomistic displacements within such Pseudo Amorphous Cells associated with orthogonal deformation modes of the cell. Simulations of nanoscale polymer tribology using full molecular mechanics computation and our multiscale approach give almost identical prediction of indentation force and the strain contours of the polymer. We further demonstrate the capability of performing adaptive simulations during which domains that were discretized into cells revert to full atomistic domains when their strain attain a predetermined threshold. The authors would like to acknowledge the financial support given to this study by the Agency of Science, Technology and Research (ASTAR), Singapore (SERC Grant No. 092 137 0013).
Multiscale permutation entropy analysis of electrocardiogram
Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao
2017-04-01
To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.
Multi-scale biomedical systems: measurement challenges
Summers, R.
2016-11-01
Multi-scale biomedical systems are those that represent interactions in materials, sensors, and systems from a holistic perspective. It is possible to view such multi-scale activity using measurement of spatial scale or time scale, though in this paper only the former is considered. The biomedical application paradigm comprises interactions that range from quantum biological phenomena at scales of 10-12 for one individual to epidemiological studies of disease spread in populations that in a pandemic lead to measurement at a scale of 10+7. It is clear that there are measurement challenges at either end of this spatial scale, but those challenges that relate to the use of new technologies that deal with big data and health service delivery at the point of care are also considered. The measurement challenges lead to the use, in many cases, of model-based measurement and the adoption of virtual engineering. It is these measurement challenges that will be uncovered in this paper.
Multiscale structure in eco-evolutionary dynamics
Stacey, Blake C.
In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.
Institute for Multiscale Modeling of Biological Interactions
Energy Technology Data Exchange (ETDEWEB)
Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham
2009-12-26
The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.
Residual-driven online generalized multiscale finite element methods
Chung, Eric T.
2015-09-08
The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.
Multi-scale salient feature extraction on mesh models
Yang, Yongliang
2012-01-01
We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.
Generalization Performance of Regularized Ranking With Multiscale Kernels.
Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin
2016-05-01
The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.
Variational multiscale models for charge transport.
Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin
2012-01-01
This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
Examining Multiscale Movement Coordination in Collaborative Problem Solving
DEFF Research Database (Denmark)
Wiltshire, Travis; Steffensen, Sune Vork
2017-01-01
During collaborative problem solving (CPS), coordination occurs at different spatial and temporal scales. This multiscale coordination should, at least on some scales, play a functional role in facilitating effective collaboration outcomes. To evaluate this, we conducted a study of computer...
Simulation of Multiphysics Multiscale Systems, 6th International Workshop
Krzhizhanovskaya, V.V.
2009-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
A computational library for multiscale modeling of material failure
Talebi, Hossein; Silani, Mohammad; Bordas, Stéphane P. A.; Kerfriden, Pierre; Rabczuk, Timon
2014-05-01
We present an open-source software framework called PERMIX for multiscale modeling and simulation of fracture in solids. The framework is an object oriented open-source effort written primarily in Fortran 2003 standard with Fortran/C++ interfaces to a number of other libraries such as LAMMPS, ABAQUS, LS-DYNA and GMSH. Fracture on the continuum level is modeled by the extended finite element method (XFEM). Using several novel or state of the art methods, the piece software handles semi-concurrent multiscale methods as well as concurrent multiscale methods for fracture, coupling two continuum domains or atomistic domains to continuum domains, respectively. The efficiency of our open-source software is shown through several simulations including a 3D crack modeling in clay nanocomposites, a semi-concurrent FE-FE coupling, a 3D Arlequin multiscale example and an MD-XFEM coupling for dynamic crack propagation.
CPR-based next-generation multiscale simulators
Cusini, M.; Lukyanov, A.; Natvig, J.; Hajibeygi, H.
2014-01-01
Unconventional Reservoir simulations involve several challenges not only arising from geological heterogeneities, but also from strong nonlinear physical coupling terms. All exiting upscaling and multiscale methods rely on a classical sequential formulation to treat the coupling between the
Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.
Biggs, Matthew B; Papin, Jason A
2013-01-01
Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM) and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.
Novel multiscale modeling tool applied to Pseudomonas aeruginosa biofilm formation.
Directory of Open Access Journals (Sweden)
Matthew B Biggs
Full Text Available Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that incorporates both an agent-based model (ABM and constraint-based metabolic modeling. The hybrid model correctly recapitulates oxygen-limited biofilm metabolic activity and predicts increased growth rate via anaerobic respiration with the addition of nitrate to the growth media. In addition, a genome-wide survey of metabolic mutants and biofilm formation exemplifies the powerful analyses that are enabled by this computational modeling tool.
Point evaluation and Hardy space : the multiscale case.
Alpay, Daniel; Dijksma, Aad; Volok, Dan
2005-01-01
We define a point evaluation for transfer operators of multiscale causal dissipative systems. We associate to such a system a de Branges Rovnyak space, which serves as the state space of a coisometric realization.
Simulation of Multiphysics Multiscale Systems, 7th International Workshop
Krzhizhanovskaya, V.
2010-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
Simulation of Multiphysics Multiscale Systems, 5th International Workshop
Krzhizhanovskaya, V.V.; Hoekstra, A.G.
2008-01-01
Modeling and Simulation of Multiphysics Multiscale Systems (SMMS) poses a grand challenge to computational science. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales spanning many orders of magnitude, sophisticated models and advanced comput
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I Y; Vasilyeva, Maria
2015-01-01
In this paper, we develop a multiscale model reduction technique that describes shale gas transport in fractured media. Due to the pore-scale heterogeneities and processes, we use upscaled models to describe the matrix. We follow our previous work \\cite{aes14}, where we derived an upscaled model in the form of generalized nonlinear diffusion model to describe the effects of kerogen. To model the interaction between the matrix and the fractures, we use Generalized Multiscale Finite Element Method. In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. We developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations on a Cartesian fine grid. In this paper, we consider arbitrary fracture orientations and use triangular fine grid and developed GMsFEM for nonlinear flows. Moreover, we develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region ...
Multiscale simulation of molecular processes in cellular environments
Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone
2016-11-01
We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated. This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.
Multiscale simulation of molecular processes in cellular environments.
Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone
2016-11-13
We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.
On multi-scale representations of geographic features
Institute of Scientific and Technical Information of China (English)
WANG Yanhui; LI Xiaojuan; GONG Huili
2006-01-01
This paper contains a review of the development of research on multiple representations compiled from Geographic Information Systems (GIS), including data structure, formalization and storage, and intelligent zoom. A summary is also included of the problems of interconnectivity, consistency maintenance, dynamic query and coexisting updates, as well as a research review of multi-scale databases and related studies. Finally,research directions and foci are proposed for the future design and implementation of multi-scale GIS.
RFP for the Auroral Multiscale Midex (AMM) Mission star tracker
DEFF Research Database (Denmark)
Riis, Troels; Betto, Maurizio; Jørgensen, John Leif;
1999-01-01
This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker.......This document is in response to the John Hopkins University - Applied Physics Laboratory RFP for the Auroral Multiscale Midex Mission star tracker.It describes the functionality, the requirements and the performance of the ASC Star Tracker....
Typograph: Multiscale Spatial Exploration of Text Documents
Energy Technology Data Exchange (ETDEWEB)
Endert, Alexander; Burtner, Edwin R.; Cramer, Nicholas O.; Perko, Ralph J.; Hampton, Shawn D.; Cook, Kristin A.
2013-12-01
Visualizing large document collections using a spatial layout of terms can enable quick overviews of information. However, these metaphors (e.g., word clouds, tag clouds, etc.) often lack interactivity to explore the information and the location and rendering of the terms are often not based on mathematical models that maintain relative distances from other information based on similarity metrics. Further, transitioning between levels of detail (i.e., from terms to full documents) can be challanging. In this paper, we present Typograph, a multi-scale spatial exploration visualization for large document collections. Based on the term-based visualization methods, Typograh enables multipel levels of detail (terms, phrases, snippets, and full documents) within the single spatialization. Further, the information is placed based on their relative similarity to other information to create the “near = similar” geography metaphor. This paper discusses the design principles and functionality of Typograph and presents a use case analyzing Wikipedia to demonstrate usage.
Multi-scale Adaptive Computational Ghost Imaging
Sun, Shuai; Liu, Wei-Tao; Lin, Hui-Zu; Zhang, Er-Feng; Liu, Ji-Ying; Li, Quan; Chen, Ping-Xing
2016-11-01
In some cases of imaging, wide spatial range and high spatial resolution are both required, which requests high performance of detection devices and huge resource consumption for data processing. We propose and demonstrate a multi-scale adaptive imaging method based on the idea of computational ghost imaging, which can obtain a rough outline of the whole scene with a wide range then accordingly find out the interested parts and achieve high-resolution details of those parts, by controlling the field of view and the transverse coherence width of the pseudo-thermal field illuminated on the scene with a spatial light modulator. Compared to typical ghost imaging, the resource consumption can be dramatically reduced using our scheme.
Multiscale systems integration in the eye.
Jacobs, Marc D
2009-01-01
A series of research topics on the eye is reviewed with the aim of illustrating how integrative and systems-biological approaches can be used to understand complex properties and functions of ocular tissues. Emphasis is placed on the diversity of physiological systems represented in the eye, and the variety of approaches required to analyze those systems, both empirically and theoretically. Modeling and empirical studies reviewed focus mainly on problems that the eye presents, in the broad areas of biomechanics and fluid dynamics from the molecular to the whole-organ scale. Attention is given to the relevance of these studies in human disease and the current potential for development of medical therapies based upon a biophysical, integrative modeling approach. The creation of a multiscale hierarchy of numerical models of the eye is proposed as an important and unifying aim of integrative eye research.
Multiscale characterization and analysis of shapes
Prasad, Lakshman; Rao, Ramana
2002-01-01
An adaptive multiscale method approximates shapes with continuous or uniformly and densely sampled contours, with the purpose of sparsely and nonuniformly discretizing the boundaries of shapes at any prescribed resolution, while at the same time retaining the salient shape features at that resolution. In another aspect, a fundamental geometric filtering scheme using the Constrained Delaunay Triangulation (CDT) of polygonized shapes creates an efficient parsing of shapes into components that have semantic significance dependent only on the shapes' structure and not on their representations per se. A shape skeletonization process generalizes to sparsely discretized shapes, with the additional benefit of prunability to filter out irrelevant and morphologically insignificant features. The skeletal representation of characters of varying thickness and the elimination of insignificant and noisy spurs and branches from the skeleton greatly increases the robustness, reliability and recognition rates of character recognition algorithms.
Multi-scale Modelling of Segmentation
DEFF Research Database (Denmark)
Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri
2016-01-01
While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...... of experimental task (i.e., real-time vs. annotated segmentation), nor of musicianship on boundary perception are clear. Our study assesses musicianship effects and differences between segmentation tasks. We conducted a real-time experiment to collect segmentations by musicians and nonmusicians from nine musical...... pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary...
Numerical methods and analysis of multiscale problems
Madureira, Alexandre L
2017-01-01
This book is about numerical modeling of multiscale problems, and introduces several asymptotic analysis and numerical techniques which are necessary for a proper approximation of equations that depend on different physical scales. Aimed at advanced undergraduate and graduate students in mathematics, engineering and physics – or researchers seeking a no-nonsense approach –, it discusses examples in their simplest possible settings, removing mathematical hurdles that might hinder a clear understanding of the methods. The problems considered are given by singular perturbed reaction advection diffusion equations in one and two-dimensional domains, partial differential equations in domains with rough boundaries, and equations with oscillatory coefficients. This work shows how asymptotic analysis can be used to develop and analyze models and numerical methods that are robust and work well for a wide range of parameters.
Multiscale Talbot effects in Fibonacci geometry
Ho, I-Lin
2014-01-01
This article investigates the Talbot effects in Fibonacci geometry by introducing the cut-and-project construction, which allows for capturing the entire infinite Fibonacci structure into a single computational cell. Theoretical and numerical calculations demonstrate the Talbot foci of Fibonacci geometry at distances that are multiples $(\\tau+2)(F_{\\mu}+\\tau F_{\\mu+1} )^{-1}p/(2q)$ or $(\\tau+2)(L_{\\mu}+\\tau L_{\\mu+1} )^{-1}p/(2q)$ of the Talbot distance. Here, ($p$, $q$) are coprime integers, $\\mu$ is an integer, $\\tau$ is the golden mean, and $F_{\\mu}$ and $L_{\\mu}$ are Fibonacci and Lucas numbers, respectively. The image of a single Talbot focus exhibits a multiscale pattern due to the self-similarity of the scaling Fourier spectrum.
Multiscale Autoregressive Identification of Neuroelectrophysiological Systems
Directory of Open Access Journals (Sweden)
Timothy P. Gilmour
2012-01-01
Full Text Available Electrical signals between connected neural nuclei are difficult to model because of the complexity and high number of paths within the brain. Simple parametric models are therefore often used. A multiscale version of the autoregressive with exogenous input (MS-ARX model has recently been developed which allows selection of the optimal amount of filtering and decimation depending on the signal-to-noise ratio and degree of predictability. In this paper, we apply the MS-ARX model to cortical electroencephalograms and subthalamic local field potentials simultaneously recorded from anesthetized rodent brains. We demonstrate that the MS-ARX model produces better predictions than traditional ARX modeling. We also adapt the MS-ARX results to show differences in internuclei predictability between normal rats and rats with 6OHDA-induced parkinsonism, indicating that this method may have broad applicability to other neuroelectrophysiological studies.
On multiscale moving contact line theory.
Li, Shaofan; Fan, Houfu
2015-07-08
In this paper, a multiscale moving contact line (MMCL) theory is presented and employed to simulate liquid droplet spreading and capillary motion. The proposed MMCL theory combines a coarse-grained adhesive contact model with a fluid interface membrane theory, so that it can couple molecular scale adhesive interaction and surface tension with hydrodynamics of microscale flow. By doing so, the intermolecular force, the van der Waals or double layer force, separates and levitates the liquid droplet from the supporting solid substrate, which avoids the shear stress singularity caused by the no-slip condition in conventional hydrodynamics theory of moving contact line. Thus, the MMCL allows the difference of the surface energies and surface stresses to drive droplet spreading naturally. To validate the proposed MMCL theory, we have employed it to simulate droplet spreading over various elastic substrates. The numerical simulation results obtained by using MMCL are in good agreement with the molecular dynamics results reported in the literature.
Discrete multiscale wavelet shrinkage and integrodifferential equations
Didas, S.; Steidl, G.; Weickert, J.
2008-04-01
We investigate the relation between discrete wavelet shrinkage and integrodifferential equations in the context of simplification and denoising of one-dimensional signals. In the continuous setting, strong connections between these two approaches were discovered in 6 (see references). The key observation is that the wavelet transform can be understood as derivative operator after the convolution with a smoothing kernel. In this paper, we extend these ideas to the practically relevant discrete setting with both orthogonal and biorthogonal wavelets. In the discrete case, the behaviour of the smoothing kernels for different scales requires additional investigation. The results of discrete multiscale wavelet shrinkage and related discrete versions of integrodifferential equations are compared with respect to their denoising quality by numerical experiments.
MUSIC: MUlti-Scale Initial Conditions
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.
Nonlinear helicons bearing multi-scale structures
Abdelhamid, Hamdi M.; Yoshida, Zensho
2017-02-01
The helicon waves exhibit varying characters depending on plasma parameters, geometry, and wave numbers. Here, we elucidate an intrinsic multi-scale property embodied by the combination of the dispersive effect and nonlinearity. The extended magnetohydrodynamics model (exMHD) is capable of describing a wide range of parameter space. By using the underlying Hamiltonian structure of exMHD, we construct an exact nonlinear solution, which turns out to be a combination of two distinct modes, the helicon and Trivelpiece-Gould (TG) waves. In the regime of relatively low frequency or high density, however, the combination is made of the TG mode and an ion cyclotron wave (slow wave). The energy partition between these modes is determined by the helicities carried by the wave fields.
Multiscale simulation approach for battery production systems
Schönemann, Malte
2017-01-01
Addressing the challenge of improving battery quality while reducing high costs and environmental impacts of the production, this book presents a multiscale simulation approach for battery production systems along with a software environment and an application procedure. Battery systems are among the most important technologies of the 21st century since they are enablers for the market success of electric vehicles and stationary energy storage solutions. However, the performance of batteries so far has limited possible applications. Addressing this challenge requires an interdisciplinary understanding of dynamic cause-effect relationships between processes, equipment, materials, and environmental conditions. The approach in this book supports the integrated evaluation of improvement measures and is usable for different planning horizons. It is applied to an exemplary battery cell production and module assembly in order to demonstrate the effectiveness and potential benefits of the simulation.
Parallel multiscale simulations of a brain aneurysm.
Grinberg, Leopold; Fedosov, Dmitry A; Karniadakis, George Em
2013-07-01
Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multi-scale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier-Stokes solver εκαr . The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers ( εκαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future
Dynamic Multiscale Averaging (DMA) of Turbulent Flow
Energy Technology Data Exchange (ETDEWEB)
Richard W. Johnson
2012-09-01
A new approach called dynamic multiscale averaging (DMA) for computing the effects of turbulent flow is described. The new method encompasses multiple applications of temporal and spatial averaging, that is, multiscale operations. Initially, a direct numerical simulation (DNS) is performed for a relatively short time; it is envisioned that this short time should be long enough to capture several fluctuating time periods of the smallest scales. The flow field variables are subject to running time averaging during the DNS. After the relatively short time, the time-averaged variables are volume averaged onto a coarser grid. Both time and volume averaging of the describing equations generate correlations in the averaged equations. These correlations are computed from the flow field and added as source terms to the computation on the next coarser mesh. They represent coupling between the two adjacent scales. Since they are computed directly from first principles, there is no modeling involved. However, there is approximation involved in the coupling correlations as the flow field has been computed for only a relatively short time. After the time and spatial averaging operations are applied at a given stage, new computations are performed on the next coarser mesh using a larger time step. The process continues until the coarsest scale needed is reached. New correlations are created for each averaging procedure. The number of averaging operations needed is expected to be problem dependent. The new DMA approach is applied to a relatively low Reynolds number flow in a square duct segment. Time-averaged stream-wise velocity and vorticity contours from the DMA approach appear to be very similar to a full DNS for a similar flow reported in the literature. Expected symmetry for the final results is produced for the DMA method. The results obtained indicate that DMA holds significant potential in being able to accurately compute turbulent flow without modeling for practical
Parallel multiscale simulations of a brain aneurysm
Energy Technology Data Exchange (ETDEWEB)
Grinberg, Leopold [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Fedosov, Dmitry A. [Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich, Jülich 52425 (Germany); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
2013-07-01
Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in
Multiscale Dynamics of Solar Magnetic Structures
Uritsky, Vadim M.; Davila, Joseph M.
2012-01-01
Multiscale topological complexity of the solar magnetic field is among the primary factors controlling energy release in the corona, including associated processes in the photospheric and chromospheric boundaries.We present a new approach for analyzing multiscale behavior of the photospheric magnetic flux underlying these dynamics as depicted by a sequence of high-resolution solar magnetograms. The approach involves two basic processing steps: (1) identification of timing and location of magnetic flux origin and demise events (as defined by DeForest et al.) by tracking spatiotemporal evolution of unipolar and bipolar photospheric regions, and (2) analysis of collective behavior of the detected magnetic events using a generalized version of the Grassberger-Procaccia correlation integral algorithm. The scale-free nature of the developed algorithms makes it possible to characterize the dynamics of the photospheric network across a wide range of distances and relaxation times. Three types of photospheric conditions are considered to test the method: a quiet photosphere, a solar active region (NOAA 10365) in a quiescent non-flaring state, and the same active region during a period of M-class flares. The results obtained show (1) the presence of a topologically complex asymmetrically fragmented magnetic network in the quiet photosphere driven by meso- and supergranulation, (2) the formation of non-potential magnetic structures with complex polarity separation lines inside the active region, and (3) statistical signatures of canceling bipolar magnetic structures coinciding with flaring activity in the active region. Each of these effects can represent an unstable magnetic configuration acting as an energy source for coronal dissipation and heating.
Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.
Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R
2015-01-01
In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.
Multi-scale model analysis and hindcast of the 2013 Colorado Flood
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
生物大分子多尺度理论和计算方法∗%Multiscale theory and computational metho d for biomolecule simulations
Institute of Scientific and Technical Information of China (English)
李文飞; 张建; 王骏; 王炜
2015-01-01
Molecular simulation is one of the most important ways of studying biomolecules. In the last two decades, by com-bining the molecular simulations with experiments, a number of key features of structure and dynamics of biomolecules have been revealed. Traditional molecular simulations often use the all-atom model or some coarse grained models. In practical applications, however, these all-atom models and coarse grained models encounter the bottlenecks in accuracy and eﬃciency, respectively, which hinder their applications to some extent. In recent years, the multiscale models have attracted much attention in the field of biomolecule simulations. In the multiscale model, the atomistic models and coarse grained models are combined together based on the principle of statistical physics, and thus the bottlenecks encountered in the traditional models can be overcome. The currently available multiscale models can be classified into four categories according to the coupling ways between the all-atom model and coarse gained model. They are 1) hybrid resolution multiscale model, 2) parallel coupling multiscale model, 3) one-way coupling multiscale model, and 4) self-learning multiscale model. All these multiscale strategies have achieved great success in certain aspects in the field of biomolecule simulations, including protein folding, aggregation, and functional motions of many kinds of protein machineries. In this review, we briefly introduce the above-mentioned four multiscale strategies, and the examples of their applications. We also discuss the limitations and advantages, as well as the application scopes of these multiscale methods. The directions for future work on improving these multiscale models are also suggested. Finally, a summary and some prospects are presented.%分子模拟是研究生物大分子的重要手段。过去二十年来，人们将分子模拟与实验研究相结合，揭示出生物大分子结构和动力学方面的诸多重要性质。
Directory of Open Access Journals (Sweden)
Jingyi Jiang
2016-03-01
Full Text Available Currently, multiple leaf area index (LAI products retrieved from remote sensing data are widely used in crop growth monitoring, land-surface process simulation and studies of climate change. However, most LAI products are only retrieved from individual satellite observations, which may result in spatial-temporal discontinuities and low accuracy in these products. In this paper, a new method was developed to simultaneously retrieve multiscale LAI data from satellite observations with different spatial resolutions based on an ensemble multiscale filter (EnMsF. The LAI average values corresponding to the date of satellite observations were calculated from the multi-year Moderate Resolution Imaging Spectroradiometer (MODIS LAI product and were used as a priori knowledge for LAI in order to construct an initial ensemble multiscale tree (EnMsT. Satellite observations obtained at different spatial resolutions were then applied to update the LAI values at each node of the EnMsT using a two-sweep filtering procedure. Next, the retrieved LAI values at the finest scale were used as a priori knowledge for LAI for the new round of construction and updating of the EnMsT, until the sum of the difference of LAI values at each node of the EnMsT between two adjacent updates is less than a given threshold. The method was tested using Thematic Mapper (TM or Enhanced Thematic Mapper Plus (ETM+ surface reflectance data and MODIS surface reflectance data from five sites that have different vegetation types. The results demonstrate that the retrieved LAI values for each spatial resolution were in good agreement with the aggregated LAI reference map values for the corresponding spatial resolution. The retrieved LAI values at the coarsest scale provided better accuracy with the aggregated LAI reference map values (root mean square error (RMSE = 0.45 compared with that obtained from the MODIS LAI values (RMSE = 1.30.
Multi-scale theoretical investigation of hydrogen storage in covalent organic frameworks.
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.
Multi-scale Science: Supporting Emerging Practice with Semantically Derived Provenance
Energy Technology Data Exchange (ETDEWEB)
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-scale theoretical investigation of hydrogen storage in covalent organic frameworks
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.
Multiscale Modeling of Mesoscale and Interfacial Phenomena
Petsev, Nikolai Dimitrov
we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.
A principled approach to distributed multiscale computing, from formalization to execution
Borgdorff, J.; Falcone, J.-L.; Lorenz, E.; Chopard, B.; Hoekstra, A.G.
2011-01-01
In several disciplines, a multiscale approach is being used to model complex natural processes yet a principled background to multiscale modeling is not clear. Additionally, some multiscale models requiring distributed resources to be computed in an acceptable timeframe, while no standard framework
The Goddard multi-scale modeling system with unified physics
Directory of Open Access Journals (Sweden)
W.-K. Tao
2009-08-01
Full Text Available 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, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.
This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.
Multiscale Modeling in the Clinic: Drug Design and Development.
Clancy, Colleen E; An, Gary; Cannon, William R; Liu, Yaling; May, Elebeoba E; Ortoleva, Peter; Popel, Aleksander S; Sluka, James P; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M
2016-09-01
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.
Conformal-Based Surface Morphing and Multi-Scale Representation
Directory of Open Access Journals (Sweden)
Ka Chun Lam
2014-05-01
Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.
Multiscale Modeling in the Clinic: Drug Design and Development
Energy Technology Data Exchange (ETDEWEB)
Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.
2016-02-17
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.
MULTISCALE MATHEMATICS FOR BIOMASS CONVERSION TO RENEWABLE HYDROGEN
Energy Technology Data Exchange (ETDEWEB)
Vlachos, Dionisios; Plechac, Petr; Katsoulakis, Markos
2013-09-05
The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomass transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.
Microphysics in Multi-scale Modeling System with Unified Physics
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.
MULTISCALE DIFFERENTIAL METHOD FOR DIGITAL IMAGE SHARPENING
Directory of Open Access Journals (Sweden)
Vitaly V. Bezzubik
2014-11-01
Full Text Available We have proposed and tested a novel method for digital image sharpening. The method is based on multi-scale image analysis, calculation of differential responses of image brightness in different spatial scales, and the subsequent calculation of a restoration function, which sharpens the image by simple subtraction of its brightness values from those of the original image. The method features spatial transposition of the restoration function elements, its normalization, and taking into account the sign of the brightness differential response gradient close to the object edges. The calculation algorithm for the proposed method makes use of integer arithmetic that significantly reduces the computation time. The paper shows that for the images containing small amount of the blur due to the residual aberrations of an imaging system, only the first two scales are needed for the calculation of the restoration function. Similar to the blind deconvolution, the method requires no a priori information about the nature and magnitude of the blur kernel, but it is computationally inexpensive and is much easier in practical implementation. The most promising applications of the method are machine vision and surveillance systems based on real-time intelligent pattern recognition and decision making.
Wide Range Multiscale Entropy Changes through Development
Directory of Open Access Journals (Sweden)
Nicola R. Polizzotto
2015-12-01
Full Text Available How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE, a measure that has been related to signal complexity, to investigate how this variability evolves during development across a broad range of temporal scales. We computed MSE, standard deviation (STD and standard spectral analyses on resting EEG from 188 healthy individuals aged 8–22 years old. We found age-related increases in entropy at lower scales (<~20 ms and decreases in entropy at higher scales (~60–80 ms. Decreases in the overall signal STD were anticorrelated with entropy, especially in the lower scales, where regression analyses showed substantial covariation of observed changes. Our findings document for the first time the scale dependency of developmental changes from childhood to early adulthood, challenging a parsimonious MSE-based account of brain maturation along a unidimensional, complexity measure. At the level of analysis permitted by electroencephalography (EEG, MSE could capture critical spatiotemporal variations in the role of noise in the brain. However, interpretations critically rely on defining how signal STD affects MSE properties.
Typograph: Multiscale Spatial Exploration of Text Documents
Energy Technology Data Exchange (ETDEWEB)
Endert, Alexander; Burtner, Edwin R.; Cramer, Nicholas O.; Perko, Ralph J.; Hampton, Shawn D.; Cook, Kristin A.
2013-10-06
Visualizing large document collections using a spatial layout of terms can enable quick overviews of information. These visual metaphors (e.g., word clouds, tag clouds, etc.) traditionally show a series of terms organized by space-filling algorithms. However, often lacking in these views is the ability to interactively explore the information to gain more detail, and the location and rendering of the terms are often not based on mathematical models that maintain relative distances from other information based on similarity metrics. In this paper, we present Typograph, a multi-scale spatial exploration visualization for large document collections. Based on the term-based visualization methods, Typograh enables multiple levels of detail (terms, phrases, snippets, and full documents) within the single spatialization. Further, the information is placed based on their relative similarity to other information to create the “near = similar” geographic metaphor. This paper discusses the design principles and functionality of Typograph and presents a use case analyzing Wikipedia to demonstrate usage.
Development of multiscale analysis and some applications
Wang, Lipo
2014-11-01
For most complex systems the interaction of different scales is among the most interesting and challenging features. Typically different scale regimes have different physical properties. The commonly used analysis approaches such as structure function and Fourier analysis have their respective limitations, for instance the mixing of large and small scale information, i.e. the so-called infrared and ultraviolet effects. To make improvement in this regard, a new method, segment structure analysis (SSA), has been developed to study the multiscale statistics. Such method can detect the regime scaling based on the conditional extremal points, depicting the geometrical features directly in physical space. From standard test cases (e.g. fractal Brownian motion) to real turbulence data, results show that SSA can appropriately distinguish the different scale effects. A successful application is the scaling of the Lagrangian velocity structure function. This long-time controversial topic has been confirmed using the present method. In principle SSA can generally be applied to various problems.
Multiscale Concrete Modeling of Aging Degradation
Energy Technology Data Exchange (ETDEWEB)
Hammi, Yousseff [Mississippi State Univ., Mississippi State, MS (United States); Gullett, Philipp [Mississippi State Univ., Mississippi State, MS (United States); Horstemeyer, Mark F. [Mississippi State Univ., Mississippi State, MS (United States)
2015-07-31
In this work a numerical finite element framework is implemented to enable the integration of coupled multiscale and multiphysics transport processes. A User Element subroutine (UEL) in Abaqus is used to simultaneously solve stress equilibrium, heat conduction, and multiple diffusion equations for 2D and 3D linear and quadratic elements. Transport processes in concrete structures and their degradation mechanisms are presented along with the discretization of the governing equations. The multiphysics modeling framework is theoretically extended to the linear elastic fracture mechanics (LEFM) by introducing the eXtended Finite Element Method (XFEM) and based on the XFEM user element implementation of Giner et al. [2009]. A damage model that takes into account the damage contribution from the different degradation mechanisms is theoretically developed. The total contribution of damage is forwarded to a Multi-Stage Fatigue (MSF) model to enable the assessment of the fatigue life and the deterioration of reinforced concrete structures in a nuclear power plant. Finally, two examples are presented to illustrate the developed multiphysics user element implementation and the XFEM implementation of Giner et al. [2009].
Multiscale Modeling of UHTC: Thermal Conductivity
Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
Navigation Operations for the Magnetospheric Multiscale Mission
Long, Anne; Farahmand, Mitra; Carpenter, Russell
2015-01-01
The Magnetospheric Multiscale (MMS) mission employs four identical spinning spacecraft flying in highly elliptical Earth orbits. These spacecraft will fly in a series of tetrahedral formations with separations of less than 10 km. MMS navigation operations use onboard navigation to satisfy the mission definitive orbit and time determination requirements and in addition to minimize operations cost and complexity. The onboard navigation subsystem consists of the Navigator GPS receiver with Goddard Enhanced Onboard Navigation System (GEONS) software, and an Ultra-Stable Oscillator. The four MMS spacecraft are operated from a single Mission Operations Center, which includes a Flight Dynamics Operations Area (FDOA) that supports MMS navigation operations, as well as maneuver planning, conjunction assessment and attitude ground operations. The System Manager component of the FDOA automates routine operations processes. The GEONS Ground Support System component of the FDOA provides the tools needed to support MMS navigation operations. This paper provides an overview of the MMS mission and associated navigation requirements and constraints and discusses MMS navigation operations and the associated MMS ground system components built to support navigation-related operations.
Laser Writing of Multiscale Chiral Polymer Metamaterials
Directory of Open Access Journals (Sweden)
E. P. Furlani
2012-01-01
Full Text Available A new approach to metamaterials is presented that involves laser-based patterning of novel chiral polymer media, wherein chirality is realized at two distinct length scales, intrinsically at the molecular level and geometrically at a length scale on the order of the wavelength of the incident field. In this approach, femtosecond-pulsed laser-induced two-photon lithography (TPL is used to pattern a photoresist-chiral polymer mixture into planar chiral shapes. Enhanced bulk chirality can be realized by tuning the wavelength-dependent chiral response at both the molecular and geometric level to ensure an overlap of their respective spectra. The approach is demonstrated via the fabrication of a metamaterial consisting of a two-dimensional array of chiral polymer-based L-structures. The fabrication process is described and modeling is performed to demonstrate the distinction between molecular and planar geometric-based chirality and the effects of the enhanced multiscale chirality on the optical response of such media. This new approach to metamaterials holds promise for the development of tunable, polymer-based optical metamaterials with low loss.
Magnetotellurics as a multiscale geophysical exploration method
Carbonari, Rolando; D'Auria, Luca; Di Maio, Rosa; Petrillo, Zaccaria
2016-04-01
Magnetotellurics (MT) is a geophysical method based on the use of natural electromagnetic signals to define subsurface electrical resistivity structure through electromagnetic induction. MT waves are generated in the Earth's atmosphere and magnetosphere by a range of physical processes, such as magnetic storms, micropulsations, lightning activity. Since the underground MT wave propagation is of diffusive type, the longer is the wavelength (i.e. the lower the wave frequency) the deeper will be the propagation depth. Considering the frequency band commonly used in MT prospecting (10-4 Hz to 104 Hz), the investigation depth ranges from few hundred meters to hundreds of kilometers. This means that magnetotellurics is inherently a multiscale method and, thus, appropriate for applications at different scale ranging from aquifer system characterization to petroleum and geothermal research. In this perspective, the application of the Wavelet transform to the MT data analysis could represent an excellent tool to emphasize characteristics of the MT signal at different scales. In this note, the potentiality of such an approach is studied. In particular, we show that the use of a Discrete Wavelet (DW) decomposition of measured MT time-series data allows to retrieve robust information about the subsoil resistivity over a wide range of spatial (depth) scales, spanning up to 5 orders of magnitude. Furthermore, the application of DWs to MT data analysis has proven to be a flexible tool for advanced data processing (e.g. non-linear filtering, denoising and clustering).
Magnetospheric MultiScale (MMS) System Manager
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.
Multiscale Simulations of Energy Storage in Polymers
Ranjan, V.; van Duin, A.; Buongiorno Nardelli, M.; Bernholc, J.
2012-02-01
Polypropelene is the most used capacitor dielectric for high energy density storage. However, exotic materials such as copolymerized PVDF and, more recently, polythiourea, could potentially lead to an order of magnitude increase in the stored energy density [1,2]. In our previous investigations we demonstrated that PVDF-CTFE possesses non-linear dielectric properties under applied electric field. These are characterized by transitions from non-polar to polar phases that lead enhanced energy density. Recent experiments [3] have also suggested that polythiourea may be another potential system with high energy-density storage and low loss. However, the characteristics of this emerging material are not yet understood and even its preferred crystalline phases are not known. We have developed a multiscale approach to predicting polymer self-organization using the REAX force field and molecular dynamics simulations. We find that polythiourea chains tend to coalesce in nanoribbon-type structures and prefer an anti-polar interchain ordering similar to PVDF. These results suggest a possible role of topological phase transitions in shaping energy storage in this system.[4pt] [1] B. Chu et al, Science 313, 334 (2006).[0pt] [2] V. Ranjan et al., PRL 99, 047801 (2007).[0pt] [3] Q. Zhang, private communication
Multiscale methods for computational RNA enzymology
Panteva, Maria T.; Dissanayake, Thakshila; Chen, Haoyuan; Radak, Brian K.; Kuechler, Erich R.; Giambaşu, George M.; Lee, Tai-Sung; York, Darrin M.
2016-01-01
RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multi-dimensional “problem space” of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues and bond breaking/forming in the chemical steps of the reaction. The goal of this article is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics (MD) simulations, reference interaction site model (RISM) calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics (HREMD) and quantum mechanical/molecular mechanical (QM/MM) simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme (HDVr) and RNase A. PMID:25726472
Holographic Dynamics from Multiscale Entanglement Renormalization Ansatz
Chua, Victor; Tiwari, Apoorv; Ryu, Shinsei
2016-01-01
The Multiscale Entanglement Renormalization Ansatz (MERA) is a tensor network based variational ansatz that is capable of capturing many of the key physical properties of strongly correlated ground states such as criticality and topological order. MERA also shares many deep relationships with the AdS/CFT (gauge-gravity) correspondence by realizing a UV complete holographic duality within the tensor networks framework. Motivated by this, we have re-purposed the MERA tensor network as an analysis tool to study the real-time evolution of the 1D transverse Ising model in its low energy excited state sector. We performed this analysis by allowing the ancilla qubits of the MERA tensor network to acquire quantum fluctuations, which yields a unitary transform between the physical (boundary) and ancilla qubit (bulk) Hilbert spaces. This then defines a reversible quantum circuit which is used as a `holographic transform' to study excited states and their real-time dynamics from the point of the bulk ancillae. In the ga...
Energy Technology Data Exchange (ETDEWEB)
David A. Randall; Marat Khairoutdinov
2007-12-14
The Colorado State University (CSU) Multi-scale Modeling Framework (MMF) is a new type of general circulation model (GCM) that replaces the conventional parameterizations of convection, clouds and boundary layer with a cloud-resolving model (CRM) embedded into each grid column. The MMF that we have been working with is a “super-parameterized” version of the Community Atmosphere Model (CAM). As reported in the publications listed below, we have done extensive work with the model. We have explored the MMF’s performance in several studies, including an AMIP run and a CAPT test, and we have applied the MMF to an analysis of climate sensitivity.
Generalized multiscale finite element method. Symmetric interior penalty coupling
Efendiev, Yalchin R.
2013-12-01
Motivated by applications to numerical simulations of flows in highly heterogeneous porous media, we develop multiscale finite element methods for second order elliptic equations. We discuss a multiscale model reduction technique in the framework of the discontinuous Galerkin finite element method. We propose two different finite element spaces on the coarse mesh. The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix. The second choice is based on generation of a snapshot space and subsequent selection of a subspace of a reduced dimension. The approximation with these multiscale spaces is based on the discontinuous Galerkin finite element method framework. We investigate the stability and derive error estimates for the methods and further experimentally study their performance on a representative number of numerical examples. © 2013 Elsevier Inc.
Multi-scale modelling and simulation in systems biology.
Dada, Joseph O; Mendes, Pedro
2011-02-01
The aim of systems biology is to describe and understand biology at a global scale where biological functions are recognised as a result of complex mechanisms that happen at several scales, from the molecular to the ecosystem. Modelling and simulation are computational tools that are invaluable for description, prediction and understanding these mechanisms in a quantitative and integrative way. Therefore the study of biological functions is greatly aided by multi-scale methods that enable the coupling and simulation of models spanning several spatial and temporal scales. Various methods have been developed for solving multi-scale problems in many scientific disciplines, and are applicable to continuum based modelling techniques, in which the relationship between system properties is expressed with continuous mathematical equations or discrete modelling techniques that are based on individual units to model the heterogeneous microscopic elements such as individuals or cells. In this review, we survey these multi-scale methods and explore their application in systems biology.
Multiscale Universal Interface: A Concurrent Framework for Coupling Heterogeneous Solvers
Tang, Yu-Hang; Bian, Xin; Li, Zhen; Karniadakis, George E
2014-01-01
Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and c...
Multiscale multifractal time irreversibility analysis of stock markets
Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin
2016-11-01
Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.
Multiscale Analysis of Information Dynamics for Linear Multivariate Processes
Faes, Luca; Stramaglia, Sebastiano; Nollo, Giandomenico; Stramaglia, Sebastiano
2016-01-01
In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using state-space (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale infor...
Algorithmic foundation of multi-scale spatial representation
Li, Zhilin
2006-01-01
With the widespread use of GIS, multi-scale representation has become an important issue in the realm of spatial data handling. However, no book to date has systematically tackled the different aspects of this discipline. Emphasizing map generalization, Algorithmic Foundation of Multi-Scale Spatial Representation addresses the mathematical basis of multi-scale representation, specifically, the algorithmic foundation.Using easy-to-understand language, the author focuses on geometric transformations, with each chapter surveying a particular spatial feature. After an introduction to the essential operations required for geometric transformations as well as some mathematical and theoretical background, the book describes algorithms for a class of point features/clusters. It then examines algorithms for individual line features, such as the reduction of data points, smoothing (filtering), and scale-driven generalization, followed by a discussion of algorithms for a class of line features including contours, hydrog...
Multiscale Stategies in Automatic Image-Domain Waveform Tomography
Institute of Scientific and Technical Information of China (English)
Yujin Liu; Zhenchun Li
2015-01-01
Multiscale strategies are very important in the successful application of waveform-based velocity inversion. The strategy that sequentially preceeds from long to short scale of velocity model, has been well developed in full waveform inversion (FWI) to solve the local mininum problem. In contrast, it’s not well understood in the image-domain waveform tomography (IWT), which back-projects incoherent waveform components of the common image gather into velocity updates. IWT is less prone to local minimum problem but tends to build long-scale model with low resolution. In order to build both long- and short-scale model by IWT, we discuss several multiscale strategies restricted in the image domain. The strategies include model reparameterization, objective function switching and gradient rescaling. Numerical tests on Marmsousi model and real data demonstrate that our proposed multiscale IWT is effective in buidling velocity model with wide wavenumber spectrum.
Multiscale modeling of thermal conductivity of polycrystalline graphene sheets.
Mortazavi, Bohayra; Pötschke, Markus; Cuniberti, Gianaurelio
2014-03-21
We developed a multiscale approach to explore the effective thermal conductivity of polycrystalline graphene sheets. By performing equilibrium molecular dynamics (EMD) simulations, the grain size effect on the thermal conductivity of ultra-fine grained polycrystalline graphene sheets is investigated. Our results reveal that the ultra-fine grained graphene structures have thermal conductivity one order of magnitude smaller than that of pristine graphene. Based on the information provided by the EMD simulations, we constructed finite element models of polycrystalline graphene sheets to probe the thermal conductivity of samples with larger grain sizes. Using the developed multiscale approach, we also investigated the effects of grain size distribution and thermal conductivity of grains on the effective thermal conductivity of polycrystalline graphene. The proposed multiscale approach on the basis of molecular dynamics and finite element methods could be used to evaluate the effective thermal conductivity of polycrystalline graphene and other 2D structures.
Coherent multiscale image processing using dual-tree quaternion wavelets.
Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G
2008-07-01
The dual-tree quaternion wavelet transform (QWT) is a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant tight frame representation whose coefficients sport a magnitude and three phases: two phases encode local image shifts while the third contains image texture information. The QWT is based on an alternative theory for the 2-D Hilbert transform and can be computed using a dual-tree filter bank with linear computational complexity. To demonstrate the properties of the QWT's coherent magnitude/phase representation, we develop an efficient and accurate procedure for estimating the local geometrical structure of an image. We also develop a new multiscale algorithm for estimating the disparity between a pair of images that is promising for image registration and flow estimation applications. The algorithm features multiscale phase unwrapping, linear complexity, and sub-pixel estimation accuracy.
Standard Model in multi-scale theories and observational constraints
Calcagni, Gianluca; Rodríguez-Fernández, David
2015-01-01
We construct and analyze the Standard Model of electroweak and strong interactions in multi-scale spacetimes with (i) weighted derivatives and (ii) $q$-derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multi-scale measures with only one characteristic time, length and energy scale $t_*$, $\\ell_*$ and $E_*$, we compute the Lamb shift in the hydrogen atom and constrain the multi-scale correction to the ordi...
Waveform relaxation for the computational homogenization of multiscale magnetoquasistatic problems
Niyonzima, I.; Geuzaine, C.; Schöps, S.
2016-12-01
This paper proposes the application of the waveform relaxation method to the homogenization of multiscale magnetoquasistatic problems. In the monolithic heterogeneous multiscale method, the nonlinear macroscale problem is solved using the Newton-Raphson scheme. The resolution of many mesoscale problems per Gauß point allows to compute the homogenized constitutive law and its derivative by finite differences. In the proposed approach, the macroscale problem and the mesoscale problems are weakly coupled and solved separately using the finite element method on time intervals for several waveform relaxation iterations. The exchange of information between both problems is still carried out using the heterogeneous multiscale method. However, the partial derivatives can now be evaluated exactly by solving only one mesoscale problem per Gauß point.
Multi-Scale Salient Features for Analyzing 3D Shapes
Institute of Scientific and Technical Information of China (English)
Yong-Liang Yang; Chao-Hui Shen
2012-01-01
Extracting feature regions on mesh models is crucial for shape analysis and understanding.It can be widely used for various 3D content-based applications in graphics and geometry field.In this paper,we present a new algorithm of extracting multi-scale salient features on meshes.This is based on robust estimation of curvature on multiple scales.The coincidence between salient feature and the scale of interest can be established straightforwardly,where detailed feature appears on small scale and feature with more global shape information shows up on large scale.We demonstrate this kind of multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection.Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes.
Complexity multiscale asynchrony measure and behavior for interacting financial dynamics
Yang, Ge; Wang, Jun; Niu, Hongli
2016-08-01
A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.
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
Generalized multiscale finite element methods (GMsFEM)
Efendiev, Yalchin R.
2013-10-01
In this paper, we propose a general approach called Generalized Multiscale Finite Element Method (GMsFEM) for performing multiscale simulations for problems without scale separation over a complex input space. As in multiscale finite element methods (MsFEMs), the main idea of the proposed approach is to construct a small dimensional local solution space that can be used to generate an efficient and accurate approximation to the multiscale solution with a potentially high dimensional input parameter space. In the proposed approach, we present a general procedure to construct the offline space that is used for a systematic enrichment of the coarse solution space in the online stage. The enrichment in the online stage is performed based on a spectral decomposition of the offline space. In the online stage, for any input parameter, a multiscale space is constructed to solve the global problem on a coarse grid. The online space is constructed via a spectral decomposition of the offline space and by choosing the eigenvectors corresponding to the largest eigenvalues. The computational saving is due to the fact that the construction of the online multiscale space for any input parameter is fast and this space can be re-used for solving the forward problem with any forcing and boundary condition. Compared with the other approaches where global snapshots are used, the local approach that we present in this paper allows us to eliminate unnecessary degrees of freedom on a coarse-grid level. We present various examples in the paper and some numerical results to demonstrate the effectiveness of our method. © 2013 Elsevier Inc.
Multiscale Finite Element Methods for Flows on Rough Surfaces
Efendiev, Yalchin
2013-01-01
In this paper, we present the Multiscale Finite Element Method (MsFEM) for problems on rough heterogeneous surfaces. We consider the diffusion equation on oscillatory surfaces. Our objective is to represent small-scale features of the solution via multiscale basis functions described on a coarse grid. This problem arises in many applications where processes occur on surfaces or thin layers. We present a unified multiscale finite element framework that entails the use of transformations that map the reference surface to the deformed surface. The main ingredients of MsFEM are (1) the construction of multiscale basis functions and (2) a global coupling of these basis functions. For the construction of multiscale basis functions, our approach uses the transformation of the reference surface to a deformed surface. On the deformed surface, multiscale basis functions are defined where reduced (1D) problems are solved along the edges of coarse-grid blocks to calculate nodalmultiscale basis functions. Furthermore, these basis functions are transformed back to the reference configuration. We discuss the use of appropriate transformation operators that improve the accuracy of the method. The method has an optimal convergence if the transformed surface is smooth and the image of the coarse partition in the reference configuration forms a quasiuniform partition. In this paper, we consider such transformations based on harmonic coordinates (following H. Owhadi and L. Zhang [Comm. Pure and Applied Math., LX(2007), pp. 675-723]) and discuss gridding issues in the reference configuration. Numerical results are presented where we compare the MsFEM when two types of deformations are used formultiscale basis construction. The first deformation employs local information and the second deformation employs a global information. Our numerical results showthat one can improve the accuracy of the simulations when a global information is used. © 2013 Global-Science Press.
Multiscale feature analysis of salivary gland branching morphogenesis.
Directory of Open Access Journals (Sweden)
Cemal Cagatay Bilgin
Full Text Available Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous
A survey on stochastic multi-scale modeling in biomechanics: computational challenges
Favino, Marco; Pivkin, Igor
2016-01-01
During the last decade, multi-scale models in mechanics, bio-mechanics and life sciences have gained increasing attention. Using multi-scale approaches, effects on different time and length scales, such as, e.g., cellular and organ scale, can be coupled and their interaction can be studied. Clearly, this requires the development of new mathematical models and numerical methods for multi-scale problems, in order to provide reliable and efficient tools for the investigation of multi-scale effects. Here, we give an overview on existing numerical approaches for multi-scale simulations in bio-mechanics with particular emphasis on stochastic effects.
Multi-scale physics mechanisms and spontaneous edge transport bifurcations in fusion plasmas
Hidalgo, C.; Pedrosa, M. A.; Silva, C.; Carralero, D.; Ascasibar, E.; Carreras, B. A.; Estrada, T.; Tabarés, F.; Tafalla, D.; Guasp, J.; Liniers, M.; López-Fraguas, A.; van Milligen, B.; Ochando, M. A.
2009-09-01
The magnitude of radial transport in magnetic confinement devices for controlled nuclear fusion suffers spontaneous bifurcations when specific system parameter values are exceeded. Here we show, for the first time, that the correlation length of the plasma potential becomes of the order of the machine size during the edge bifurcation itself, quite unlike the density fluctuations. The mechanism governing the development of this bifurcation, leading to the establishment of an edge transport barrier, is still one of the main scientific conundrums facing the magnetic fusion community after more than twenty years of intense research. The results presented here show the dominant role of long-range correlations when approaching the Low to High confinement edge transition in fusion plasmas. This is in line with the expectation that multi-scale interactions are a crucial ingredient of complex dynamics in many non-equilibrium systems.
Multi-scale analysis of lung computed tomography images
Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C
2007-01-01
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
Modeling Temporal Evolution and Multiscale Structure in Networks
DEFF Research Database (Denmark)
Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard
2013-01-01
Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...
Rough Set Approach to Incomplete Multiscale Information System
Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu
2014-01-01
Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852
Multiscale modeling of complex materials phenomenological, theoretical and computational aspects
Trovalusci, Patrizia
2014-01-01
The papers in this volume deal with materials science, theoretical mechanics and experimental and computational techniques at multiple scales, providing a sound base and a framework for many applications which are hitherto treated in a phenomenological sense. The basic principles are formulated of multiscale modeling strategies towards modern complex multiphase materials subjected to various types of mechanical, thermal loadings and environmental effects. The focus is on problems where mechanics is highly coupled with other concurrent physical phenomena. Attention is also focused on the historical origins of multiscale modeling and foundations of continuum mechanics currently adopted to model non-classical continua with substructure, for which internal length scales play a crucial role.
Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen
Energy Technology Data Exchange (ETDEWEB)
Plechac, Petr [Univ. of Delaware, Newark, DE (United States). Dept. of Mathematical Sciences
2016-03-01
The overall objective of this project was to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics and developing rigorous mathematical techniques and computational algorithms to study such models. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals.
Multiscale Shannon entropy and its application in the stock market
Gu, Rongbao
2017-10-01
In this paper, we perform a multiscale entropy analysis on the Dow Jones Industrial Average Index using the Shannon entropy. The stock index shows the characteristic of multi-scale entropy that caused by noise in the market. The entropy is demonstrated to have significant predictive ability for the stock index in both long-term and short-term, and empirical results verify that noise does exist in the market and can affect stock price. It has important implications on market participants such as noise traders.
Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems
Ringsmuth, Andrew K
2014-01-01
This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.
Computational technology of multiscale modeling the gas flows in microchannels
Podryga, V. O.
2016-11-01
The work is devoted to modeling the gas mixture flows in engineering microchannels under conditions of many scales of computational domain. The computational technology of using the multiscale approach combining macro - and microscopic models is presented. At macrolevel the nature of the flow and the external influence on it are considered. As a model the system of quasigasdynamic equations is selected. At microlevel the correction of gasdynamic parameters and the determination of boundary conditions are made. As a numerical model the Newton's equations and the molecular dynamics method are selected. Different algorithm types used for implementation of multiscale modeling are considered. The results of the model problems for separate stages are given.
Multiscale analysis and nonlinear dynamics from genes to the brain
Schuster, Heinz Georg
2013-01-01
Since modeling multiscale phenomena in systems biology and neuroscience is a highly interdisciplinary task, the editor of the book invited experts in bio-engineering, chemistry, cardiology, neuroscience, computer science, and applied mathematics, to provide their perspectives. Each chapter is a window into the current state of the art in the areas of research discussed and the book is intended for advanced researchers interested in recent developments in these fields. While multiscale analysis is the major integrating theme of the book, its subtitle does not call for bridging the scales from g
Multiscale integration schemes for jump-diffusion systems
Energy Technology Data Exchange (ETDEWEB)
Givon, D.; Kevrekidis, I.G.
2008-12-09
We study a two-time-scale system of jump-diffusion stochastic differential equations. We analyze a class of multiscale integration methods for these systems, which, in the spirit of [1], consist of a hybridization between a standard solver for the slow components and short runs for the fast dynamics, which are used to estimate the effect that the fast components have on the slow ones. We obtain explicit bounds for the discrepancy between the results of the multiscale integration method and the slow components of the original system.
Nanomechanics and Multiscale Modeling of Sustainable Concretes
Zanjani Zadeh, Vahid
The work presented in this dissertation is aimed to implement and further develop the recent advances in material characterization for porous and heterogeneous materials and apply these advances to sustainable concretes. The studied sustainable concretes were concrete containing fly ash and slag, Kenaf fiber reinforced concrete, and lightweight aggregate concrete. All these cement-based materials can be categorized as sustainable concrete, by achieving concrete with high strength while reducing cement consumption. The nanoindentation technique was used to infer the nanomechanical properties of the active hydration phases in bulk cement paste. Moreover, the interfacial transition zone (ITZ) of lightweight aggregate, normal aggregate, and Kenaf fibers were investigated using nanoindentation and imagine techniques, despite difficulties regarding characterizing this region. Samples were also tested after exposure to high temperature to evaluate the damage mechanics of sustainable concretes. It has been shown that there is a direct correlation between the nature of the nanoscale structure of a cement-based material with its macroscopic properties. This was addressed in two steps in this dissertation: (i) Nanoscale characterization of sustainable cementitious materials to understand the different role of fly ash, slag, lightweight aggregate, and Kenaf fibers on nanoscale (ii) Link the nanoscale mechanical properties to macroscale ones with multiscale modeling. The grid indentation technique originally developed for normal concrete was extended to sustainable concretes with more complex microstructure. The relation between morphology of cement paste materials and submicron mechanical properties, indentation modulus, hardness, and dissipated energy is explained in detail. Extensive experimental and analytical approaches were focused on description of the materials' heterogeneous microstructure as function of their composition and physical phenomenon. Quantitative
Macioł, Piotr; Regulski, Krzysztof
2016-08-01
We present a process of semantic meta-model development for data management in an adaptable multiscale modeling framework. The main problems in ontology design are discussed, and a solution achieved as a result of the research is presented. The main concepts concerning the application and data management background for multiscale modeling were derived from the AM3 approach—object-oriented Agile multiscale modeling methodology. The ontological description of multiscale models enables validation of semantic correctness of data interchange between submodels. We also present a possibility of using the ontological model as a supervisor in conjunction with a multiscale model controller and a knowledge base system. Multiscale modeling formal ontology (MMFO), designed for describing multiscale models' data and structures, is presented. A need for applying meta-ontology in the MMFO development process is discussed. Examples of MMFO application in describing thermo-mechanical treatment of metal alloys are discussed. Present and future applications of MMFO are described.
Stochastic multiscale modeling of polycrystalline materials
Wen, Bin
provides a new outlook to multi-scale materials modeling accounting for microstructure and process uncertainties. Predictive materials modeling will accelerate the development of new materials and processes for critical applications in industry.
Multi-scale characterization of topographic anisotropy
Roy, S. G.; Koons, P. O.; Osti, B.; Upton, P.; Tucker, G. E.
2016-05-01
We present the every-direction variogram analysis (EVA) method for quantifying orientation and scale dependence of topographic anisotropy to aid in differentiation of the fluvial and tectonic contributions to surface evolution. Using multi-directional variogram statistics to track the spatial persistence of elevation values across a landscape, we calculate anisotropy as a multiscale, direction-sensitive variance in elevation between two points on a surface. Tectonically derived topographic anisotropy is associated with the three-dimensional kinematic field, which contributes (1) differential surface displacement and (2) crustal weakening along fault structures, both of which amplify processes of surface erosion. Based on our analysis, tectonic displacements dominate the topographic field at the orogenic scale, while a combination of the local displacement and strength fields are well represented at the ridge and valley scale. Drainage network patterns tend to reflect the geometry of underlying active or inactive tectonic structures due to the rapid erosion of faults and differential uplift associated with fault motion. Regions that have uniform environmental conditions and have been largely devoid of tectonic strain, such as passive coastal margins, have predominantly isotropic topography with typically dendritic drainage network patterns. Isolated features, such as stratovolcanoes, are nearly isotropic at their peaks but exhibit a concentric pattern of anisotropy along their flanks. The methods we provide can be used to successfully infer the settings of past or present tectonic regimes, and can be particularly useful in predicting the location and orientation of structural features that would otherwise be impossible to elude interpretation in the field. Though we limit the scope of this paper to elevation, EVA can be used to quantify the anisotropy of any spatially variable property.
Fast Particle Methods for Multiscale Phenomena Simulations
Koumoutsakos, P.; Wray, A.; Shariff, K.; Pohorille, Andrew
2000-01-01
We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.
Multiscale agent-based consumer market modeling.
Energy Technology Data Exchange (ETDEWEB)
North, M. J.; Macal, C. M.; St. Aubin, J.; Thimmapuram, P.; Bragen, M.; Hahn, J.; Karr, J.; Brigham, N.; Lacy, M. E.; Hampton, D.; Decision and Information Sciences; Procter & Gamble Co.
2010-05-01
Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.
A multiscale problem in thermal science
Directory of Open Access Journals (Sweden)
Casenave Fabien
2013-01-01
Full Text Available We consider a multiscale heat problem in civil aviation: determine the temperature field in a plane in flying conditions, with air conditioning. Ventilated electronic components in the bay bring a heat source, introducing a second scale in the problem. First, we present three levels of modelling for the physical phenomena, which are applied to the two sub-problems: the plane and the electronic component. Then, having reduced the complexity of the problem to a linear non-symmetric coercive PDE, we will use the reduced basis method for the electronic component problem. Nous considérons un problème multi-échelle d’aérothermie en aviation civile. Nous souhai- tons déterminer le champ de température dans un avion en conditions de vol, avec présence d’une climatisation. Des composants électroniques ventilés sont présents dans la soute, et constituent une source de chaleur, introduisant une deuxième échelle dans notre problème. Dans un premier temps, nous présentons trois niveaux de modélisation pour le phénomène d’aérothermie, que nous appliquerons aux deux sous-problèmes : l’avion et le composant électronique. Ensuite, nous appliquons la méthode des bases réduites au problème du composant électronique, en considérant des simplifications de modélisation amenant à la résolution numérique d’une EDP elliptique linéaire coercive non-symétrique.
Multiscale mechanical modeling of soft biological tissues
Stylianopoulos, Triantafyllos
2008-10-01
Soft biological tissues include both native and artificial tissues. In the human body, tissues like the articular cartilage, arterial wall, and heart valve leaflets are examples of structures composed of an underlying network of collagen fibers, cells, proteins and molecules. Artificial tissues are less complex than native tissues and mainly consist of a fiber polymer network with the intent of replacing lost or damaged tissue. Understanding of the mechanical function of these materials is essential for many clinical treatments (e.g. arterial clamping, angioplasty), diseases (e.g. arteriosclerosis) and tissue engineering applications (e.g. engineered blood vessels or heart valves). This thesis presents the derivation and application of a multiscale methodology to describe the macroscopic mechanical function of soft biological tissues incorporating directly their structural architecture. The model, which is based on volume averaging theory, accounts for structural parameters such as the network volume fraction and orientation, the realignment of the fibers in response to strain, the interactions among the fibers and the interactions between the fibers and the interstitial fluid in order to predict the overall tissue behavior. Therefore, instead of using a constitutive equation to relate strain to stress, the tissue microstructure is modeled within a representative volume element (RVE) and the macroscopic response at any point in the tissue is determined by solving a micromechanics problem in the RVE. The model was applied successfully to acellular collagen gels, native blood vessels, and electrospun polyurethane scaffolds and provided accurate predictions for permeability calculations in isotropic and oriented fiber networks. The agreement of model predictions with experimentally determined mechanical properties provided insights into the mechanics of tissues and tissue constructs, while discrepancies revealed limitations of the model framework.
Holographic dynamics from multiscale entanglement renormalization ansatz
Chua, Victor; Passias, Vasilios; Tiwari, Apoorv; Ryu, Shinsei
2017-05-01
The multiscale entanglement renormalization ansatz (MERA) is a tensor network based variational ansatz that is capable of capturing many of the key physical properties of strongly correlated ground states such as criticality and topological order. MERA also shares many deep relationships with the AdS/CFT (gauge-gravity) correspondence by realizing a UV complete holographic duality within the tensor networks framework. Motivated by this, we have repurposed the MERA tensor network as an analysis tool to study the real-time evolution of the 1D transverse Ising model in its low-energy excited state sector. We performed this analysis by allowing the ancilla qubits of the MERA tensor network to acquire quantum fluctuations, which yields a unitary transform between the physical (boundary) and ancilla qubit (bulk) Hilbert spaces. This then defines a reversible quantum circuit, which is used as a "holographic transform" to study excited states and their real-time dynamics from the point of the bulk ancillae. In the gapped paramagnetic phase of the transverse field Ising model, we demonstrate the holographic duality between excited states induced by single spin-flips (Ising "magnons") acting on the ground state and single ancilla qubit spin flips. The single ancillae qubit excitation is shown to be stable in the bulk under real-time evolution and hence defines a stable holographic quasiparticle, which we have named the "hologron." Their bulk 2D Hamiltonian, energy spectrum, and dynamics within the MERA network are studied numerically. The "dictionary" between the bulk and boundary is determined and realizes many features of the holographic correspondence in a non-CFT limit of the boundary theory. As an added spin-off, this dictionary together with the extension to multihologron sectors gives us a systematic way to construct quantitatively accurate low-energy effective Hamiltonians.
Magnetospheric Multiscale Overview and Science Objectives
Burch, J. L.; Moore, T. E.; Torbert, R. B.; Giles, B. L.
2015-01-01
Magnetospheric Multiscale (MMS), a NASA four-spacecraft constellation mission launched on March 12, 2015, will investigate magnetic reconnection in the boundary regions of the Earth's magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. The most important goal of MMS is to conduct a definitive experiment to determine what causes magnetic field lines to reconnect in a collisionless plasma. The significance of the MMS results will extend far beyond the Earth's magnetosphere because reconnection is known to occur in interplanetary space and in the solar corona where it is responsible for solar flares and the disconnection events known as coronal mass ejections. Active research is also being conducted on reconnection in the laboratory and specifically in magnetic-confinement fusion devices in which it is a limiting factor in achieving and maintaining electron temperatures high enough to initiate fusion. Finally, reconnection is proposed as the cause of numerous phenomena throughout the universe such as comet-tail disconnection events, magnetar flares, supernova ejections, and dynamics of neutron-star accretion disks. The MMS mission design is focused on answering specific questions about reconnection at the Earth's magnetosphere. The prime focus of the mission is on determining the kinetic processes occurring in the electron diffusion region that are responsible for reconnection and that determine how it is initiated; but the mission will also place that physics into the context of the broad spectrum of physical processes associated with reconnection. Connections to other disciplines such as solar physics, astrophysics, and laboratory plasma physics are expected to be made through theory and modeling as informed by the MMS results.
Romeny, Bart M Haar
2008-01-01
Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective
Multiscale seismic tomography and mantle dynamics
Zhao, Dapeng
2010-05-01
Multiscale (local, regional and global) tomographic studies are made to determine the 3-D structure of the Earth, particularly for imaging mantle plumes and subducting slabs. Plume-like slow anomalies are clearly visible under the major hotspot regions in most parts of the mantle, in particular, under Hawaii, Iceland, Kerguelen, South Pacific and Africa (Zhao, 2001, 2004, 2009). The slow anomalies under South Pacific and Africa have lateral extensions of over 1000 km and exist in the entire mantle, representing two superplumes. The Pacific superplume has a larger spatial extent and stronger slow anomalies than that of the Africa superplume. The Hawaiian plume is not part of the Pacific superplume but an independent whole-mantle plume (Zhao, 2004, 2009). The slow anomalies under hotspots usually do not show a straight pillar shape, but exhibit winding images, suggesting that plumes are not fixed in the mantle but can be deflected by the mantle flow. As a consequence, hotspots are not really fixed but can wander on the Earth's surface, as evidenced by the recent paleomagnetic and numeric modeling studies. Wider and more prominent slow anomalies are visible at the core-mantle boundary (CMB) than most of the lower mantle, and there is a good correlation between the distribution of slow anomalies at the CMB and that of hotspots on the surface, suggesting that most of the strong mantle plumes under the hotspots originate from the CMB. However, there are some small-scaled, weak plumes originating from the transition zone or mid mantle depths (Zhao et al., 2006; Zhao, 2009; Lei et al., 2009; Gupta et al., 2009). Clear images of subducting slabs and magma chambers in the upper-mantle wedge beneath active arc volcanoes are obtained, indicating that geodynamic systems associated with arc magmatism and back-arc spreading are related to deep processes, such as convective circulation in the mantle wedge and dehydration reactions of the subducting slab (Zhao et al., 2002, 2007
EPOS Multi-Scale Laboratory platform: a long-term reference tool for experimental Earth Sciences
Trippanera, Daniele; Tesei, Telemaco; Funiciello, Francesca; Sagnotti, Leonardo; Scarlato, Piergiorgio; Rosenau, Matthias; Elger, Kirsten; Ulbricht, Damian; Lange, Otto; Calignano, Elisa; Spiers, Chris; Drury, Martin; Willingshofer, Ernst; Winkler, Aldo
2017-04-01
With continuous progress on scientific research, a large amount of datasets has been and will be produced. The data access and sharing along with their storage and homogenization within a unique and coherent framework is a new challenge for the whole scientific community. This is particularly emphasized for geo-scientific laboratories, encompassing the most diverse Earth Science disciplines and typology of data. To this aim the "Multiscale Laboratories" Work Package (WP16), operating in the framework of the European Plate Observing System (EPOS), is developing a virtual platform of geo-scientific data and services for the worldwide community of laboratories. This long-term project aims at merging the top class multidisciplinary laboratories in Geoscience into a coherent and collaborative network, facilitating the standardization of virtual access to data, data products and software. This will help our community to evolve beyond the stage in which most of data produced by the different laboratories are available only within the related scholarly publications (often as print-version only) or they remain unpublished and inaccessible on local devices. The EPOS multi-scale laboratory platform will provide the possibility to easily share and discover data by means of open access, DOI-referenced, online data publication including long-term storage, managing and curation services and to set up a cohesive community of laboratories. The WP16 is starting with three pilot cases laboratories: (1) rock physics, (2) palaeomagnetic, and (3) analogue modelling. As a proof of concept, first analogue modelling datasets have been published via GFZ Data Services (http://doidb.wdc-terra.org/search/public/ui?&sort=updated+desc&q=epos). The datasets include rock analogue material properties (e.g. friction data, rheology data, SEM imagery), as well as supplementary figures, images and movies from experiments on tectonic processes. A metadata catalogue tailored to the specific communities
A multiscale two-point flux-approximation method
Møyner, Olav; Lie, Knut-Andreas
2014-10-01
A large number of multiscale finite-volume methods have been developed over the past decade to compute conservative approximations to multiphase flow problems in heterogeneous porous media. In particular, several iterative and algebraic multiscale frameworks that seek to reduce the fine-scale residual towards machine precision have been presented. Common for all such methods is that they rely on a compatible primal-dual coarse partition, which makes it challenging to extend them to stratigraphic and unstructured grids. Herein, we propose a general idea for how one can formulate multiscale finite-volume methods using only a primal coarse partition. To this end, we use two key ingredients that are computed numerically: (i) elementary functions that correspond to flow solutions used in transmissibility upscaling, and (ii) partition-of-unity functions used to combine elementary functions into basis functions. We exemplify the idea by deriving a multiscale two-point flux-approximation (MsTPFA) method, which is robust with regards to strong heterogeneities in the permeability field and can easily handle general grids with unstructured fine- and coarse-scale connections. The method can easily be adapted to arbitrary levels of coarsening, and can be used both as a standalone solver and as a preconditioner. Several numerical experiments are presented to demonstrate that the MsTPFA method can be used to solve elliptic pressure problems on a wide variety of geological models in a robust and efficient manner.
A practical multiscale approach for optimization of structural damping
DEFF Research Database (Denmark)
Andreassen, Erik; Jensen, Jakob Søndergaard
2016-01-01
A simple and practical multiscale approach suitable for topology optimization of structural damping in a component ready for additive manufacturing is presented.The approach consists of two steps: First, the homogenized loss factor of a two-phase material is maximized. This is done in order...
Computer Laboratory for Multi-scale Simulations of Novel Nanomaterials
2014-09-15
Patents Submitted Patents Awarded Awards Graduate Students Names of Post Doctorates Names of Faculty Supported Names of Under Graduate students...on sulfonated polystyrene containing block-copolymers, we developed a hierarchical multiscale methodology for computational studies of the membrane...hydrated polyelectrolytes. Three types of hydrated polyelectrolytes were considered Nafion, sulfonated polystyrene (sPS) that forms the hydrophilic
Multiscale analysis of structure development in expanded starch snacks
Sman, van der R.G.M.; Broeze, J.
2014-01-01
In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the mo
Adaptive Multiscale Finite Element Method for Subsurface Flow Simulation
Van Esch, J.M.
2010-01-01
Natural geological formations generally show multiscale structural and functional heterogeneity evolving over many orders of magnitude in space and time. In subsurface hydrological simulations the geological model focuses on the structural hierarchy of physical sub units and the flow model addresses
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
DEFF Research Database (Denmark)
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximati...
Special Column on Multiscale Stochastic Finite Element Method
Institute of Scientific and Technical Information of China (English)
2015-01-01
In the past decade, multi-scale modelling in mathema- tical physics and engineering has been growing with vast advancement based on deterministic assumption. Because all information across scales contains a certain level of uncertainty due to incomplete knowledge and inherent chaos with respect to physical laws and parameters.
Multi-Scale Pattern Recognition for Image Classification and Segmentation
Li, Y.
2013-01-01
Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basi
Homogeneous Turbulence Generated by Multi-scale Grids
Energy Technology Data Exchange (ETDEWEB)
Krogstad, Per-Age [Norwegian University of Science and Technology, N-7491 Trondheim (Norway); Davidson, Peter, E-mail: per.a.krogstad@ntnu.no [University of Cambridge, Cambridge CB2 1PZ (United Kingdom)
2011-12-22
We investigate wind tunnel turbulence generated by a conventional and two multi-scale grids. The conventional and multi-scale grids were all designed to produce turbulence with the same integral scale, so that a direct comparison could be made between the different flows. The decay of the turbulent energy was mapped in detail from a distance from the grid less than one mesh width, down to distances of the order of 200 meshes using a combination of laser doppler and hot wire anemometry tools. The turbulent decay rate behind our multi-scale grids was found to be virtually identical to that behind the equivalent conventional grid after the initial transition had been completed. In particular, all flows exhibit a power-law decay of energy, u{sup 2} {approx} t{sup -n}, where n is very close to the classical Saffman exponent of n = 6/5 in the far field. Our results are at odds with some other experiments performed on multi-scale grids, where significantly higher energy decay exponents have been reported.
Benchmark of Schemes for Multiscale Molecular Dynamics Simulations
Goga, N.; Melo, M. N.; Rzepiela, A. J.; de Vries, Alex; Hadar, A.; Marrink, S. J.; Berendsen, Herman
2015-01-01
In multiscale molecular dynamics simulations the accuracy of detailed models is combined with the efficiency of a reduced representation. For several applications - namely those of sampling enhancement - it is desirable to combine fine-grained (FG) and coarse-grained (CG) approaches into a single hy
Cooperative Research Alliance Multiscale Modeling of Electronic Materials (MSME)
2010-11-19
transport characterization in nano-scale structures DC-40GHz environmental cryogenic I/V probe station Spectral dissection of bacteria and thin-films...Sensors and actuators for microrobots Graphene Flexible Displays Family of UGS Compact Radar Carbon Nanotubes Environmental Sensing Reformed...simulations • Develop innovative experimentation & validation techniques • Define multiscale material metrics • Perform processing & synthesis Multi
Intensify Denoisy Image Using Adaptive Multiscale Product Thresholding
Directory of Open Access Journals (Sweden)
Mr. Anup T. Gadre,
2015-06-01
Full Text Available This Paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. This paper proposed a method based on image de-noising and edge enhancement of noisy multidimensional imaging data sets. Medical images are generally suffered from signal dependent noises i.e. speckle noise and broken edges. Most of the noises signals appear from machine and environment generally not contribute to the tissue differentiation. But, the noise generated due to above mentioned reason causes a grainy appearance on the image, hence image enhancement is required. For the intent of image denoising, Adaptive Multiscale Product Thresholding based on 2-D wavelet transform is used. In this method, contiguous wavelet sub bands are multiplied to improve edge structure while reducing noise. In multiscale products, boundaries can be successfully distinguished from noise. Adaptive threshold is designed and forced on multiscale products as an alternative of wavelet coefficients or recognize important features. For the edge enhancement. Canny Edge Detection Algorithm is used with scale multiplication technique. Simulation results shows that the planned technique better suppress the Poisson noise among several noises i.e. salt & pepper, speckle noise and random noise. The Performance of Image Intesification can be estimate by means of PSNR, MSE.
On a multiscale approach for filter efficiency simulations
Iliev, Oleg P.
2014-07-01
Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.
Randomized Oversampling for Generalized Multiscale Finite Element Methods
Calo, Victor M.
2016-03-23
In this paper, we develop efficient multiscale methods for flows in heterogeneous media. We use the generalized multiscale finite element (GMsFEM) framework. GMsFEM approximates the solution space locally using a few multiscale basis functions. This approximation selects an appropriate snapshot space and a local spectral decomposition, e.g., the use of oversampled regions, in order to achieve an efficient model reduction. However, the successful construction of snapshot spaces may be costly if too many local problems need to be solved in order to obtain these spaces. We use a moderate quantity of local solutions (or snapshot vectors) with random boundary conditions on oversampled regions with zero forcing to deliver an efficient methodology. Motivated by the randomized algorithm presented in [P. G. Martinsson, V. Rokhlin, and M. Tygert, A Randomized Algorithm for the approximation of Matrices, YALEU/DCS/TR-1361, Yale University, 2006], we consider a snapshot space which consists of harmonic extensions of random boundary conditions defined in a domain larger than the target region. Furthermore, we perform an eigenvalue decomposition in this small space. We study the application of randomized sampling for GMsFEM in conjunction with adaptivity, where local multiscale spaces are adaptively enriched. Convergence analysis is provided. We present representative numerical results to validate the method proposed.
Coarse-grained sensitivity for multiscale data assimilation
Sugiura, Nozomi
2015-01-01
We show that the effective average action and its gradient are useful for solving multiscale data assimilation problems. We also present a procedure for numerically evaluating the gradient of the effective average action, and demonstrate that the variational problem for slow degrees of freedom can be solved properly using the "effective gradient."
A Liver-centric Multiscale Modeling Framework for Xenobiotics
We describe a multi-scale framework for modeling acetaminophen-induced liver toxicity. Acetaminophen is a widely used analgesic. Overdose of acetaminophen can result in liver injury via its biotransformation into toxic product, which further induce massive necrosis. Our study foc...
Multiscale modeling and simulation of brain blood flow
Energy Technology Data Exchange (ETDEWEB)
Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)
2016-02-15
The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.
Riparian ecosystems and buffers - multiscale structure, function, and management: introduction
Kathleen A. Dwire; Richard R. Lowrance
2006-01-01
Given the importance of issues related to improved understanding and management of riparian ecosystems and buffers, the American Water Resources Association (AWRA) sponsored a Summer Specialty Conference in June 2004 at Olympic Valley, California, entitled 'Riparian Ecosystems and Buffers: Multiscale Structure, Function, and Management.' The primary objective...
Multiscale perspectives of species richness in East Africa
Said, M.
2003-01-01
This dissertation describes and analyses animal species richness in East Africa from a multi-scale perspective. We studied diversity patterns at sub-continental, national and sub-national level. The study demonstrated that species diversity patterns were scale-dependent. Diversity patterns varied wi
Multi-scale modeling in microstructure evolution of materials
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Intelligent design and control of the microstructure to tailor properties of materials is the dream that materials scientists have been worked hard for many years. Formation of research area of computational materials science paves the way to realize the dream. Simulation of microstructure evolution is a chief branch of the computational materials science and has caused great attention from materials researchers. Multi-scale modeling gets popular just within 5- 6 years recently due to huge research works to try to shorten the distance between simulation and application. People have to command one or more classical simulation methods in order to do the multi-scale modeling so chief simulation methods will be discussed first and then more reviews in detail are given to the phase field simulation. The main part of the paper is carried out to introduce two key approaches to do the multi-scale modeling job. It is suggested that extension of the multiscale modeling is necessary to study the technologies to link microstructure simulation, processing simulation and property simulation each other as well as to build bridges between different simulation methods and between analytical models and numerical models.
Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation
Energy Technology Data Exchange (ETDEWEB)
Tchelepi, Hamdi
2014-11-14
A multiscale linear-solver framework for the pressure equation associated with flow in highly heterogeneous porous formations was developed. The multiscale based approach is cast in a general algebraic form, which facilitates integration of the new scalable linear solver in existing flow simulators. The Algebraic Multiscale Solver (AMS) is employed as a preconditioner within a multi-stage strategy. The formulations investigated include the standard MultiScale Finite-Element (MSFE) andMultiScale Finite-Volume (MSFV) methods. The local-stage solvers include incomplete factorization and the so-called Correction Functions (CF) associated with the MSFV approach. Extensive testing of AMS, as an iterative linear solver, indicate excellent convergence rates and computational scalability. AMS compares favorably with advanced Algebraic MultiGrid (AMG) solvers for highly detailed three-dimensional heterogeneous models. Moreover, AMS is expected to be especially beneficial in solving time-dependent problems of coupled multiphase flow and transport in large-scale subsurface formations.
Multiscale patterned transplantable stem cell patches for bone tissue regeneration.
Kim, Jangho; Bae, Won-Gyu; Choung, Han-Wool; Lim, Ki Taek; Seonwoo, Hoon; Jeong, Hoon Eui; Suh, Khap-Yang; Jeon, Noo Li; Choung, Pill-Hoon; Chung, Jong Hoon
2014-11-01
Stem cell-based therapy has been proposed as an enabling alternative not only for the treatment of diseases but also for the regeneration of tissues beyond complex surgical treatments or tissue transplantation. In this study, we approached a conceptual platform that can integrate stem cells into a multiscale patterned substrate for bone regeneration. Inspired by human bone tissue, we developed hierarchically micro- and nanopatterned transplantable patches as synthetic extracellular matrices by employing capillary force lithography in combination with a surface micro-wrinkling method using a poly(lactic-co-glycolic acid) (PLGA) polymer. The multiscale patterned PLGA patches were highly flexible and showed higher tissue adhesion to the underlying tissue than did the single nanopatterned patches. In response to the anisotropically multiscale patterned topography, the adhesion and differentiation of human mesenchymal stem cells (hMSCs) were sensitively controlled. Furthermore, the stem cell patch composed of hMSCs and transplantable PLGA substrate promoted bone regeneration in vivo when both the micro- and nanotopography of the substrate surfaces were synergistically combined. Thus, our study concludes that multiscale patterned transplantable stem cell patches may have a great potential for bone regeneration as well as for various regenerative medicine approaches.
Adaptive Multiscale Finite Element Method for Subsurface Flow Simulation
Van Esch, J.M.
2010-01-01
Natural geological formations generally show multiscale structural and functional heterogeneity evolving over many orders of magnitude in space and time. In subsurface hydrological simulations the geological model focuses on the structural hierarchy of physical sub units and the flow model addresses
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I. Y.
2016-05-18
In this paper, we develop a multiscale model reduction technique that describes shale gas transport in fractured media. Due to the pore-scale heterogeneities and processes, we use upscaled models to describe the matrix. We follow our previous work (Akkutlu et al. Transp. Porous Media 107(1), 235–260, 2015), where we derived an upscaled model in the form of generalized nonlinear diffusion model to describe the effects of kerogen. To model the interaction between the matrix and the fractures, we use Generalized Multiscale Finite Element Method (Efendiev et al. J. Comput. Phys. 251, 116–135, 2013, 2015). In this approach, the matrix and the fracture interaction is modeled via local multiscale basis functions. In Efendiev et al. (2015), we developed the GMsFEM and applied for linear flows with horizontal or vertical fracture orientations aligned with a Cartesian fine grid. The approach in Efendiev et al. (2015) does not allow handling arbitrary fracture distributions. In this paper, we (1) consider arbitrary fracture distributions on an unstructured grid; (2) develop GMsFEM for nonlinear flows; and (3) develop online basis function strategies to adaptively improve the convergence. The number of multiscale basis functions in each coarse region represents the degrees of freedom needed to achieve a certain error threshold. Our approach is adaptive in a sense that the multiscale basis functions can be added in the regions of interest. Numerical results for two-dimensional problem are presented to demonstrate the efficiency of proposed approach. © 2016 Springer International Publishing Switzerland
Multi-scale MSDT inversion based on LAI spatial knowledge
Institute of Scientific and Technical Information of China (English)
ZHU XiaoHua; FENG XiaoMing; ZHAO YingShi
2012-01-01
Quantitative remote sensing inversion is ill-posed.The Moderate Resolution Imaging Spectroradiometer at 250 m resolution (MODIS_250m) contains two bands.To deal with this ill-posed inversion of MODIS_250m data,we propose a framework,the Multi-scale,Multi-stage,Sample-direction Dependent,Target-decisions (Multi-scale MSDT) inversion method,based on spatial knowledge.First,MODIS images (1 km,500 m,250 m) are used to extract multi-scale spatial knowledge.The inversion accuracy of MODIS_1km data is improved by reducing the impact of spatial heterogeneity.Then,coarse-scale inversion is taken as prior knowledge for the fine scale,again by inversion.The prior knowledge is updated after each inversion step.At each scale,MODIS_1km to MODIS_250m,the inversion is directed by the Uncertainty and Sensitivity Matrix (USM),and the most uncertain parameters are inversed by the most sensitive data.All remote sensing data are involved in the inversion,during which multi-scale spatial knowledge is introduced,to reduce the impact of spatial heterogeneity.The USM analysis is used to implement a reasonable allocation of limited remote sensing data in the model space.In the entire multi-scale inversion process,field data,spatial knowledge and multi-scale remote sensing data are all involved.As the multi-scale,multi-stage inversion is gradually refined,initial expectations of parameters become more reasonable and their uncertainty range is effectively reduced,so that the inversion becomes increasingly targeted.Finally,the method is tested by retrieving the Leaf Area Index (LAI) of the crop canopy in the Heihe River Basin.The results show that the proposed method is reliable.
Multiscale stabilization for convection-dominated diffusion in heterogeneous media
Calo, Victor M.
2016-02-23
We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion, which may not be sufficient to stabilize multiscale systems. We seek a local reduced-order model for this kind of multiscale transport problems and thus, develop a systematic approach for finding reduced-order approximations of the solution. We start from a Petrov-Galerkin framework using optimal weighting functions. We introduce an auxiliary variable to a mixed formulation of the problem. The auxiliary variable stands for the optimal weighting function. The problem reduces to finding a test space (a dimensionally reduced space for this auxiliary variable), which guarantees that the error in the primal variable (representing the solution) is close to the projection error of the full solution on the dimensionally reduced space that approximates the solution. To find the test space, we reformulate some recent mixed Generalized Multiscale Finite Element Methods. We introduce snapshots and local spectral problems that appropriately define local weight and trial spaces. In particular, we use energy minimizing snapshots and local spectral decompositions in the natural norm associated with the auxiliary variable. The resulting spectral decomposition adaptively identifies and builds the optimal multiscale space to stabilize the system. We discuss the stability and its relation to the approximation property of the test space. We design online basis functions, which accelerate convergence in the test space, and consequently, improve stability. We present several numerical examples and show that one needs a few test functions to achieve an error similar to the projection error in the primal variable irrespective of the Peclet number.
Probabilistic multiscale image segmentation by the hyperstack
Vincken, Koenraad Lucas
2001-01-01
In the medical community, images from different modalities have found their way to a variety of medical disciplines. Multidimensional images have become indispensable in clinical diagnosis, therapy planning and evaluation. Image segmentation -- dividing an image into meaningful objects -- is a s
Study on Key Techniques for Multi-scale Expression of Laneway Traverse Data in MGIS
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The multi-scale expression of enormously complicated laneway data requires differentiation of both contents and the way the contents are expressed.To accomplish multi-scale expression laneway data must support multi-scale transformation and have consistent topological relationships.Although the laneway data generated by traverse surveying is non-scale data it is still impossible to construct a multi-scale spatial database directly from it.In this paper an algorithm is presented to first calculate the laneway mid-line to support multi-scale transformation; then to express topological relationships arising from the data structure; and, finally, a laneway spatial database is built and multi-scale expression is achieved using components GIS-SuperMap Objects.The research result is of great significance for improving the efficiency of laneway data storage and updating, for ensuring consistency of laneway data expression and for extending the potential value of a mine spatial database.
Generalized multiscale finite element method for non-Newtonian fluid flow in perforated domain
Chung, E. T.; Iliev, O.; Vasilyeva, M. V.
2016-10-01
In this work, we consider a non-Newtonian fluid flow in perforated domains. Fluid flow in perforated domains have a multiscale nature and solution techniques for such problems require high resolution. In particular, the discretization needs to honor the irregular boundaries of perforations. This gives rise to a fine-scale problems with many degrees of freedom which can be very expensive to solve. In this work, we develop a multiscale approach that attempt to solve such problems on a coarse grid by constructing multiscale basis functions. We follow Generalized Multiscale Finite Element Method (GMsFEM) [1, 2] and develop a multiscale procedure where we identify multiscale basis functions in each coarse block using snapshot space and local spectral problems [3, 4]. We show that with a few basis functions in each coarse block, one can accurately approximate the solution, where each coarse block can contain many small inclusions.
A Generalized Multiscale Finite Element Method for Poroelasticity Problems I: Linear Problems
Brown, Donald L
2015-01-01
In this paper, we consider the numerical solution of poroelasticity problems that are of Biot type and develop a general algorithm for solving coupled systems. We discuss the challenges associated with mechanics and flow problems in heterogeneous media. The two primary issues being the multiscale nature of the media and the solutions of the fluid and mechanics variables traditionally developed with separate grids and methods. For the numerical solution we develop and implement a Generalized Multiscale Finite Element Method (GMsFEM) that solves problem on a coarse grid by constructing local multiscale basis functions. The procedure begins with construction of multiscale bases for both displacement and pressure in each coarse block. Using a snapshot space and local spectral problems, we construct a basis of reduced dimension. Finally, after multiplying by a multiscale partitions of unity, the multiscale basis is constructed in the offline phase and the coarse grid problem then can be solved for arbitrary forcin...
Multiscale/multiresolution landslides susceptibility mapping
Grozavu, Adrian; Cătălin Stanga, Iulian; Valeriu Patriche, Cristian; Toader Juravle, Doru
2014-05-01
Within the European strategies, landslides are considered an important threatening that requires detailed studies to identify areas where these processes could occur in the future and to design scientific and technical plans for landslide risk mitigation. In this idea, assessing and mapping the landslide susceptibility is an important preliminary step. Generally, landslide susceptibility at small scale (for large regions) can be assessed through qualitative approach (expert judgements), based on a few variables, while studies at medium and large scale requires quantitative approach (e.g. multivariate statistics), a larger set of variables and, necessarily, the landslide inventory. Obviously, the results vary more or less from a scale to another, depending on the available input data, but also on the applied methodology. Since it is almost impossible to have a complete landslide inventory on large regions (e.g. at continental level), it is very important to verify the compatibility and the validity of results obtained at different scales, identifying the differences and fixing the inherent errors. This paper aims at assessing and mapping the landslide susceptibility at regional level through a multiscale-multiresolution approach from small scale and low resolution to large scale and high resolution of data and results, comparing the compatibility of results. While the first ones could be used for studies at european and national level, the later ones allows results validation, including through fields surveys. The test area, namely the Barlad Plateau (more than 9000 sq.km) is located in Eastern Romania, covering a region where both the natural environment and the human factor create a causal context that favor these processes. The landslide predictors were initially derived from various databases available at pan-european level and progressively completed and/or enhanced together with scale and the resolution: the topography (from SRTM at 90 meters to digital
Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling
Energy Technology Data Exchange (ETDEWEB)
Du, Qiang [Pennsylvania State Univ., State College, PA (United States)
2014-11-12
The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of which is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next
Modeling Damage in Composite Materials Using an Enrichment Based Multiscale Method
2015-03-01
Technical Report ARWSB-TR-15002 Modeling Damage in Composite Materials Using an Enrichment Based Multiscale Method Michael F...4. TITLE AND SUBTITLE Modeling Damage in Composite Materials Using an Enrichment Based Multiscale Method 5a. CONTRACT NUMBER 5b...the RVE and how microdamage can be incorporated into the model . For many applications the material used in the multiscale model is some type of fiber
Shi, Wuzhen; Jiang, Feng; Zhao, Debin
2017-01-01
Traditional works have shown that patches in a natural image tend to redundantly recur many times inside the image, both within the same scale, as well as across different scales. Make full use of these multi-scale information can improve the image restoration performance. However, the current proposed deep learning based restoration methods do not take the multi-scale information into account. In this paper, we propose a dilated convolution based inception module to learn multi-scale informa...
OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH
Directory of Open Access Journals (Sweden)
Y. Jia
2016-06-01
Full Text Available 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.
Directory of Open Access Journals (Sweden)
Won-Gyu Bae
2015-12-01
Full Text Available Engineering complex extracellular matrix (ECM is an important challenge for cell and tissue engineering applications as well as for understanding fundamental cell biology. We developed the methodology for fabrication of precisely controllable multiscale hierarchical structures using capillary force lithography in combination with original wrinkling technique for the generation of well-defined native ECM-like platforms by culturing fibroblast cells on the multiscale substrata [1]. This paper provides information on detailed characteristics of polyethylene glycol-diacrylate multiscale substrata. In addition, a possible model for guided extracellular matrix formation from fibroblast cells cultured on bio-inspired configurable multiscale substrata is proposed.
Multi-scale morphology of the galaxy distribution
Saar, E; Starck, J L; Donoho, D L; Saar, Enn; Martinez, Vicent J.; Starck, Jean-Luc; Donoho, David L.
2006-01-01
Many statistical methods have been proposed in the last years for analyzing the spatial distribution of galaxies. Very few of them, however, can handle properly the border effects of complex observational sample volumes. In this paper, we first show how to calculate the Minkowski Functionals (MF) taking into account these border effects. Then we present a multiscale extension of the MF which gives us more information about how the galaxies are spatially distributed. A range of examples using Gaussian random fields illustrate the results. Finally we have applied the Multiscale Minkowski Functionals (MMF) to the 2dF Galaxy Redshift Survey data. The MMF clearly indicates an evolution of morphology with scale. We also compare the 2dF real catalog with mock catalogs and found that Lambda-CDM simulations roughly fit the data, except at the finest scale.
Multiscale Turbulence Models Based on Convected Fluid Microstructure
Holm, Darryl D
2012-01-01
The Euler-Poincar\\'e approach to complex fluids is used to derive multiscale equations for computationally modelling Euler flows as a basis for modelling turbulence. The model is based on a \\emph{kinematic sweeping ansatz} (KSA) which assumes that the mean fluid flow serves as a Lagrangian frame of motion for the fluctuation dynamics. Thus, we regard the motion of a fluid parcel on the computationally resolvable length scales as a moving Lagrange coordinate for the fluctuating (zero-mean) motion of fluid parcels at the unresolved scales. Even in the simplest 2-scale version on which we concentrate here, the contributions of the fluctuating motion under the KSA to the mean motion yields a system of equations that extends known results and appears to be suitable for modelling nonlinear backscatter (energy transfer from smaller to larger scales) in turbulence using multiscale methods.
A Multiscale Wavelet Solver with O( n) Complexity
Williams, John R.; Amaratunga, Kevin
1995-11-01
In this paper, we use the biorthogonal wavelets recently constructed by Dahlke and Weinreich to implement a highly efficient procedure for solving a certain class of one-dimensional problems, (∂21/∂x21)u = f,I ɛ Z, I > 0. For these problems, the discrete biorthogonal wavelet transform allows us to set up a system of wavelet-Galerkin equations in which the scales are uncoupled, so that a true multiscale solution procedure may be formulated. We prove that the resulting stiffness matrix is in fact an almost perfectly diagonal matrix (the original aim of the construction was to achieve a block diagonal structure) and we show that this leads to an algorithm whose cost is O(n). We also present numerical results which demonstrate that the multiscale biorthogonal wavelet algorithm is superior to the more conventional single scale orthogonal wavelet approach both in terms of speed and in terms of convergence.
Multi-scale atmospheric environment modelling for urban areas
Directory of Open Access Journals (Sweden)
A. A. Baklanov
2009-04-01
Full Text Available Modern supercomputers allow realising multi-scale systems for assessment and forecasting of urban meteorology, air pollution and emergency preparedness and considering nesting with obstacle-resolved models. A multi-scale modelling system with downscaling from regional to city-scale with the Environment – HIgh Resolution Limited Area Model (Enviro-HIRLAM and to micro-scale with the obstacle-resolved Micro-scale Model for Urban Environment (M2UE is suggested and demonstrated. The M2UE validation results versus the Mock Urban Setting Trial (MUST experiment indicate satisfactory quality of the model. Necessary conditions for the choice of nested models, building descriptions, areas and resolutions of nested models are analysed. Two-way nesting (up- and down-scaling, when scale effects both directions (from the meso-scale on the micro-scale and from the micro-scale on the meso-scale, is also discussed.
Wavelet correlations to reveal multiscale coupling in geophysical systems
Casagrande, Erik; Miralles, Diego; Entekhabi, Dara; Molini, Annalisa
2015-01-01
The interactions between climate and the environment are highly complex. Due to this complexity, process-based models are often preferred to estimate the net magnitude and directionality of interactions in the Earth System. However, these models are based on simplifications of our understanding of nature, thus are unavoidably imperfect. Conversely, observation-based data of climatic and environmental variables are becoming increasingly accessible over large scales due to the progress of space-borne sensing technologies and data-assimilation techniques. Albeit uncertain, these data enable the possibility to start unraveling complex multivariable, multiscale relationships if the appropriate statistical methods are applied. Here, we investigate the potential of the wavelet cross-correlation method as a tool for identifying multiscale interactions, feedback and regime shifts in geophysical systems. The ability of wavelet cross-correlation to resolve the fast and slow components of coupled systems is tested on syn...
Multiscale MRF-based Texture Segmentation of SAR Image
Institute of Scientific and Technical Information of China (English)
XUXin; LIDeren; SUNHong
2004-01-01
We propose a multiscale Bayesian segmentation algorithm for SAR image in this paper. A hierarchical two-level Markov random field (MRF) is applied to represent both texture and region label over the wavelet lattice. The high level uses an isotropic Multi-level logistic (MLL) random field to characterize the blob-like region formation process at each scale and the interscale dependencies over the corresponding multiresolution region. At lower level a novel Causal Gaussian autoregressive (CGAR) process is proposed to describe the fill-in of multiresolution region. Once the multiscale double MRFs model is established, in term of Sequential maximum a posteriori (SMAP), model parameter estimate and region segmentation are performed alternately from coarse to fine scale. Our segmentation method is tested on both synthetic and ERS-1 SAR images.
Multiscale singular value manifold for rotating machinery fault diagnosis
Energy Technology Data Exchange (ETDEWEB)
Feng, Yi; Lu, BaoChun; Zhang, Deng Feng [School of Mechanical Engineering, Nanjing University of Science and Technology,Nanjing (United States)
2017-01-15
Time-frequency distribution of vibration signal can be considered as an image that contains more information than signal in time domain. Manifold learning is a novel theory for image recognition that can be also applied to rotating machinery fault pattern recognition based on time-frequency distributions. However, the vibration signal of rotating machinery in fault condition contains cyclical transient impulses with different phrases which are detrimental to image recognition for time-frequency distribution. To eliminate the effects of phase differences and extract the inherent features of time-frequency distributions, a multiscale singular value manifold method is proposed. The obtained low-dimensional multiscale singular value manifold features can reveal the differences of different fault patterns and they are applicable to classification and diagnosis. Experimental verification proves that the performance of the proposed method is superior in rotating machinery fault diagnosis.
Walklets: Multiscale Graph Embeddings for Interpretable Network Classification
Perozzi, Bryan; Skiena, Steven
2016-01-01
We present Walklets, a novel approach for learning multiscale representations of vertices in a network. These representations clearly encode multiscale vertex relationships in a continuous vector space suitable for multi-label classification problems. Unlike previous work, the latent features generated using Walklets are analytically derivable, and human interpretable. Walklets uses the offsets between vertices observed in a random walk to learn a series of latent representations, each which captures successively larger relationships. This variety of dependency information allows the same representation strategy to model phenomenon which occur at different scales. We demonstrate Walklets' latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that Walklets outperforms new methods based on neural matrix factorization, and can scale to graphs with millions of vertices and edges.
Multiscale modeling and simulation of nanotube-based torsional oscillators
Directory of Open Access Journals (Sweden)
Xiao Shaoping
2006-01-01
Full Text Available AbstractIn this paper, we propose the first numerical study of nanotube-based torsional oscillators via developing a new multiscale model. The edge-to-edge technique was employed in this multiscale method to couple the molecular model, i.e., nanotubes, and the continuum model, i.e., the metal paddle. Without losing accuracy, the metal paddle was treated as the rigid body in the continuum model. Torsional oscillators containing (10,0 nanotubes were mainly studied. We considered various initial angles of twist to depict linear/nonlinear characteristics of torsional oscillators. Furthermore, effects of vacancy defects and temperature on mechanisms of nanotube-based torsional oscillators were discussed.
RBF Multiscale Collocation for Second Order Elliptic Boundary Value Problems
Farrell, Patricio
2013-01-01
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multilevel fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. On each level, standard symmetric collocation is employed. A convergence theory is given, which builds on recent theoretical advances for multiscale approximation using compactly supported radial basis functions. We are able to show that the convergence is linear in the number of levels. We also discuss the condition numbers of the arising systems and the effect of simple, diagonal preconditioners, now proving rigorously previous numerical observations. © 2013 Society for Industrial and Applied Mathematics.
Materials with internal structure multiscale and multifield modeling and simulation
2016-01-01
The book presents a series of concise papers by researchers specialized in various fields of continuum and computational mechanics and of material science. The focus is on principles and strategies for multiscale modeling and simulation of complex heterogeneous materials, with periodic or random microstructure, subjected to various types of mechanical, thermal, chemical loadings and environmental effects. A wide overview of complex behavior of materials (plasticity, damage, fracture, growth, etc.) is provided. Among various approaches, attention is given to advanced non-classical continua modeling which, provided by constitutive characterization for the internal and external actions (in particular boundary conditions), is a very powerful frame for the gross mechanical description of complex material behaviors, able to circumvent the restrictions of classical coarse–graining multiscale approaches.
Multiscale-tailored bioelectrode surfaces for optimized catalytic conversion efficiency.
Bon Saint Côme, Yémima; Lalo, Hélène; Wang, Zhijie; Etienne, Mathieu; Gajdzik, Janine; Kohring, Gert-Wieland; Walcarius, Alain; Hempelmann, Rolf; Kuhn, Alexander
2011-10-18
We describe the elaboration of a multiscale-tailored bioelectrocatalytic system. The combination of two enzymes, D-sorbitol dehydrogenase and diaphorase, is studied with respect to the oxidation of D-sorbitol as a model system. The biomolecules are immobilized in an electrodeposited paint (EDP) layer. Reproducible and efficient catalysis of D-sorbitol oxidation is recorded when this system is immobilized on a gold electrode modified by a self-assembled monolayer of 4-carboxy-(2,5,7-trinitro-9-fluorenylidene)malonitrile used as a mediator. The insertion of mediator-modified gold nanoparticles into the EDP film increases significantly the active surface area for the catalytic reaction, which can be further enhanced when the whole system is immobilized in macroporous gold electrodes. This multiscale architecture finally leads to a catalytic device with optimized efficiency for potential use in biosensors, bioelectrosynthesis, and biofuel cells.
Complexity of carbon market from multi-scale entropy analysis
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.
MULTI-SCALE STRUCTURES IN EMULSION AND MICROSPHERE COMPLEX SYSTEMS
Institute of Scientific and Technical Information of China (English)
Guanghui Ma; Fangling Gong; Guohua Hu; Dongxia Hao; Rong Liu; Renwei Wang
2005-01-01
Multi-scale structures involved in emulsion and microsphere complex systems are presented and discussed. The stability and spatio-temporal structures of emulsions, as well as nano-structures formed on the surface of microspheres after polymerization, are affected by the molecular emulsifier/stabilizer structures and the adsorbed emulsifier/stabilizer nano-structures on the oil/water interface. The broad size distribution and variation of surface features of droplets are responsible for variations of the adsorbed emulsifier/stabilizer structures and the stability of the emulsions.On the other hand, preparation of a uniformly sized emulsion and employment of a combined emulsifier/stabilizer system can preserve the stability of the emulsions and microspheres. The above phenomena should be modeled by a multiscale method, in order to maintain the stability of individual emulsion systems and realize the desired nano-structures of microspheres by choosing adequate emulsifier/stabilizer and experimental parameters.
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.
Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K
2015-04-01
Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.
Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels
Lang, F.; Yang, J.; Wu, L.; Li, D.
2016-06-01
Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.
A multiphysics and multiscale software environment for modeling astrophysical systems
Zwart, Simon Portegies; Harfst, Stefan; Groen, Derek; Fujii, Michiko
2008-01-01
We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a ``Noah's Ark'' milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multi-scale and multi-physics systems in which the time- and size-scales are well separated, like simulating the evolution of plan...
ProtoMD: A prototyping toolkit for multiscale molecular dynamics
Somogyi, Endre; Mansour, Andrew Abi; Ortoleva, Peter J.
2016-05-01
ProtoMD is a toolkit that facilitates the development of algorithms for multiscale molecular dynamics (MD) simulations. It is designed for multiscale methods which capture the dynamic transfer of information across multiple spatial scales, such as the atomic to the mesoscopic scale, via coevolving microscopic and coarse-grained (CG) variables. ProtoMD can be also be used to calibrate parameters needed in traditional CG-MD methods. The toolkit integrates 'GROMACS wrapper' to initiate MD simulations, and 'MDAnalysis' to analyze and manipulate trajectory files. It facilitates experimentation with a spectrum of coarse-grained variables, prototyping rare events (such as chemical reactions), or simulating nanocharacterization experiments such as terahertz spectroscopy, AFM, nanopore, and time-of-flight mass spectroscopy. ProtoMD is written in python and is freely available under the GNU General Public License from github.com/CTCNano/proto_md.
Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance
Energy Technology Data Exchange (ETDEWEB)
Estep, Donald [Colorado State Univ., Fort Collins, CO (United States); El-Azab, Anter [Florida State Univ., Tallahassee, FL (United States); Pernice, Michael [Idaho National Lab. (INL), Idaho Falls, ID (United States); Peterson, John W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Polyakov, Peter [Univ. of Wyoming, Laramie, WY (United States); Tavener, Simon [Colorado State Univ., Fort Collins, CO (United States); Xiu, Dongbin [Purdue Univ., West Lafayette, IN (United States); Univ. of Utah, Salt Lake City, UT (United States)
2017-03-23
In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.
A multi-scale code for flexible hybrid simulations
Leukkunen, L; Lopez-Acevedo, O
2012-01-01
Multi-scale computer simulations combine the computationally efficient classical algorithms with more expensive but also more accurate ab-initio quantum mechanical algorithms. This work describes one implementation of multi-scale computations using the Atomistic Simulation Environment (ASE). This implementation can mix classical codes like LAMMPS and the Density Functional Theory-based GPAW. Any combination of codes linked via the ASE interface however can be mixed. We also introduce a framework to easily add classical force fields calculators for ASE using LAMMPS, which also allows harnessing the full performance of classical-only molecular dynamics. Our work makes it possible to combine different simulation codes, quantum mechanical or classical, with great ease and minimal coding effort.
Multiscale content extraction and representation for video indexing
Ferman, Ahmet M.; Tekalp, A. Murat
1997-10-01
This paper presents a general multiscale framework for extraction and representation of video content. The approach exploits the inherent multiscale nature of many TV and film productions to delineate an input stream effectively and to construct consistent scenes reliably. The method first utilizes basic signal processing techniques, and unsupervised clustering to determine shot boundaries in the video sequence. Similarity comparison using shot representative histograms and clustering to determine shot boundaries in the video sequence. Similarity comparison using shot representative histograms and clustering is then carried out within each shot to automatically select representative key frames. Finally, a model that takes into account the filmic structure of the input stream is discussed and developed to efficiently merge individual shots into coherent, meaningful segments, i.e. scenes.
Energy-Consistent Multiscale Algorithms for Granular Flows
2014-08-07
8-98) v Prescribed by ANSI Std. Z39.18 30-07-2014 Final 01-MAY-2011 - 30-APR-2014 AFOSR YIP Energy-Consistent Multiscale Algorithms for Granular...document the achievements made as a result of this Young Investigator Program ( YIP ) project. We worked on the development of multi scale energy... YIP ) project. We worked on the development of multi scale energy-consistent algorithms to simulate and capture flow phenomena in granular
Statistical multiscale image segmentation via Alpha-stable modeling
Wan, Tao; Canagarajah, CN; Achim, AM
2007-01-01
This paper presents a new statistical image segmentation algorithm, in which the texture features are modeled by symmetric alpha-stable (SalphaS) distributions. These features are efficiently combined with the dominant color feature to perform automatic segmentation. First, the image is roughly segmented into textured and nontextured regions using the dual-tree complex wavelet transform (DT-CWT) with the sub-band coefficients modeled as SalphaS random variables. A mul-tiscale segmentation is ...
Coupling of Peridynamics and Finite Element Formulation for Multiscale Simulations
2012-10-16
comparison of stresses and strains by finite element analysis (FEA) and peridynamic solutions is performed for a ductile material. A multiscale...problems. One common benchmark problem characterized by the mixed mode fracture is the test of a double-edge-notched concrete specimen conducted by Nooru...Mohamed et al. [19]. The test of Nooru-Mohamed was adopted by De Borst [20] in the discussion of computational modeling of concrete fracture. For
One dimensional and multiscale models for blood flow circulation
Lamponi, Daniele
2004-01-01
The aim of this work is to provide mathematically sound and computationally effective tools for the numerical simulation of the interaction between fluid and structures as occurring, for instance, in the simulation of the human cardiovascular system. This problem is global, in the sense that local changes can modify the solution far away. From the point of view of computing and modelling this calls for the use of multiscale methods, where simplified models are used to treat the global problem...
Final Report for Integrated Multiscale Modeling of Molecular Computing Devices
Energy Technology Data Exchange (ETDEWEB)
Glotzer, Sharon C.
2013-08-28
In collaboration with researchers at Vanderbilt University, North Carolina State University, Princeton and Oakridge National Laboratory we developed multiscale modeling and simulation methods capable of modeling the synthesis, assembly, and operation of molecular electronics devices. Our role in this project included the development of coarse-grained molecular and mesoscale models and simulation methods capable of simulating the assembly of millions of organic conducting molecules and other molecular components into nanowires, crossbars, and other organized patterns.
Final Technical Report "Multiscale Simulation Algorithms for Biochemical Systems"
Energy Technology Data Exchange (ETDEWEB)
Petzold, Linda R.
2012-10-25
Biochemical systems are inherently multiscale and stochastic. In microscopic systems formed by living cells, the small numbers of reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA, Gillespie, 1976), a numerical simulation procedure that is essentially exact for chemical systems that are spatially homogeneous or well stirred. Despite recent improvements, as a procedure that simulates every reaction event, the SSA is necessarily inefficient for most realistic problems. There are two main reasons for this, both arising from the multiscale nature of the underlying problem: (1) stiffness, i.e. the presence of multiple timescales, the fastest of which are stable; and (2) the need to include in the simulation both species that are present in relatively small quantities and should be modeled by a discrete stochastic process, and species that are present in larger quantities and are more efficiently modeled by a deterministic differential equation (or at some scale in between). This project has focused on the development of fast and adaptive algorithms, and the fun- damental theory upon which they must be based, for the multiscale simulation of biochemical systems. Areas addressed by this project include: (1) Theoretical and practical foundations for ac- celerated discrete stochastic simulation (tau-leaping); (2) Dealing with stiffness (fast reactions) in an efficient and well-justified manner in discrete stochastic simulation; (3) Development of adaptive multiscale algorithms for spatially homogeneous discrete stochastic simulation; (4) Development of high-performance SSA algorithms.
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.
2012-04-30
In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.
Multiscale computer modeling in biomechanics and biomedical engineering
2013-01-01
This book reviews the state-of-the-art in multiscale computer modeling, in terms of both accomplishments and challenges. The information in the book is particularly useful for biomedical engineers, medical physicists and researchers in systems biology, mathematical biology, micro-biomechanics and biomaterials who are interested in how to bridge between traditional biomedical engineering work at the organ and tissue scales, and the newer arenas of cellular and molecular bioengineering.
Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers
Tang, Yu-Hang; Kudo, Shuhei; Bian, Xin; Li, Zhen; Karniadakis, George Em
2015-09-01
Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM).
Asymptotic-Preserving methods and multiscale models for plasma physics
Degond, Pierre
2016-01-01
The purpose of the present paper is to provide an overview of Asymptotic-Preserving methods for multiscale plasma simulations by addressing three singular perturbation problems. First, the quasi-neutral limit of fluid and kinetic models is investigated in the framework of non magnetized as well as magnetized plasmas. Second, the drift limit for fluid descriptions of thermal plasmas under large magnetic fields is addressed. Finally efficient numerical resolutions of anisotropic elliptic or diffusion equations arising in magnetized plasma simulation are reviewed.
Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers
Energy Technology Data Exchange (ETDEWEB)
Tang, Yu-Hang, E-mail: yuhang_tang@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Kudo, Shuhei, E-mail: shuhei-kudo@outlook.jp [Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, 657-8501 (Japan); Bian, Xin, E-mail: xin_bian@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Li, Zhen, E-mail: zhen_li@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI (United States); Collaboratory on Mathematics for Mesoscopic Modeling of Materials, Pacific Northwest National Laboratory, Richland, WA 99354 (United States)
2015-09-15
Graphical abstract: - Abstract: Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i.e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A data sampler concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers' own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM)
MULTISCALE HOMOGENIZATION OF NONLINEAR HYPERBOLIC EQUATIONS WITH SEVERAL TIME SCALES
Institute of Scientific and Technical Information of China (English)
Jean Louis Woukeng; David Dongo
2011-01-01
We study the multiscale homogenization of a nonlinear hyperbolic equation in a periodic setting. We obtain an accurate homogenization result. We also show that as the nonlinear term depends on the microscopic time variable, the global homogenized problem thus obtained is a system consisting of two hyperbolic equations. It is also shown that in spite of the presence of several time scales, the global homogenized problem is not a reiterated one.
Hybrid multiscale simulation of a mixing-controlled reaction
Energy Technology Data Exchange (ETDEWEB)
Scheibe, Timothy D.; Schuchardt, Karen L.; Agarwal, Khushbu; Chase, Jared M.; Yang, Xiaofan; Palmer, Bruce J.; Tartakovsky, Alexandre M.; Elsethagen, Todd O.; Redden, George D.
2015-09-01
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 and study pore-scale phenomena, such as mineral precipitation and dissolution reactions, microbially-mediated surface reactions, and other complex processes. However, these highly-resolved models are prohibitively expensive for modeling domains of sizes relevant to practical problems. To broaden the utility of pore-scale models for larger domains, we developed a hybrid multiscale model that initially simulates the full domain at the continuum scale and applies a pore-scale model only to areas of high reactivity. Since the location and number of pore-scale model regions in the model varies as the reactions proceed, an adaptive script defines the number and location of pore regions within each continuum iteration and initializes pore-scale simulations from macroscale information. Another script communicates information from the pore-scale simulation results back to the continuum scale. These components provide loose coupling between the pore- and continuum-scale codes into a single hybrid multiscale model implemented within the SWIFT workflow environment. In this paper, we consider an irreversible homogenous bimolecular reaction (two solutes reacting to form a third solute) in a 2D test problem. This paper is focused on the approach used for multiscale coupling between pore- and continuum-scale models, application to a realistic test problem, and implications of the results for predictive simulation of mixing-controlled reactions in porous media. Our results and analysis demonstrate that loose coupling provides a feasible, efficient and scalable approach for multiscale subsurface simulations.
Smart Gating Multi-Scale Pore/Channel-Based Membranes.
Hou, Xu
2016-09-01
Smart gating membranes are important and promising in membrane science and technology. Rapid progress in developing smart membranes is transforming technology in many different fields, from energy and environmental to the life sciences. How a specific smart behavior for controllable gating of porous membranes can be obtained, especially for nano- and micrometer-sized multi-scale pore/channel-based membrane systems is addressed.
Nonlinear Multiscale Transformations: From Synchronization to Error Control
2001-07-01
Donat Dept. Matematica Aplicada, University of Valencia, Spain. arandiga@uv. es donat uv. es Abstract Data-dependent interpolatory techniques can be used...Numer. Algorith. 23, 175-216, 2000. 5. F. Arhndiga, R. Donat, and A. Harten. Multiresolution based on weighted averages of the hat function II : Nonlinear...transforms for image coding via lifting scheme. submitted to IEEE Trans. on Image Nonlinear multiscale transformations 313 Method II ’ 1 I ŕ, 11蕀 r
Hybrid multiscale modeling and prediction of cancer cell behavior.
Zangooei, Mohammad Hossein; Habibi, Jafar
2017-01-01
Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.
Multiscale Monte Carlo equilibration: pure Yang-Mills theory
Endres, Michael G; Detmold, William; Orginos, Kostas; Pochinsky, Andrew V
2015-01-01
We present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.
Higher-Dimensional Signal Processing via Multiscale Geometric Analysis
2010-02-10
1.1 Review of motivation Over the past twenty years multiscale methods like the discrete wavelet transform (DWT) have revolutionized signal processing...sparsity and structure boost the performance of wavelet -domain statistical models and enable simple yet powerful algorithms for estimation/ denoising ...for many state-of-the-art wavelet domain processing algorithms for applications including compression [23,24], denoising [25,26], and segmentation [27
Multi-Scale Jacobi Method for Anderson Localization
Imbrie, John Z.
2014-01-01
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 [arXiv:1403.7837].
Generalization of mixed multiscale finite element methods with applications
Energy Technology Data Exchange (ETDEWEB)
Lee, C S [Texas A & M Univ., College Station, TX (United States)
2016-08-01
Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixed multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii
Multiscale modelling of fluid-immersed granular media
Clément, Christian Paul André René
2010-01-01
In this thesis we present numerical simulation studies of fluid-immersed granular systems using models of varying scales and complexities. These techniques are used to examine the effects of an interstitial fluid on the dynamics of dense granular beds within a number of vibrated systems. After an introduction to the field of granular materials, we present the techniques used to model both the granular dynamics and the fluid flow. We introduce various multiscale techniques to couple the mo...
Mixed Generalized Multiscale Finite Element Methods and Applications
Chung, Eric T.
2015-03-03
In this paper, we present a mixed generalized multiscale finite element method (GMsFEM) for solving flow in heterogeneous media. Our approach constructs multiscale basis functions following a GMsFEM framework and couples these basis functions using a mixed finite element method, which allows us to obtain a mass conservative velocity field. To construct multiscale basis functions for each coarse edge, we design a snapshot space that consists of fine-scale velocity fields supported in a union of two coarse regions that share the common interface. The snapshot vectors have zero Neumann boundary conditions on the outer boundaries, and we prescribe their values on the common interface. We describe several spectral decompositions in the snapshot space motivated by the analysis. In the paper, we also study oversampling approaches that enhance the accuracy of mixed GMsFEM. A main idea of oversampling techniques is to introduce a small dimensional snapshot space. We present numerical results for two-phase flow and transport, without updating basis functions in time. Our numerical results show that one can achieve good accuracy with a few basis functions per coarse edge if one selects appropriate offline spaces. © 2015 Society for Industrial and Applied Mathematics.
Detection of multiscale pockets on protein surfaces using mathematical morphology.
Kawabata, Takeshi
2010-04-01
Detection of pockets on protein surfaces is an important step toward finding the binding sites of small molecules. In a previous study, we defined a pocket as a space into which a small spherical probe can enter, but a large probe cannot. The radius of the large probes corresponds to the shallowness of pockets. We showed that each type of binding molecule has a characteristic shallowness distribution. In this study, we introduced fundamental changes to our previous algorithm by using a 3D grid representation of proteins and probes, and the theory of mathematical morphology. We invented an efficient algorithm for calculating deep and shallow pockets (multiscale pockets) simultaneously, using several different sizes of spherical probes (multiscale probes). We implemented our algorithm as a new program, ghecom (grid-based HECOMi finder). The statistics of calculated pockets for the structural dataset showed that our program had a higher performance of detecting binding pockets, than four other popular pocket-finding programs proposed previously. The ghecom also calculates the shallowness of binding ligands, R(inaccess) (minimum radius of inaccessible spherical probes) that can be obtained from the multiscale molecular volume. We showed that each part of the binding molecule had a bias toward a specific range of shallowness. These findings will be useful for predicting the types of molecules that will be most likely to bind putative binding pockets, as well as the configurations of binding molecules. The program ghecom is available through the Web server (http://biunit.naist.jp/ghecom).
Information theoretic multiscale truncated SVD for multilead electrocardiogram.
Sharma, L N
2016-06-01
In this paper an information theory based multiscale singular value decomposition (SVD) is proposed for multilead electrocardiogram (ECG) signal processing. The shrinkage of singular values for different multivariate multiscale matrices at wavelet scales is based on information content. It aims to capture and preserve the information of clinically important local waves like P-waves, Q-waves, T-waves and QRS-complexes. The information is derived through clinically relevant multivariate multiscale entropy in SVD domain modifying Shannon's entropy. This optimizes the approximate ranks for matrices to capture the clinical components of ECG signals appearing at different scales. A newly introduced multivariate clinical distortion (MCD) metric is computed and compared with existing subjective and objective signal distortion measures. The proposed method is tested with records from CSE multilead measurement library and PTB diagnostic ECG database for various pathological cases. It gives average percentage root mean square difference (PRD), average normalized root mean square error (NRMSE), average wavelet energy based diagnostic distortion measure (WEDD) values 5.8879%, 0.0059 and 1.0760% respectively for myocarditis pathology. The corresponding MCD value is 1.9429%. The highest average PRD and average WEDD values are 11.4053% and 5.5194% for cardiomyopathy with the corresponding MCD value 1.4003%. Based on WEDD values and mean opinion scores (MOS), the quality group of all processed signals fall under excellent category. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Multiscale structure of time series revealed by the monotony spectrum.
Vamoş, Călin
2017-03-01
Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.
Learning multiscale and deep representations for classifying remotely sensed imagery
Zhao, Wenzhi; Du, Shihong
2016-03-01
It is widely agreed that spatial features can be combined with spectral properties for improving interpretation performances on very-high-resolution (VHR) images in urban areas. However, many existing methods for extracting spatial features can only generate low-level features and consider limited scales, leading to unpleasant classification results. In this study, multiscale convolutional neural network (MCNN) algorithm was presented to learn spatial-related deep features for hyperspectral remote imagery classification. Unlike traditional methods for extracting spatial features, the MCNN first transforms the original data sets into a pyramid structure containing spatial information at multiple scales, and then automatically extracts high-level spatial features using multiscale training data sets. Specifically, the MCNN has two merits: (1) high-level spatial features can be effectively learned by using the hierarchical learning structure and (2) multiscale learning scheme can capture contextual information at different scales. To evaluate the effectiveness of the proposed approach, the MCNN was applied to classify the well-known hyperspectral data sets and compared with traditional methods. The experimental results shown a significant increase in classification accuracies especially for urban areas.
Introduction and application of the multiscale coefficient of variation analysis.
Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh
2016-09-20
Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
Efendiev, Yalchin R.
2014-03-11
In this paper, multiscale finite element methods (MsFEMs) and domain decomposition techniques are developed for a class of nonlinear elliptic problems with high-contrast coefficients. In the process, existing work on linear problems [Y. Efendiev, J. Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y. Efendiev, SIAM Multiscale Model. Simul. 8 (2010) 1461–1483.] is extended to treat a class of nonlinear elliptic operators. The proposed method requires the solutions of (small dimension and local) nonlinear eigenvalue problems in order to systematically enrich the coarse solution space. Convergence of the method is shown to relate to the dimension of the coarse space (due to the enrichment procedure) as well as the coarse mesh size. In addition, it is shown that the coarse mesh spaces can be effectively used in two-level domain decomposition preconditioners. A number of numerical results are presented to complement the analysis.
Generalized multiscale finite element method for elasticity equations
Chung, Eric T.
2014-10-05
In this paper, we discuss the application of generalized multiscale finite element method (GMsFEM) to elasticity equation in heterogeneous media. We consider steady state elasticity equations though some of our applications are motivated by elastic wave propagation in subsurface where the subsurface properties can be highly heterogeneous and have high contrast. We present the construction of main ingredients for GMsFEM such as the snapshot space and offline spaces. The latter is constructed using local spectral decomposition in the snapshot space. The spectral decomposition is based on the analysis which is provided in the paper. We consider both continuous Galerkin and discontinuous Galerkin coupling of basis functions. Both approaches have their cons and pros. Continuous Galerkin methods allow avoiding penalty parameters though they involve partition of unity functions which can alter the properties of multiscale basis functions. On the other hand, discontinuous Galerkin techniques allow gluing multiscale basis functions without any modifications. Because basis functions are constructed independently from each other, this approach provides an advantage. We discuss the use of oversampling techniques that use snapshots in larger regions to construct the offline space. We provide numerical results to show that one can accurately approximate the solution using reduced number of degrees of freedom.
Multiscale geometric modeling of macromolecules II: Lagrangian representation.
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-09-15
Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics, and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR, and cryo-electron microscopy, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation, and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger's functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, whereas our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions.
Multiscale modeling and mechanics of filamentous actin cytoskeleton.
Yamaoka, Hidetaka; Matsushita, Shinji; Shimada, Yoshitaka; Adachi, Taiji
2012-03-01
The adaptive structure and functional changes of the actin cytoskeleton are induced by its mechanical behavior at various temporal and spatial scales. In particular, the mechanical behaviors at different scales play important roles in the mechanical functions of various cells, and these multiscale phenomena require clarification. To establish a milestone toward achieving multiscale modeling and simulation, this paper reviews mathematical analyses and simulation methods applied to the mechanics of the filamentous actin cytoskeleton. The actin cytoskeleton demonstrates characteristic behaviors at every temporal and spatial scale, and mathematical models and simulation methods can be applied to each level of actin cytoskeletal structure ranging from the molecular to the network level. This paper considers studies on mathematical models and simulation methods based on the molecular dynamics, coarse-graining, and continuum dynamics approaches. Every temporal and spatial scale of actin cytoskeletal structure is considered, and it is expected that discrete and continuum dynamics ranging from functional expression at the molecular level to macroscopic functional expression at the whole cell level will be developed and applied to multiscale modeling and simulation.
Multiscale Simulation of Electrochemical_/ Phenomena: Fuel Cells and Batteries
Voth, Gregory
2012-02-01
Results will be presented from multiscale simulations of two important systems from renewable energy technology, fuel cell proton membranes and electrochemical cells. In the first case, the solvation and transport of hydrated protons in proton exchange membranes (PEMs) such as Nafion^TM will be described using a novel multi-state reactive molecular dynamics (MD) approach. The multi-state MD methodology allows for the treatment of explicit (Grotthuss) proton shuttling and charge defect delocalization which, in turn, can strongly influence the properties of the hydrated protons in various aqueous and complex environments. The role of PEM hydration level and morphology on these properties will be further described. A new multiscale computational methodology for describing the mesoscopic features of the proton transport will also be described, which can be coupled to the results from the molecular-scale simulations. On the second topic, a computationally efficient method will be presented for the treatment of electrostatic interactions between polarizable metallic electrodes held at a constant potential and separated by an electrolyte. The method combines a fluctuating uniform electrode charge with explicit image charges to account for the polarization of the electrode by the electrolyte, and a constant uniform charge added to the fluctuating uniform electrode charge to account for the constant potential condition. The method is used to calculate electron transport rates using electron transfer theory; these rates are incorporated in a multiscale approach to model oxidation/reduction reactions in an electrochemical cell efficiently.
Multi-scale interactions in inter personal coordination
Institute of Scientific and Technical Information of China (English)
Tehran J. Davis; Thomas R. Brooks; James A. Dixon
2016-01-01
Background: Interpersonal coordination is an essential aspect of daily life, and crucial to performance in cooperative and competitive team sports. While empirical research has investigated interpersonal coordination using a wide variety of analytical tools and frameworks, to date very few studies have employed multifractal techniques to study the nature of interpersonal coordination across multiple spatiotemporal scales. In the present study we address this gap. Methods: We investigated the dynamics of a simple dyadic interpersonal coordination task where each participant manually controlled a virtual object in relation to that of his or her partner. We tested whether the resulting hand-movement time series exhibits multi-scale properties and whether those properties are associated with successful performance. Results: Using the formalism of multifractals, we show that the performance on the coordination task is strongly multi-scale, and that the multi-scale properties appear to arise from interaction-dominant dynamics. Further, we find that the measure of across-scale interactions, multifractal spectrum width, predicts successful performance at the level of the dyad. Conclusion: The results are discussed with respect to the implications of multifractals and interaction-dominance for understanding control in an interpersonal context.
A Multiscale Approach to Optimal In Situ Bioremediation Design
Minsker, B. S.; Liu, Y.
2001-12-01
The use of optimization methods for in situ bioremediation design is quite challenging because the dynamics of bioremediation require that fine spatial and temporal scales be used in simulation, which substantially increases computational effort for optimization. In this paper, we present a multiscale approach that can be used to solve substantially larger-scale problems than previously possible. The multiscale method starts from a coarse mesh and proceeds to a finer mesh when it converges. While it is on a finer mesh, it switches back to a coarser mesh to calculate derivatives. The derivatives are then interpolated back to the finer mesh to approximate the derivatives on the finer mesh. To demonstrate the method, a four-level case study with 6,500 state variables is solved in less than 9 days, compared with nearly one year that would have been required using the original single-scale model. These findings illustrate that the multiscale method will allow solution of substantially larger-scale problems than previously possible, particularly since the method also enables easy parallelization of the model in the future.
Moist multi-scale models for the hurricane embryo
Energy Technology Data Exchange (ETDEWEB)
Majda, Andrew J. [New York University; Xing, Yulong [ORNL; Mohammadian, Majid [University of Ottawa, Canada
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.
Integrated Multiscale Latent Variable Regression and Application to Distillation Columns
Directory of Open Access Journals (Sweden)
Muddu Madakyaru
2013-01-01
Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.
Standard Model in multiscale theories and observational constraints
Calcagni, Gianluca; Nardelli, Giuseppe; Rodríguez-Fernández, David
2016-08-01
We construct and analyze the Standard Model of electroweak and strong interactions in multiscale spacetimes with (i) weighted derivatives and (ii) q -derivatives. Both theories can be formulated in two different frames, called fractional and integer picture. By definition, the fractional picture is where physical predictions should be made. (i) In the theory with weighted derivatives, it is shown that gauge invariance and the requirement of having constant masses in all reference frames make the Standard Model in the integer picture indistinguishable from the ordinary one. Experiments involving only weak and strong forces are insensitive to a change of spacetime dimensionality also in the fractional picture, and only the electromagnetic and gravitational sectors can break the degeneracy. For the simplest multiscale measures with only one characteristic time, length and energy scale t*, ℓ* and E*, we compute the Lamb shift in the hydrogen atom and constrain the multiscale correction to the ordinary result, getting the absolute upper bound t*28 TeV . Stronger bounds are obtained from the measurement of the fine-structure constant. (ii) In the theory with q -derivatives, considering the muon decay rate and the Lamb shift in light atoms, we obtain the independent absolute upper bounds t*35 MeV . For α0=1 /2 , the Lamb shift alone yields t*450 GeV .
Multi-scale interactions in Dictyostelium discoideum aggregation
Dixon, James A.; Kelty-Stephen, Damian G.
2012-12-01
Cellular aggregation is essential for a wide range of phenomena in developmental biology, and a crucial event in the life-cycle of Dictyostelium discoideum. The current manuscript presents an analysis of multi-scale interactions involved in D. discoideum aggregation and non-aggregation events. The multi-scale fractal dimensions of a sequence of microscope images were used to estimate changing structure at different spatial scales. Three regions showing aggregation and three showing non-aggregation were considered. The results showed that both aggregation and non-aggregation regions were strongly multi-fractal. Analyses of the over-time relationships among nine scales of the generalized dimension, D(q), were conducted using vector autoregression and vector error-correction models. Both types of regions showed evidence that across-scale interactions serve to maintain the equilibrium of the system. Aggregation and non-aggregation regions also showed different patterns of effects of individual scales on other scales. Specifically, aggregation regions showed greater effects of both the smallest and largest scales on the smaller scale structures. The results suggest that multi-scale interactions are responsible for maintaining and altering the cellular structures during aggregation.
Multiscale diffusion in the mitotic Drosophila melanogaster syncytial blastoderm.
Daniels, Brian R; Rikhy, Richa; Renz, Malte; Dobrowsky, Terrence M; Lippincott-Schwartz, Jennifer
2012-05-29
Despite the fundamental importance of diffusion for embryonic morphogen gradient formation in the early Drosophila melanogaster embryo, there remains controversy regarding both the extent and the rate of diffusion of well-characterized morphogens. Furthermore, the recent observation of diffusional "compartmentalization" has suggested that diffusion may in fact be nonideal and mediated by an as-yet-unidentified mechanism. Here, we characterize the effects of the geometry of the early syncytial Drosophila embryo on the effective diffusivity of cytoplasmic proteins. Our results demonstrate that the presence of transient mitotic membrane furrows results in a multiscale diffusion effect that has a significant impact on effective diffusion rates across the embryo. Using a combination of live-cell experiments and computational modeling, we characterize these effects and relate effective bulk diffusion rates to instantaneous diffusion coefficients throughout the syncytial blastoderm nuclear cycle phase of the early embryo. This multiscale effect may be related to the effect of interphase nuclei on effective diffusion, and thus we propose that an as-yet-unidentified role of syncytial membrane furrows is to temporally regulate bulk embryonic diffusion rates to balance the multiscale effect of interphase nuclei, which ultimately stabilizes the shapes of various morphogen gradients.
Multi-scale symbolic transfer entropy analysis of EEG
Yao, Wenpo; Wang, Jun
2017-10-01
From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.
Reduced Noise Effect in Nonlinear Model Estimation Using Multiscale Representation
Directory of Open Access Journals (Sweden)
Mohamed N. Nounou
2010-01-01
Full Text Available Nonlinear process models are widely used in various applications. In the absence of fundamental models, it is usually relied on empirical models, which are estimated from measurements of the process variables. Unfortunately, measured data are usually corrupted with measurement noise that degrades the accuracy of the estimated models. Multiscale wavelet-based representation of data has been shown to be a powerful data analysis and feature extraction tool. In this paper, these characteristics of multiscale representation are utilized to improve the estimation accuracy of the linear-in-the-parameters nonlinear model by developing a multiscale nonlinear (MSNL modeling algorithm. The main idea in this MSNL modeling algorithm is to decompose the data at multiple scales, construct multiple nonlinear models at multiple scales, and then select among all scales the model which best describes the process. The main advantage of the developed algorithm is that it integrates modeling and feature extraction to improve the robustness of the estimated model to the presence of measurement noise in the data. This advantage of MSNL modeling is demonstrated using a nonlinear reactor model.
A multiscale mortar multipoint flux mixed finite element method
Wheeler, Mary Fanett
2012-02-03
In this paper, we develop a multiscale mortar multipoint flux mixed finite element method for second order elliptic problems. The equations in the coarse elements (or subdomains) are discretized on a fine grid scale by a multipoint flux mixed finite element method that reduces to cell-centered finite differences on irregular grids. The subdomain grids do not have to match across the interfaces. Continuity of flux between coarse elements is imposed via a mortar finite element space on a coarse grid scale. With an appropriate choice of polynomial degree of the mortar space, we derive optimal order convergence on the fine scale for both the multiscale pressure and velocity, as well as the coarse scale mortar pressure. Some superconvergence results are also derived. The algebraic system is reduced via a non-overlapping domain decomposition to a coarse scale mortar interface problem that is solved using a multiscale flux basis. Numerical experiments are presented to confirm the theory and illustrate the efficiency and flexibility of the method. © EDP Sciences, SMAI, 2012.
Directory of Open Access Journals (Sweden)
Haitao Cao
2014-01-01
Full Text Available We propose a fully discrete method for the multiscale Richards’ equation of van Genuchten-Mualem model which describes the flow transport in unsaturated heterogenous porous media. Under the framework of heterogeneous multiscale method (HMM, a fully discrete scheme combined with a regularized procedure is proposed. Including the numerical integration, the discretization is given by C0 piecewise finite element in space and an implicit scheme in time. Error estimates between the numerical solution and the solution of homogenized problem are derived under the assumption that the permeability is periodic. Numerical experiments with periodic and random permeability are carried out for the van Genuchten-Mualem model of Richards’ equation to show the efficiency and accuracy of the proposed method.
Sun, S.
2011-01-01
The temporal discretization scheme is one important ingredient of efficient simulator for two-phase flow in the fractured porous media. The application of single-scale temporal scheme is restricted by the rapid changes of the pressure and saturation in the fractured system with capillarity. In this paper, we propose a multi-scale time splitting strategy to simulate multi-scale multi-physics processes of two-phase flow in fractured porous media. We use the multi-scale time schemes for both the pressure and saturation equations; that is, a large time-step size is employed for the matrix domain, along with a small time-step size being applied in the fractures. The total time interval is partitioned into four temporal levels: the first level is used for the pressure in the entire domain, the second level matching rapid changes of the pressure in the fractures, the third level treating the response gap between the pressure and the saturation, and the fourth level applied for the saturation in the fractures. This method can reduce the computational cost arisen from the implicit solution of the pressure equation. Numerical examples are provided to demonstrate the efficiency of the proposed method.
Directory of Open Access Journals (Sweden)
Jisheng Kou
2011-01-01
Full Text Available The temporal discretization scheme is one important ingredient of efficient simulator for two-phase flow in the fractured porous media. The application of single-scale temporal scheme is restricted by the rapid changes of the pressure and saturation in the fractured system with capillarity. In this paper, we propose a multi-scale time splitting strategy to simulate multi-scale multi-physics processes of two-phase flow in fractured porous media. We use the multi-scale time schemes for both the pressure and saturation equations; that is, a large time-step size is employed for the matrix domain, along with a small time-step size being applied in the fractures. The total time interval is partitioned into four temporal levels: the first level is used for the pressure in the entire domain, the second level matching rapid changes of the pressure in the fractures, the third level treating the response gap between the pressure and the saturation, and the fourth level applied for the saturation in the fractures. This method can reduce the computational cost arisen from the implicit solution of the pressure equation. Numerical examples are provided to demonstrate the efficiency of the proposed method.
DEFF Research Database (Denmark)
Dai, Gaoming; Mishnaevsky, Leon, Jr.
2014-01-01
3D numerical simulations of fatigue damage of multiscale fiber reinforced polymer composites with secondary nanoclay reinforcement are carried out. Macro–micro FE models of the multiscale composites are generated automatically using Python based software. The effect of the nanoclay reinforcement...
Application of computer-aided multi-scale modelling framework - Aerosol case study
DEFF Research Database (Denmark)
Heitzig, Martina; Gregson, Christopher; Sin, Gürkan;
2011-01-01
A computer-aided modelling tool for efficient multi-scale modelling has been developed and is applied to solve a multi-scale modelling problem related to design and evaluation of fragrance aerosol products. The developed modelling scenario spans three length scales and describes how droplets...
Multiscale finite element methods for high-contrast problems using local spectral basis functions
Efendiev, Yalchin
2011-02-01
In this paper we study multiscale finite element methods (MsFEMs) using spectral multiscale basis functions that are designed for high-contrast problems. Multiscale basis functions are constructed using eigenvectors of a carefully selected local spectral problem. This local spectral problem strongly depends on the choice of initial partition of unity functions. The resulting space enriches the initial multiscale space using eigenvectors of local spectral problem. The eigenvectors corresponding to small, asymptotically vanishing, eigenvalues detect important features of the solutions that are not captured by initial multiscale basis functions. Multiscale basis functions are constructed such that they span these eigenfunctions that correspond to small, asymptotically vanishing, eigenvalues. We present a convergence study that shows that the convergence rate (in energy norm) is proportional to (H/Λ*)1/2, where Λ* is proportional to the minimum of the eigenvalues that the corresponding eigenvectors are not included in the coarse space. Thus, we would like to reach to a larger eigenvalue with a smaller coarse space. This is accomplished with a careful choice of initial multiscale basis functions and the setup of the eigenvalue problems. Numerical results are presented to back-up our theoretical results and to show higher accuracy of MsFEMs with spectral multiscale basis functions. We also present a hierarchical construction of the eigenvectors that provides CPU savings. © 2010.
Xu, F.; Niu, J.; Chi, Z.; Xie, W.
2013-05-01
Analyzing and evaluating the reliability of multi-scale representation of spatial data are already becoming an important issue of the current digital cartography and GIS. Settlement place is the main content of maps. For this reason, studying on the uncertainty of multi-scale representation of settlement place is one of important contents of the uncertainty of multi-scale representation of spatial data. In this paper, uncertainty of multi-scale representation of street-block settlement was get comprehensive analysis and system research. This paper holds that map generalization is the essential cause leading to uncertainty of multi-scale representation of streetblock settlement. First, it is explored of essence and types of uncertainty on multi-scale representation of street-block settlement, and it divides these uncertainties into four large classes and seven subclasses. Second, among all kinds of uncertainties of multi-scale representation of street-block settlement, this paper mainly studies the uncertainty of settlement of street-block symbolic representation, and establishes the evaluation content and evaluation indexes and computing method of uncertainty of street-block and street network generalization and building generalization. The result can use for evaluating the good and bad of scale transfer methods and the uncertainty of products of multi-scale representation of street-block settlement.
2010-01-01
can also refer to hierarchical parameterization transcending any scale, such as mesoscopic to continuum levels. Such a multiscale modeling paradigm ...particularly suited for systems defined by long-chain polymers with relatively short persistence lengths, or systems that are entropically driven...mechanics. Thus, we introduce a universal framework through a finer-trains-coarser multiscale paradigm , which effectively defines coarse- grain
RESEARCH COLLABORATION GROUP ON MULTI-SCALE METHODOLOGY AND COMPLEX SYSTEMS
Institute of Scientific and Technical Information of China (English)
Jinghai Li; Wei Ge; Jiayuan Zhang
2005-01-01
@@ Background In response to the evolution of science and technology from compartmentalization to reunification, the study of complex systems and multi-scale methodology has received increasing attention from various scientific disciplines and engineering fields, so much so that complexity has sometimes been called the science of the 21st century with multi-scale methodology as an accompanying challenge.
Multiscale analysis of damage using dual and primal domain decomposition techniques
Lloberas-Valls, O.; Everdij, F.P.X.; Rixen, D.J.; Simone, A.; Sluys, L.J.
2014-01-01
In this contribution, dual and primal domain decomposition techniques are studied for the multiscale analysis of failure in quasi-brittle materials. The multiscale strategy essentially consists in decomposing the structure into a number of nonoverlapping domains and considering a refined spatial res
A Multiscale Approach to Automatic Medical Image Segmentation Using Self—Organizing Map
Institute of Scientific and Technical Information of China (English)
马峰; 夏绍玮
1998-01-01
In this paper,a new medical image classification scheme is proposed using selforganizing map(SOM)combined with multiscale technique.It addresses the problem of the handling of edge pixels in the traditional multiscale SOM classifiers.First,to solve the difficulty in manual selection of edge pixels,a multiscale edge detection algorithm based on wavelet transform is proposed.Edge pixels detected are then selected into the training set as a new class and a multiscale SOM classifier is trained using this training set.In this new scheme,the SOM classifier can perform both the classification on the entire image and the edge detection simultaneously.On the other hand,the misclassification of the traditional multiscale SOM classifier in regions near edges is graeatly reduced and the correct classification is improved at the same time.
Cho, Hyesung; Moon Kim, Sang; Sik Kang, Yun; Kim, Junsoo; Jang, Segeun; Kim, Minhyoung; Park, Hyunchul; Won Bang, Jung; Seo, Soonmin; Suh, Kahp-Yang; Sung, Yung-Eun; Choi, Mansoo
2015-01-01
The production of multiscale architectures is of significant interest in materials science, and the integration of those structures could provide a breakthrough for various applications. Here we report a simple yet versatile strategy that allows for the LEGO-like integrations of microscale membranes by quantitatively controlling the oxygen inhibition effects of ultraviolet-curable materials, leading to multilevel multiscale architectures. The spatial control of oxygen concentration induces different curing contrasts in a resin allowing the selective imprinting and bonding at different sides of a membrane, which enables LEGO-like integration together with the multiscale pattern formation. Utilizing the method, the multilevel multiscale Nafion membranes are prepared and applied to polymer electrolyte membrane fuel cell. Our multiscale membrane fuel cell demonstrates significant enhancement of performance while ensuring mechanical robustness. The performance enhancement is caused by the combined effect of the decrease of membrane resistance and the increase of the electrochemical active surface area. PMID:26412619
Multiscale Asymptotic Analysis and Parallel Algorithm of Parabolic Equation in Composite Materials
Directory of Open Access Journals (Sweden)
Xin Wang
2014-01-01
Full Text Available An efficient parallel multiscale numerical algorithm is proposed for a parabolic equation with rapidly oscillating coefficients representing heat conduction in composite material with periodic configuration. Instead of following the classical multiscale asymptotic expansion method, the Fourier transform in time is first applied to obtain a set of complex-valued elliptic problems in frequency domain. The multiscale asymptotic analysis is presented and multiscale asymptotic solutions are obtained in frequency domain which can be solved in parallel essentially without data communications. The inverse Fourier transform will then recover the approximate solution in time domain. Convergence result is established. Finally, a novel parallel multiscale FEM algorithm is proposed and some numerical examples are reported.
Jiang, Lijian
2010-08-01
In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.
Multiscale Computer Simulation of Failure in Aerogels
Good, Brian S.
2008-01-01
Aerogels have been of interest to the aerospace community primarily for their thermal properties, notably their low thermal conductivities. While such gels are typically fragile, recent advances in the application of conformal polymer layers to these gels has made them potentially useful as lightweight structural materials as well. We have previously performed computer simulations of aerogel thermal conductivity and tensile and compressive failure, with results that are in qualitative, and sometimes quantitative, agreement with experiment. However, recent experiments in our laboratory suggest that gels having similar densities may exhibit substantially different properties. In this work, we extend our original diffusion limited cluster aggregation (DLCA) model for gel structure to incorporate additional variation in DLCA simulation parameters, with the aim of producing DLCA clusters of similar densities that nevertheless have different fractal dimension and secondary particle coordination. We perform particle statics simulations of gel strain on these clusters, and consider the effects of differing DLCA simulation conditions, and the resultant differences in fractal dimension and coordination, on gel strain properties.
Multiscale geometric modeling of macromolecules I: Cartesian representation.
Xia, Kelin; Feng, Xin; Chen, Zhan; Tong, Yiying; Wei, Guo Wei
2014-01-01
This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the
Multiscale Regional Formula Fertilization Considering Environment Information Incompleteness
Institute of Scientific and Technical Information of China (English)
Qianqian ZHANG; Yan LIANG
2015-01-01
Conventional formula fertilization tends to calculate regional rate of fertilizer application by means of analyzing spatial distribution of regional cultivated land productivity combined with experiment data. However,as environment information of cultivated land is incomplete due to limitation of traditional cultivated land management technology and data acquisition,uncertainty of rate of fertilizer makes it hard to define the interval of formula fertilization and support the regional fertilization task. With the technique of spatial analysis and multiscale uncertainty theory,conventional fertilization can be optimized. Four steps are involved to calculate regional formula fertilization interval based on conventional formula fertilization:( i) To simulate cultivated land productivity according to EGLSN Model,and make it crop target field;( ii) To determine rate of fertilizer according to target field to define cultivated land productivity fertilizer interval and mid-value;( iii) To define region fertilizer interval length and value of region varying with scales as environment information becomes complete gradually;( iv) To apply block fertilizer combined with conventional formula by soil testing. Multiscale optimizing formula fertilization system has been established by using the Arc Engine as a platform to integrate the methods,which is applied in Xinjiang County,Shanxi Province,in order to optimize the existing fertilization formula in study area. It showed that the optimized formula fertilization had more spatial details of productivity than the original one.And the new method is available to support formula fertilization in any region or the block with uncertain environment information. It is therefore concluded that the proposed method has the potential for popularity,which provides a multiscale,multiple-factor and standardized formula fertilization method.
Multi-Scale SSA or Data-Adaptive Wavelets
Yiou, P.; Sornette, D.; Sornette, D.; Sornette, D.; Ghil, M.; Ghil, M.
2001-05-01
Using multi-scale ideas from wavelet analysis, the singular-spectrum analysis (SSA) is extended to the study of nonstationary time series, including the case where their variance diverges. The wavelet transform is similar to a local Fourier transform within a finite moving window whose width W, proportional to the major period of interest, is varied to explore a broad range of such periods. SSA, on the other hand, relies on the construction of the lag-correlation matrix C on M lagged copies of the time series over a fixed window width W proportional to M to detect the regular part of the variability in that window in terms of the minimal number of oscillatory components. The proposed multi-scale SSA is a local SSA analysis within a moving window of width Mwavelets; successive eigenvectors of C(M) correspond approximately to successive derivatives of the first mother wavelet in standard wavelet analysis. Multi-scale SSA thus solves objectively the delicate problem of optimizing the analyzing wavelet in the time-frequency domain, by a suitable localization of the signal's correlation matrix. We present several examples of application to synthetic signals with fractal or power-law behavior which mimic selected features of certain climatic or geophysical time series. The method is applied to the monthly values of the Southern Oscillation index (SOI) which captures major features of the El Niño/Southern Oscillation in the Tropical Pacific. Our methodology highlights an abrupt periodicity shift in the SOI near 1960. This abrupt shift between 5 and 3 years supports the Devil's staircase scenario for the El Niño/Southern Oscillation phenomenon.
Multi-Scale Physical Process in the Magnetosphere
Institute of Scientific and Technical Information of China (English)
CAO Jinbin; LIU Zhenxing
2008-01-01
The brief report presents a part of the research results of the magnetospheric physics researches in China during the period of 2006--2008.During the past two years,China-ESA cooperation DSP(Double Star Program)satellites were basically operating normally in its extended lifetime.The DSP and Cluster missions provide Chinese space physicists high quality data to study multi-scale physical process in the magnetosphere.The work made based on the data of DSP is presented in the paper of"Progress of Double Star Program"of this issue.
Multi-scale Representation of Building Feature in Urban GIS
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
This paper aims at multi-scale representation of urban GIS,presenting a model to dynamically generalize the building on the basis of Delaunay triangulation model.Considering the constraints of position accuracy,statistical area balance and orthogonal characteristics in building cluster generalization,this paper gives a progressive algorithm of building cluster aggregation,including conflict detection (where),object (who) displacement,and geometrical combination operation (how).The algorithm has been realized in an interactive generalization system and some experiment illustrations are provided.
Analysis of the Spatial Distribution of Galaxies by Multiscale Methods
Directory of Open Access Journals (Sweden)
E. Saar
2005-09-01
Full Text Available Galaxies are arranged in interconnected walls and filaments forming a cosmic web encompassing huge, nearly empty, regions between the structures. Many statistical methods have been proposed in the past in order to describe the galaxy distribution and discriminate the different cosmological models. We present in this paper multiscale geometric transforms sensitive to clusters, sheets, and walls: the 3D isotropic undecimated wavelet transform, the 3D ridgelet transform, and the 3D beamlet transform. We show that statistical properties of transform coefficients measure in a coherent and statistically reliable way, the degree of clustering, filamentarity, sheetedness, and voidedness of a data set.
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.
2012-11-01
We present a three-dimensional, multiscale model of vascular tumour growth, which couples nutrient/growth factor transport, blood flow, angiogenesis, vascular remodelling, movement of and interactions between normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. We present computational simulations which show how a vascular network may evolve and interact with tumour and healthy cells. We also demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour.
Growth of nitrogen-doped graphene on copper: Multiscale simulations
Gaillard, P.; Schoenhalz, A. L.; Moskovkin, P.; Lucas, S.; Henrard, L.
2016-02-01
We used multiscale simulations to model the growth of nitrogen-doped graphene on a copper substrate by chemical vapour deposition (CVD). Our simulations are based on ab-initio calculations of energy barriers for surface diffusion, which are complemented by larger scale Kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape of grown doped graphene flakes depends on the temperature and deposition flux they are submitted during the process, but we found no significant effect of nitrogen doping on this shape. However, we show that nitrogen atoms have a preference for pyridine-like sites compared to graphite-like sites, as observed experimentally.
The Total Variation Regularized L1 Model for Multiscale Decomposition
2006-01-01
N00014-03-1- 0514, and DOE Grant GE-FG01-92ER-25126. †Department of Industrial Engineering and Operations Research, Columbia University, New York, NY...5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Columbia University,Department of Industrial Engineering and Operations...2r . THE TV-L1 MODEL FOR MULTISCALE DECOMPOSITION 5 In general the minimizer of the TV-L1 is nonunique . In the above disk example, if λ = 2/r
Multi-Scale Dissemination of Time Series Data
DEFF Research Database (Denmark)
Guo, Qingsong; Zhou, Yongluan; Su, Li
2013-01-01
In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time-series...
Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries
DEFF Research Database (Denmark)
Sturm, Bob L.; Christensen, Mads Græsbøll
2010-01-01
We generalize cyclic matching pursuit (CMP), propose an orthogonal variant, and examine their performance using multiscale time-frequency dictionaries in the sparse approximation of signals. Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation...... error than existing greedy iterative descent methods such as matching pursuit (MP), and are competitive with models found using orthogonal MP (OMP), and orthogonal least squares (OLS). This implies that CMP is a strong alternative to the more computationally complex approaches of OMP and OLS...... for modeling high-dimensional signals....
Multiscale simulation of water flow past a C540 fullerene
Walther, Jens H.; Praprotnik, Matej; Kotsalis, Evangelos M.; Koumoutsakos, Petros
2012-04-01
We present a novel, three-dimensional, multiscale algorithm for simulations of water flow past a fullerene. We employ the Schwarz alternating overlapping domain method to couple molecular dynamics (MD) of liquid water around the C540 buckyball with a Lattice-Boltzmann (LB) description for the Navier-Stokes equations. The proposed method links the MD and LB domains using a fully three-dimensional interface and coupling of velocity gradients. The present overlapping domain method implicitly preserves the flux of mass and momentum and bridges flux-based and Schwarz domain decomposition algorithms. We use this method to determine the slip length and hydrodynamic radius for water flow past a buckyball.
Multi-scale statistical analysis of coronal solar activity
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.
Multiscale models and approximation algorithms for protein electrostatics
Bardhan, Jaydeep P
2015-01-01
Electrostatic forces play many important roles in molecular biology, but are hard to model due to the complicated interactions between biomolecules and the surrounding solvent, a fluid composed of water and dissolved ions. Continuum model have been surprisingly successful for simple biological questions, but fail for important problems such as understanding the effects of protein mutations. In this paper we highlight the advantages of boundary-integral methods for these problems, and our use of boundary integrals to design and test more accurate theories. Examples include a multiscale model based on nonlocal continuum theory, and a nonlinear boundary condition that captures atomic-scale effects at biomolecular surfaces.
Multiscale topology optimization of solid and fluid structures
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe
This thesis considers the application of the topology optimization method to multiscale problems, specifically the fluid-structure interaction problem. By multiple-scale methods the governing equations, the Navier-Cauchy and the incompressible Navier-Stokes equations are expanded and separated......, it is shown that the material microstructure can be optimized with respect to application scale properties. A poroelastic actuator consisting of two saturated porous materials is optimized using this approach. Based on the homogenization of a fixed microstructure topology, material design interpolation...... designs a new explicit parametrization is proposed. It allows for casting/milling type manufacturing and ensures a binary design. The method is successfully applied to micromixer design....
A Multi-Scale Gradient Algorithm Based on Morphological Operators
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Watershed transformation is a powerful morphological tool for image segmentation. However, the performance of the image segmentation methods based on watershed transformation depends largely on the algorithm for computing the gradient of the image to be segmented. In this paper, we present a multi-scale gradient algorithm based on morphological operators for watershed-based image segmentation, with effective handling of both step and blurred edges. We also present an algorithm to eliminate the local minima produced by noise and quantization errors. Experimental results indicate that watershed transformation with the algorithms proposed in this paper produces meaningful segmentations, even without a region-merging step.
Modeling of Multiscale and Multiphase Phenomena in Materials Processing
Ludwig, Andreas; Kharicha, Abdellah; Wu, Menghuai
2013-03-01
In order to demonstrate how CFD can help scientists and engineers to better understand the fundamentals of engineering processes, a number of examples are shown and discussed. The paper covers (i) special aspects of continuous casting of steel including turbulence, motion and entrapment of non-metallic inclusions, and impact of soft reduction; (ii) multiple flow phenomena and multiscale aspects during casting of large ingots including flow-induced columnar-to-equiaxed transition and 3D formation of channel segregation; (iii) multiphase magneto-hydrodynamics during electro-slag remelting; and (iv) melt flow and solidification of thin but large centrifugal castings.
The turbulent flow generated by inhomogeneous multiscale grids
Zheng, Shaokai; Bruce, Paul J. K.; Graham, J. Michael R.; Vassilicos, John Christos
2015-11-01
A group of inhomogeneous multiscale grids have been designed and tested in a low speed wind tunnel in an attempt to generate bespoke turbulent shear flows. Cross-wire anemometry measurements were performed in different planes parallel to the grid and at various streamwise locations to study turbulence development behind each of the different geometry grids. Two spatially separated single hot wires were also used to measure transverse integral length scale at selected locations. Results are compared to previous studies of shearless mixing layer grids and fractal grids, including mean flow profiles and turbulence statistics.
Multiscale physics of ion-induced radiation damage.
Surdutovich, Eugene; Solov'yov, A V
2014-01-01
This is a review of a multiscale approach to the physics of ion-beam cancer therapy, an approach suggested in order to understand the interplay of a large number of phenomena involved in the radiation damage scenario occurring on a range of temporal, spatial, and energy scales. We describe different effects that take place on different scales and play major roles in the scenario of interaction of ions with tissue. The understanding of these effects allows an assessment of relative biological effectiveness that relates the physical quantities, such as dose, to the biological values, such as the probability of cell survival.
Engineering Complex Systems: Multiscale Analysis and Evolutionary Engineering
Bar-Yam, Yaneer
We describe an analytic approach, multiscale analysis, that can demonstrate the fundamental limitations of decomposition based engineering for the development of highly complex systems. The interdependence of components and communication between design teams limits any planning based process. Recognizing this limitation, we found that a new strategy for constructing many highly complex systems should be modeled after biological evolution, or market economies, where multiple design efforts compete in parallel for adoption through testing in actual use. Evolution is the only process that is known to create highly complex systems.
Multi-scale modeling for sustainable chemical production
DEFF Research Database (Denmark)
Zhuang, Kai; Bakshi, Bhavik R.; Herrgard, Markus
2013-01-01
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......, 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...
Gaussian multiscale aggregation applied to segmentation in hand biometrics.
de Santos Sierra, Alberto; Avila, Carmen Sánchez; Casanova, Javier Guerra; del Pozo, Gonzalo Bailador
2011-01-01
This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.
Hypoglycemia-Related Electroencephalogram Changes Assessed by Multiscale Entropy
DEFF Research Database (Denmark)
Fabris, C.; Sparacino, G.; Sejling, A. S.
2014-01-01
physiopathological conditions have never been assessed in hypoglycemia. The present study investigates if properties of the EEG signal measured by nonlinear entropy-based algorithms are altered in a significant manner when a state of hypoglycemia is entered. Subjects and Methods: EEG was acquired from 19 patients...... derivation in the two glycemic intervals was assessed using the multiscale entropy (MSE) approach, obtaining measures of sample entropy (SampEn) at various temporal scales. The comparison of how signal irregularity measured by SampEn varies as the temporal scale increases in the two glycemic states provides...
Multi-Scale Dynamics, Control, and Simulation of Granular Spacecraft
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 structural similarity index for motion detection
Directory of Open Access Journals (Sweden)
M. Abdel-Salam Nasr
2017-07-01
Full Text Available The most recent approach for measuring the image quality is the structural similarity index (SSI. This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed.
Moving in a crowd: human perception as a multiscale process
Colombi, Annachiara; Tosin, Andrea
2015-01-01
The strategic behavior of pedestrians is largely determined by how they perceive and consequently react to neighboring people. Such interpersonal interactions may be dictated by the emotional state of the individuals, the purpose of their trip, the local crowding, the quality of the environment to mention but a few common examples. This issue is addressed in this paper by a mathematical model which combines, in an evolutionary time- and space-dependent way, discrete and continuous effects of pedestrian interactions. Numerical simulations and qualitative analysis suggest that human perception, and its impact on crowd dynamics, can be effectively modeled as a multiscale process based on such a dual representation of groups of agents.
Multiscale Modeling of Red Blood Cells Squeezing through Submicron Slits
Peng, Zhangli; Lu, Huijie
2016-11-01
A multiscale model is applied to study the dynamics of healthy red blood cells (RBCs), RBCs in hereditary spherocytosis, and sickle cell disease squeezing through submicron slits. This study is motivated by the mechanical filtration of RBCs by inter-endothelial slits in the spleen. First, the model is validated by comparing the simulation results with experiments. Secondly, the deformation of the cytoskeleton in healthy RBCs is investigated. Thirdly, the mechanisms of damage in hereditary spherocytosis are investigated. Finally, the effects of cytoplasm and membrane viscosities, especially in sickle cell disease, are examined. The simulations results provided guidance for future experiments to explore the dynamics of RBCs under extreme deformation.
Fluid-Solid Interaction and Multiscale Dynamic Processes: Experimental Approach
Arciniega-Ceballos, Alejandra; Spina, Laura; Mendo-Pérez, Gerardo M.; Guzmán-Vázquez, Enrique; Scheu, Bettina; Sánchez-Sesma, Francisco J.; Dingwell, Donald B.
2017-04-01
The speed and the style of a pressure drop in fluid-filled conduits determines the dynamics of multiscale processes and the elastic interaction between the fluid and the confining solid. To observe this dynamics we performed experiments using fluid-filled transparent tubes (15-50 cm long, 2-4 cm diameter and 0.3-1 cm thickness) instrumented with high-dynamic piezoelectric sensors and filmed the evolution of these processes with a high speed camera. We analyzed the response of Newtonian fluids to slow and sudden pressure drops from 3 bar-10 MPa to ambient pressure. We used fluids with viscosities of mafic to intermediate silicate melts of 1 to 1000 Pa s and water. The processes observed are fluid mass expansion, fluid flow, jets, bubbles nucleation, growth, coalescence and collapse, degassing, foam building at the surface and vertical wagging. All these processes (in fine and coarse scales) are triggered by the pressure drop and are sequentially coupled in time while interacting with the solid. During slow decompression, the multiscale processes are recognized occurring within specific pressure intervals, and exhibit a localized distribution along the conduit. In this, degassing predominates near the surface and may present piston-like oscillations. In contrast, during sudden decompression the fluid-flow reaches higher velocities, the dynamics is dominated by a sequence of gas-packet pulses driving jets of the gas-fluid mixture. The evolution of this multiscale phenomenon generates complex non-stationary microseismic signals recorded along the conduit. We discuss distinctive characteristics of these signals depending on the decompression style and compare them with synthetics. These synthetics are obtained numerically under an averaging modeling scheme, that accounted for the stress-strain of the cyclic dynamic interaction between the fluid and the solid wall, assuming an incompressible and viscous fluid that flows while the elastic solid responds oscillating
Multi-Scale Jacobi Method for Anderson Localization
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, arXiv:1403.7837 , 2014).
A Reduced Basis Approach for Some Weakly Stochastic Multiscale Problems
Institute of Scientific and Technical Information of China (English)
Claude LE BRIS; Florian THOMINES
2012-01-01
In this paper,a multiscale problem arising in material science is considered.The problem involves a random coefficient which is assumed to be a perturbation of a deterministic coefficient,in a sense made precisely in the body of the text.The homogenized limit is then computed by using a perturbation approach.This computation requires repeatedly solving a corrector-like equation for various configurations of the material.For this purpose,the reduced basis approach is employed and adapted to the specific context.The authors perform numerical tests that demonstrate the efficiency of the approach.
A service-oriented distributed semantic mediator: integrating multiscale biomedical information.
Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus
2012-11-01
Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.
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.
2016-02-01
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.
Generalized multiscale finite element methods for problems in perforated heterogeneous domains
Chung, Eric T.
2015-06-08
Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales. Moreover, these problems are intrinsically multiscale and their discretizations can yield very large linear or nonlinear systems. In this paper, we investigate multiscale approaches that attempt to solve such problems on a coarse grid by constructing multiscale basis functions in each coarse grid, where the coarse grid can contain many perforations. In particular, we are interested in cases when there is no scale separation and the perforations can have different sizes. In this regard, we mention some earlier pioneering works, where the authors develop multiscale finite element methods. In our paper, we follow Generalized Multiscale Finite Element Method (GMsFEM) and develop a multiscale procedure where we identify multiscale basis functions in each coarse block using snapshot space and local spectral problems. We show that with a few basis functions in each coarse block, one can approximate the solution, where each coarse block can contain many small inclusions. We apply our general concept to (1) Laplace equation in perforated domains; (2) elasticity equation in perforated domains; and (3) Stokes equations in perforated domains. Numerical results are presented for these problems using two types of heterogeneous perforated domains. The analysis of the proposed methods will be presented elsewhere. © 2015 Taylor & Francis
Ontology-based analysis of multi-scale modeling of geographical features
Institute of Scientific and Technical Information of China (English)
WANG; Yanhui; LI; Xiaojuan; GONG; Huili
2006-01-01
As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. However, the results of multi-scale conceptual abstraction schema may differ, according to which cognition, abstraction and application views are utilized, which presents an obvious obstacle to the reuse and sharing of spatial data. To facilitate the design of unified, common and objective abstract schema views for multi-scale spatial databases, this paper proposes an ontology-based analysis method for the multi-scale modeling of geographical features. It includes a three-layer ontology model, which serves as the framework for common multi-scale abstraction schema; an explanation of formulary abstractions accompanied by definitions of entities and their relationships at the same scale, as well as different scales,which are meant to provide strong feasibility, expansibility and speciality functions; and a case in point involving multi-scale representations of road features, to verify the method's feasibility.
Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology
Macioł, Piotr; Michalik, Kazimierz
2016-10-01
Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.
Multiscale Hybrid Nonlocal Means Filtering Using Modified Similarity Measure
Directory of Open Access Journals (Sweden)
Zahid Hussain Shamsi
2015-01-01
Full Text Available A new multiscale implementation of nonlocal means filtering (MHNLM for image denoising is proposed. The proposed algorithm also introduces a modification of the similarity measure for patch comparison. Assuming the patch as an oriented surface, the notion of a normal vectors patch is introduced. The inner product of these normal vectors patches is defined and then used in the weighted Euclidean distance of intensity patches as the weight factor. The algorithm involves two steps: the first step is a multiscale implementation of an accelerated nonlocal means filtering in the discrete stationary wavelet domain to obtain a refined version of the noisy patches for later comparison. The next step is to apply the proposed modification of standard nonlocal means filtering to the noisy image using the reference patches obtained in the first step. These refined patches contain less noise, and consequently the computation of normal vectors and partial derivatives is more precise. Experimental results show equivalent or better performance of the proposed algorithm compared to various state-of-the-art algorithms.
Fast point cloud registration algorithm using multiscale angle features
Lu, Jun; Guo, Congling; Fang, Ying; Xia, Guihua; Wang, Wanjia; Elahi, Ahsan
2017-05-01
To fulfill the demands of rapid and real-time three-dimensional optical measurement, a fast point cloud registration algorithm using multiscale axis angle features is proposed. The key point is selected based on the mean value of scalar projections of the vectors from the estimated point to the points in the neighborhood on the normal of the estimated point. This method has a small amount of computation and good discriminating ability. A rotation invariant feature is proposed using the angle information calculated based on multiscale coordinate axis. The feature descriptor of a key point is computed using cosines of the angles between corresponding coordinate axes. Using this method, the surface information around key points is obtained sufficiently in three axes directions and it is easy to recognize. The similarity of descriptors is employed to quickly determine the initial correspondences. The rigid spatial distance invariance and clustering selection method are used to make the corresponding relationships more accurate and evenly distributed. Finally, the rotation matrix and translation vector are determined using the method of singular value decomposition. Experimental results show that the proposed algorithm has high precision, fast matching speed, and good antinoise capability.
Strong, Multi-Scale Heterogeneity in Earth's Lowermost Mantle.
Tkalčić, Hrvoje; Young, Mallory; Muir, Jack B; Davies, D Rhodri; Mattesini, Maurizio
2015-12-17
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.
Multiscale CNNs for Brain Tumor Segmentation and Diagnosis
Zhao, Liya; Jia, Kebin
2016-01-01
Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs). Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness. PMID:27069501
Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm.
Wen, Xian-Bin; Zhang, Hua; Jiang, Ze-Tao
2008-03-12
A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization(EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive(MMAR) model is introduced to characterize and exploit the scale-to-scale statisticalvariations and statistical variations in the same scale in SAR imagery due to radar speckle,and a segmentation method is given by combining the GA algorithm with the EMalgorithm. This algorithm is capable of selecting the number of components of the modelusing the minimum description length (MDL) criterion. Our approach benefits from theproperties of the Genetic and the EM algorithm by combination of both into a singleprocedure. The population-based stochastic search of the genetic algorithm (GA) exploresthe search space more thoroughly than the EM method. Therefore, our algorithm enablesescaping from local optimal solutions since the algorithm becomes less sensitive to itsinitialization. Some experiment results are given based on our proposed approach, andcompared to that of the EM algorithms. The experiments on the SAR images show that theGA-EM outperforms the EM method.
Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm
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Ze-Tao Jiang
2008-03-01
Full Text Available A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR imagery is proposed by a combination GA-EM of the Expectation Maximization(EM algorith with the genetic algorithm (GA. The mixture multiscale autoregressive(MMAR model is introduced to characterize and exploit the scale-to-scale statisticalvariations and statistical variations in the same scale in SAR imagery due to radar speckle,and a segmentation method is given by combining the GA algorithm with the EMalgorithm. This algorithm is capable of selecting the number of components of the modelusing the minimum description length (MDL criterion. Our approach benefits from theproperties of the Genetic and the EM algorithm by combination of both into a singleprocedure. The population-based stochastic search of the genetic algorithm (GA exploresthe search space more thoroughly than the EM method. Therefore, our algorithm enablesescaping from local optimal solutions since the algorithm becomes less sensitive to itsinitialization. Some experiment results are given based on our proposed approach, andcompared to that of the EM algorithms. The experiments on the SAR images show that theGA-EM outperforms the EM method.
Computer aided polymer design using multi-scale modelling
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K. C. Satyanarayana
2010-09-01
Full Text Available The ability to predict the key physical and chemical properties of polymeric materials from their repeat-unit structure and chain-length architecture prior to synthesis is of great value for the design of polymer-based chemical products, with new functionalities and improved performance. Computer aided molecular design (CAMD methods can expedite the design process by establishing input-output relations between the type and number of functional groups in a polymer repeat unit and the desired macroscopic properties. A multi-scale model-based approach that combines a CAMD technique based on group contribution plus models for predicting polymer repeat unit properties with atomistic simulations for providing first-principles arrangements of the repeat units and for predictions of physical properties of the chosen candidate polymer structures, has been developed and tested for design of polymers with desired properties. A case study is used to highlight the main features of this multi-scale model-based approach for the design of a polymer-based product.
Extracting the multiscale backbone of complex weighted networks
Serrano, M. Ángeles; Boguñá, Marián; Vespignani, Alessandro
2009-01-01
A large number of complex systems find a natural abstraction in the form of weighted networks whose nodes represent the elements of the system and the weighted edges identify the presence of an interaction and its relative strength. In recent years, the study of an increasing number of large-scale networks has highlighted the statistical heterogeneity of their interaction pattern, with degree and weight distributions that vary over many orders of magnitude. These features, along with the large number of elements and links, make the extraction of the truly relevant connections forming the network's backbone a very challenging problem. More specifically, coarse-graining approaches and filtering techniques come into conflict with the multiscale nature of large-scale systems. Here, we define a filtering method that offers a practical procedure to extract the relevant connection backbone in complex multiscale networks, preserving the edges that represent statistically significant deviations with respect to a null model for the local assignment of weights to edges. An important aspect of the method is that it does not belittle small-scale interactions and operates at all scales defined by the weight distribution. We apply our method to real-world network instances and compare the obtained results with alternative backbone extraction techniques. PMID:19357301
Hierarchical Multiscale Modeling of Macromolecules and their Assemblies.
Ortoleva, P; Singharoy, A; Pankavich, S
2013-04-28
Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character of such systems often makes traditional molecular dynamics simulation impractical, a multiscale approach has been presented that allows for long-time simulation with atomic detail based on the co-evolution of slowly-varying order parameters (OPs) with the quasi-equilibrium probability density of atomic configurations. However, this approach breaks down when the structural change is extreme, or when nearest-neighbor connectivity of atoms is not maintained. In the current study, a self-consistent approach is presented wherein OPs and a reference structure co-evolve slowly to yield long-time simulation for dynamical soft-matter phenomena such as structural transitions and self-assembly. The development begins with the Liouville equation for N classical atoms and an ansatz on the form of the associated N-atom probability density. Multiscale techniques are used to derive Langevin equations for the coupled OP-configurational dynamics. The net result is a set of equations for the coupled stochastic dynamics of the OPs and centers of mass of the subsystems that constitute a soft material body. The theory is based on an all-atom methodology and an interatomic force field, and therefore enables calibration-free simulations of soft matter, such as macromolecular assemblies.
Linking Futures across Scales: a Dialog on Multiscale Scenarios
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Reinette Biggs
2007-06-01
Full Text Available Scenario analysis is a useful tool for exploring key uncertainties that may shape the future of social-ecological systems. This paper explores the methods, costs, and benefits of developing and linking scenarios of social-ecological systems across multiple spatial scales. Drawing largely on experiences in the Millennium Ecosystem Assessment, we suggest that the desired degree of cross-scale linkage depends on the primary aim of the scenario exercise. Loosely linked multiscale scenarios appear more appropriate when the primary aim is to engage in exploratory dialog with stakeholders. Tightly coupled cross-scale scenarios seem to work best when the main objective is to further our understanding of cross-scale interactions or to assess trade-offs between scales. The main disadvantages of tightly coupled cross-scale scenarios are that their development requires substantial time and financial resources, and that they often suffer loss of credibility at one or more scales. The reasons for developing multiscale scenarios and the expectations associated with doing so therefore need to be carefully evaluated when choosing the desired degree of cross-scale linkage in a particular scenario exercise.
Multiscale modeling of soft matter: scaling of dynamics.
Fritz, Dominik; Koschke, Konstantin; Harmandaris, Vagelis A; van der Vegt, Nico F A; Kremer, Kurt
2011-06-14
Many physical phenomena and properties of soft matter systems are characterized by an interplay of interactions and processes that span a wide range of length- and time scales. Computer simulation approaches require models, which cover these scales. These are typically multiscale models that combine and link different levels of resolution. In order to reach mesoscopic time- and length scales, necessary to access material properties, coarse-grained models are developed. They are based on microscopic, atomistic descriptions of systems and represent these systems on a coarser, mesoscopic level. While the connection between length scales can be established immediately, the link between the different time scales that takes into account the faster dynamics of the coarser system cannot be obtained directly. In this perspective paper we discuss methods that link the time scales in structure based multiscale models. Concepts which try to rigorously map dynamics of related models are limited to simple model systems, while the challenge in soft matter systems is the multitude of fluctuating energy barriers of comparable height. More pragmatic methods to match time scales are applied successfully to quantitatively understand and predict dynamics of one-component soft matter systems. However, there are still open questions. We point out that the link between the dynamics on different resolution levels can be affected by slight changes of the system, as for different tacticities. Furthermore, in two-component systems the dynamics of the host polymer and of additives are accelerated very differently.
Multiscale modeling and computation of optically manipulated nano devices
Bao, Gang; Liu, Di; Luo, Songting
2016-07-01
We present a multiscale modeling and computational scheme for optical-mechanical responses of nanostructures. The multi-physical nature of the problem is a result of the interaction between the electromagnetic (EM) field, the molecular motion, and the electronic excitation. To balance accuracy and complexity, we adopt the semi-classical approach that the EM field is described classically by the Maxwell equations, and the charged particles follow the Schrödinger equations quantum mechanically. To overcome the numerical challenge of solving the high dimensional multi-component many-body Schrödinger equations, we further simplify the model with the Ehrenfest molecular dynamics to determine the motion of the nuclei, and use the Time-Dependent Current Density Functional Theory (TD-CDFT) to calculate the excitation of the electrons. This leads to a system of coupled equations that computes the electromagnetic field, the nuclear positions, and the electronic current and charge densities simultaneously. In the regime of linear responses, the resonant frequencies initiating the out-of-equilibrium optical-mechanical responses can be formulated as an eigenvalue problem. A self-consistent multiscale method is designed to deal with the well separated space scales. The isomerization of azobenzene is presented as a numerical example.
Multiscale object-oriented change detection over urban areas
Wang, Jianmei; Li, Deren
2006-10-01
Urban growth induces urban spatial expansion in many cities in China. There is a great need for up-to-date information for effective urban decision-making and sustainable development. Many researches have demonstrated that satellite images, especial high resolution images, are very suitable for urban growth studies. However, change detection technique is the key to keep current with the rapid urban growth rate, taking advantage of tremendous amounts of satellite data. In this paper, a multi-scale object-oriented change detection approach integrating GIS and remote sensing is introduced. Firstly, a subset of image is cropped based on existing parcel boundaries stored in GIS database, then a multi-scale watershed transform is carried out to obtain the image objects. The image objects are classified into different land cover types by supervised classification based on their spectral, geometry and texture attributes. Finally a rule-based system is set up to judge every parcel one by one whether or not change happened comparing to existing GIS land use types. In order to verify the application validity of the presented methodology, the rural-urban fringe of Shanghai in China with the support of QuickBird date and GIS is tested, the result shown that it is effective to detect illegal land use parcel.
Multiscale recurrence analysis of spatio-temporal data
Riedl, M.; Marwan, N.; Kurths, J.
2015-12-01
The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.
Strain analysis of nanowire interfaces in multiscale composites
Malakooti, Mohammad H.; Zhou, Zhi; Spears, John H.; Shankwitz, Timothy J.; Sodano, Henry A.
2016-04-01
Recently, the reinforcement-matrix interface of fiber reinforced polymers has been modified through grafting nanostructures - particularly carbon nanotubes and ZnO nanowires - on to the fiber surface. This type of interface engineering has made a great impact on the development of multiscale composites that have high stiffness, interfacial strength, toughness, and vibrational damping - qualities that are mutually exclusive to a degree in most raw materials. Although the efficacy of such nanostructured interfaces has been established, the reinforcement mechanisms of these multiscale composites have not been explored. Here, strain transfer across a nanowire interphase is studied in order to gain a heightened understanding of the working principles of physical interface modification and the formation of a functional gradient. This problem is studied using a functionally graded piezoelectric interface composed of vertically aligned lead zirconate titanate nanowires, as their piezoelectric properties can be utilized to precisely control the strain on one side of the interface. The displacement and strain across the nanowire interface is captured using digital image correlation. It is demonstrated that the material gradient created through nanowires cause a smooth strain transfer from reinforcement phase into matrix phase that eliminates the stress concentration between these phases, which have highly mismatched elasticity.
Multi-scale window specification over streaming trajectories
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Kostas Patroumpas
2013-12-01
Full Text Available Enormous amounts of positional information are collected by monitoring applications in domains such as fleet management, cargo transport, wildlife protection, etc. With the advent of modern location-based services, processing such data mostly focuses on providing real-time response to a variety of user requests in continuous and scalable fashion. An important class of such queries concerns evolving trajectories that continuously trace the streaming locations of moving objects, like GPS-equipped vehicles, commodities with RFID's, people with smartphones etc. In this work, we propose an advanced windowing operator that enables online, incremental examination of recent motion paths at multiple resolutions for numerous point entities. When applied against incoming positions, this window can abstract trajectories at coarser representations towards the past, while retaining progressively finer features closer to the present. We explain the semantics of such multi-scale sliding windows through parameterized functions that reflect the sequential nature of trajectories and can effectively capture their spatiotemporal properties. Such window specification goes beyond its usual role for non-blocking processing of multiple concurrent queries. Actually, it can offer concrete subsequences from each trajectory, thus preserving continuity in time and contiguity in space along the respective segments. Further, we suggest language extensions in order to express characteristic spatiotemporal queries using windows. Finally, we discuss algorithms for nested maintenance of multi-scale windows and evaluate their efficiency against streaming positional data, offering empirical evidence of their benefits to online trajectory processing.