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...
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...
Zanin, Massimiliano; Chorbev, Ivan; Stres, Blaz; Stalidzans, Egils; Vera, Julio; Tieri, Paolo; Castiglione, Filippo; Groen, Derek; Zheng, Huiru; Baumbach, Jan; Schmid, Johannes A; Basilio, José; Klimek, Peter; Debeljak, Nataša; Rozman, Damjana; Schmidt, Harald H H W
2017-12-05
Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine. © The Author 2017. Published by Oxford University Press.
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.
Multi-scale structural community organisation of the human genome.
Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin
2017-04-11
Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.
Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...
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.
Reconfiguration of Cortical Networks in MDD Uncovered by Multiscale Community Detection with fMRI.
He, Ye; Lim, Sol; Fortunato, Santo; Sporns, Olaf; Zhang, Lei; Qiu, Jiang; Xie, Peng; Zuo, Xi-Nian
2018-04-01
Major depressive disorder (MDD) is known to be associated with altered interactions between distributed brain regions. How these regional changes relate to the reorganization of cortical functional systems, and their modulation by antidepressant medication, is relatively unexplored. To identify changes in the community structure of cortical functional networks in MDD, we performed a multiscale community detection algorithm on resting-state functional connectivity networks of unmedicated MDD (uMDD) patients (n = 46), medicated MDD (mMDD) patients (n = 38), and healthy controls (n = 50), which yielded a spectrum of multiscale community partitions. we selected an optimal resolution level by identifying the most stable community partition for each group. uMDD and mMDD groups exhibited a similar reconfiguration of the community structure of the visual association and the default mode systems but showed different reconfiguration profiles in the frontoparietal control (FPC) subsystems. Furthermore, the central system (somatomotor/salience) and 3 frontoparietal subsystems showed strengthened connectivity with other communities in uMDD but, with the exception of 1 frontoparietal subsystem, returned to control levels in mMDD. These findings provide evidence for reconfiguration of specific cortical functional systems associated with MDD, as well as potential effects of medication in restoring disease-related network alterations, especially those of the FPC system.
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.
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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.
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Karen Ikin
Full Text Available Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1 How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2 Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3 Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha over two time periods across a large (6,800 km(2 agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities.
Gantt, B.; Kelly, J. T.; Bash, J. O.
2015-01-01
Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are also important due to the localized impact of SSAs on atmospheric chemistry near the coast. In this study, SSA emissions in the Community Multiscale Air Quality (CMAQ) model were updated to enhance the...
J. T. Kelly; P. V. Bhave; C. G. Nolte; U. Shankar; K. M. Foley
2009-01-01
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 (C...
Updating Sea Spray Aerosol Emissions in the Community Multiscale Air Quality Model
Gantt, B.; Bash, J. O.; Kelly, J.
2014-12-01
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, include sea surface temperature (SST) dependency, and revise surf zone emissions. Based on evaluation with several regional and national observational datasets in the continental U.S., the updated emissions generally improve surface concentrations predictions of primary aerosols composed of sea-salt and secondary aerosols affected by sea-salt chemistry in coastal and near-coastal sites. Specifically, the updated emissions lead to better predictions of the magnitude and coastal-to-inland gradient of sodium, chloride, and nitrate concentrations at Bay Regional Atmospheric Chemistry Experiment (BRACE) sites near Tampa, FL. Including SST-dependency to the SSA emission parameterization leads to increased sodium concentrations in the southeast U.S. and decreased concentrations along the Pacific coast and northeastern U.S., bringing predictions into closer agreement with observations at most Interagency Monitoring of Protected Visual Environments (IMPROVE) and Chemical Speciation Network (CSN) sites. Model comparison with California Research at the Nexus of Air Quality and Climate Change (CalNex) observations will also be discussed, with particular focus on the South Coast Air Basin where clean marine air mixes with anthropogenic pollution in a complex environment. These SSA emission updates enable more realistic simulation of chemical processes in coastal environments, both in clean marine air masses and mixtures of clean marine and polluted conditions.
Incremental testing of the Community Multiscale Air Quality (CMAQ modeling system version 4.7
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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.
Morris, Ralph E; McNally, Dennis E; Tesche, Thomas W; Tonnesen, Gail; Boylan, James W; Brewer, Patricia
2005-11-01
The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve
Macklin, Paul; Cristini, Vittorio
2013-01-01
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 insight on 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. PMID:21529163
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.
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.
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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.
Matthias , V.
2008-01-01
The aerosol distribution in Europe was simulated with the Community Multiscale Air Quality (CMAQ) model system version 4.5 for the years 2000 and 2001. The results were compared with daily averages of PM_{10} measurements taken in the framework of EMEP and with aerosol optical depth (AOD) values measured within AERONET. The modelled total aerosol mass is typically about 30–60% lower than the corresponding measurements. However a comparison of the chemical composition of th...
Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A
2018-07-01
Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.
Matichuk, Rebecca; Tonnesen, Gail; Luecken, Deborah; Gilliam, Rob; Napelenok, Sergey L.; Baker, Kirk R.; Schwede, Donna; Murphy, Ben; Helmig, Detlev; Lyman, Seth N.; Roselle, Shawn
2017-12-01
The Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models were used to simulate a 10 day high-ozone episode observed during the 2013 Uinta Basin Winter Ozone Study (UBWOS). The baseline model had a large negative bias when compared to ozone (O3) and volatile organic compound (VOC) measurements across the basin. Contrary to other wintertime Uinta Basin studies, predicted nitrogen oxides (NOx) were typically low compared to measurements. Increases to oil and gas VOC emissions resulted in O3 predictions closer to observations, and nighttime O3 improved when reducing the deposition velocity for all chemical species. Vertical structures of these pollutants were similar to observations on multiple days. However, the predicted surface layer VOC mixing ratios were generally found to be underestimated during the day and overestimated at night. While temperature profiles compared well to observations, WRF was found to have a warm temperature bias and too low nighttime mixing heights. Analyses of more realistic snow heat capacity in WRF to account for the warm bias and vertical mixing resulted in improved temperature profiles, although the improved temperature profiles seldom resulted in improved O3 profiles. While additional work is needed to investigate meteorological impacts, results suggest that the uncertainty in the oil and gas emissions contributes more to the underestimation of O3. Further, model adjustments based on a single site may not be suitable across all sites within the basin.
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.
Blending science and community voices for multi-scale disaster risk ...
African Journals Online (AJOL)
This paper documents the experience of CARE International in Ethiopia in facilitating bottom-up approaches to promote community-led disaster risk management and climate change adaptation planning through a participator scenario planning (PSP) methodology. PSP is a coordinated approach which leverages a variety ...
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
Fahey, Kathleen M.; Carlton, Annmarie G.; Pye, Havala O. T.; Baek, Jaemeen; Hutzell, William T.; Stanier, Charles O.; Baker, Kirk R.; Wyat Appel, K.; Jaoui, Mohammed; Offenberg, John H.
2017-04-01
This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM - KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM - KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM - KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in cloud SOA at the surface in the eastern United States for June 2013.
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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
Gantt, B.; Kelly, J. T.; Bash, J. O.
2015-11-01
Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are also important due to the localized impact of SSAs on atmospheric chemistry near the coast. In this study, SSA emissions in the Community Multiscale Air Quality (CMAQ) model were updated to enhance the fine-mode size distribution, include sea surface temperature (SST) dependency, and reduce surf-enhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several coastal and national observational data sets in the continental US. The updated emissions generally reduced model underestimates of sodium, chloride, and nitrate surface concentrations for coastal sites in 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 southeastern 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 a modest improvement in the predicted surface concentration of sodium and nitrate at several central and southern California coastal sites. This update of SSA emissions enabled a more realistic simulation of the atmospheric chemistry in coastal environments where marine air mixes with urban pollution.
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
Distributed multiscale computing
Borgdorff, J.
2014-01-01
Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale
Multi-scales analysis of the global change impact on the diversity of the aphid communities
International Nuclear Information System (INIS)
Hulle, M.
2007-01-01
The primary objective of this project is to investigate the effects of global change on the biodiversity of aphid communities in Western Europe. Biodiversity has been examined at 3 levels: total number of species, phenology and reproductive strategy. Data were provided by EXAMINE, the European suction traps network which has been now operating for 35 years. 392 different species have been identified. At each location, total number of species has been regularly increasing, one additional species being caught every 1 or 2 years depending on location. This is due to introduced species but also to warming which favours rare species. No general trend of increasing density has been detected, but phenological earliness of almost all species (annual date of first appearance in suction traps) is strongly correlated with temperature and especially with mean daily temperature (during more or less long periods of time lying principally in February and March) or number of days below 0 C. Strong relationships between aphid phenology and environmental variables have been found and there is strong discrimination between species with different life cycle strategies, and between species feeding on herbs and trees, suggesting the possible value of trait-based groupings in predicting responses to environmental changes. These preliminary results suggest that 1) biodiversity has increased during the last decades; 2) there is a pool of species among which some of them reach a detectable density only during years where temperatures are high enough; 3) a set of newly introduced species succeed in settling being favoured by warming and 4) phenology of aphids is expected to advance and their abundance to increase with temperature, and the possible role of natural enemies to regulate abundant species is discussed. (author)
Rasmussen, Pil U; Hugerth, Luisa W; Blanchet, F Guillaume; Andersson, Anders F; Lindahl, Björn D; Tack, Ayco J M
2018-03-24
Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above-ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood. We sequenced DNA markers from roots and root-associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root-associated fungi. AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes. We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small-scale variation in community dynamics and biodiversity. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.
Directory of Open Access Journals (Sweden)
K. W. Appel
2013-07-01
Full Text Available The Community Multiscale Air Quality (CMAQ model is a state-of-the-science air quality model that simulates the emission, transformation, transport, and fate of the many different air pollutant species that comprise particulate matter (PM, including dust (or soil. The CMAQ model version 5.0 (CMAQv5.0 has several enhancements over the previous version of the model for estimating the emission and transport of dust, including the ability to track the specific elemental constituents of dust and have the model-derived concentrations of those elements participate in chemistry. The latest version of the model also includes a parameterization to estimate emissions of dust due to wind action. The CMAQv5.0 modeling system was used to simulate the entire year 2006 for the continental United States, and the model estimates were evaluated against daily surface-based measurements from several air quality networks. The CMAQ modeling system overall did well replicating the observed soil concentrations in the western United States (mean bias generally around ±0.5 μg m−3; however, the model consistently overestimated the observed soil concentrations in the eastern United States (mean bias generally between 0.5–1.5 μg m−3, regardless of season. The performance of the individual trace metals was highly dependent on the network, species, and season, with relatively small biases for Fe, Al, Si, and Ti throughout the year at the Interagency Monitoring of Protected Visual Environments (IMPROVE sites, while Ca, K, and Mn were overestimated and Mg underestimated. For the urban Chemical Speciation Network (CSN sites, Fe, Mg, and Mn, while overestimated, had comparatively better performance throughout the year than the other trace metals, which were consistently overestimated, including very large overestimations of Al (380%, Ti (370% and Si (470% in the fall. An underestimation of nighttime mixing in the urban areas appears to contribute to the overestimation of
Directory of Open Access Journals (Sweden)
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)
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.
Directory of Open Access Journals (Sweden)
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
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 0nitrate and sulfate concentrations are also well reproduced. The other unresolved PM2.5 components (OTHER) are significantly overestimated by more than a factor of two. No conclusive explanations can be made regarding the possible cause of this universal overestimation, which warrants a follow-up study to better understand this problem. Copyright © 2013 Elsevier B.V. All rights reserved.
Buonocore, Jonathan J; Dong, Xinyi; Spengler, John D; Fu, Joshua S; Levy, Jonathan I
2014-07-01
We estimated PM2.5-related public health impacts/ton emitted of primary PM2.5, SO2, and NOx for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration-response functions for PM2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM2.5 (range: $22,000-230,000), $28,000/ton for SO2 (range: $19,000-33,000), and $16,000/ton for NOx (range: $7100-26,000). Impacts of NOx were a median of 34% (range: 20%-75%) from ammonium nitrate and 66% (range: 25%-79%) from ammonium sulfate. The latter pathway is likely from NOx enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management. Copyright © 2014 Elsevier Ltd. All rights reserved.
Franklin, Rima B.; Mills, Aaron L.
2003-01-01
To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
Matichuk, R.; Tonnesen, G.; Luecken, D.; Roselle, S. J.; Napelenok, S. L.; Baker, K. R.; Gilliam, R. C.; Misenis, C.; Murphy, B.; Schwede, D. B.
2015-12-01
The western United States is an important source of domestic energy resources. One of the primary environmental impacts associated with oil and natural gas production is related to air emission releases of a number of air pollutants. Some of these pollutants are important precursors to the formation of ground-level ozone. To better understand ozone impacts and other air quality issues, photochemical air quality models are used to simulate the changes in pollutant concentrations in the atmosphere on local, regional, and national spatial scales. These models are important for air quality management because they assist in identifying source contributions to air quality problems and designing effective strategies to reduce harmful air pollutants. The success of predicting oil and natural gas air quality impacts depends on the accuracy of the input information, including emissions inventories, meteorological information, and boundary conditions. The treatment of chemical and physical processes within these models is equally important. However, given the limited amount of data collected for oil and natural gas production emissions in the past and the complex terrain and meteorological conditions in western states, the ability of these models to accurately predict pollution concentrations from these sources is uncertain. Therefore, this presentation will focus on understanding the Community Multiscale Air Quality (CMAQ) model's ability to predict air quality impacts associated with oil and natural gas production and its sensitivity to input uncertainties. The results will focus on winter ozone issues in the Uinta Basin, Utah and identify the factors contributing to model performance issues. The results of this study will help support future air quality model development, policy and regulatory decisions for the oil and gas sector.
Directory of Open Access Journals (Sweden)
X. Dong
2016-07-01
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. 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.
Directory of Open Access Journals (Sweden)
V. Matthias
2008-09-01
Full Text Available The aerosol distribution in Europe was simulated with the Community Multiscale Air Quality (CMAQ model system version 4.5 for the years 2000 and 2001. The results were compared with daily averages of PM_{10} measurements taken in the framework of EMEP and with aerosol optical depth (AOD values measured within AERONET. The modelled total aerosol mass is typically about 30–60% lower than the corresponding measurements. However a comparison of the chemical composition of the aerosol revealed a considerably better agreement between the modelled and the measured aerosol components for ammonium, nitrate and sulfate, which are on average only 15–20% underestimated. Sligthly worse agreement was determined for sea salt, that was only avaliable at two sites. The largest discrepancies result from the aerosol mass which was not chemically specified by the measurements. The agreement between measurements and model is better in winter than in summer. The modelled organic aerosol mass is higher in summer than in winter but it is significantly underestimated by the model. This could be one of the main reasons for the discrepancies between measurements and model results. The other is that primary coarse particles are underestimated in the emissions. The probability distribution function of the PM_{10} measurements follows a log-normal distribution at most sites. The model is only able to reproduce this distribution function at non-coastal low altitude stations. The AOD derived from the model results is 20–70% lower than the values observed within AERONET. This is mainly attributed to the missing aerosol mass in the model. The day-to-day variability of the AOD and the log-normal distribution functions are quite well reproduced by the model. The seasonality on the other hand is underestimated by the model results because better agreement is achieved in winter.
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
O'Neill, Susan M; Lamb, Brian K; Chen, Jack; Claiborn, Candis; Finn, Dennis; Otterson, Sally; Figueroa, Cristiana; Bowman, Clint; Boyer, Mike; Wilson, Rob; Arnold, Jeff; Aalbers, Steven; Stocum, Jeffrey; Swab, Christopher; Stoll, Matt; Dubois, Mike; Anderson, Mary
2006-02-15
The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El
Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan
2006-10-01
A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.
Directory of Open Access Journals (Sweden)
K. W. Appel
2010-02-01
Full Text Available This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5 and the Weather Research and Forecasting (WRF meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ and the other utilized WRF meteorology (WRF-CMAQ, while all other model inputs and options were kept the same. For January, predicted ozone (O_{3} mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O_{3} mixing ratios are attributed to less dry deposition of O_{3} in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO_{4}^{2−}, similar performance for nitrate (NO_{3}^{−}, and slightly worse performance for nitric acid (HNO_{3}, total carbon (TC and total fine particulate (PM_{2.5} mass than the corresponding MM5-CMAQ results. For August, predictions of O_{3} were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO_{4}^{2−} were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u_{∗} in the MM5 and WRF model simulations, while
Directory of Open Access Journals (Sweden)
K. W. Appel
2011-05-01
Full Text Available This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ model simulations for 2002–2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (SO_{4}^{=}, ammonium (NH_{4}^{+} and nitrate (NO_{3}^{−}. Performance of the wet deposition estimates from the model is determined by comparing CMAQ predicted concentrations to concentrations measured by the National Acid Deposition Program (NADP, specifically the National Trends Network (NTN. For SO_{4}^{=} wet deposition, the CMAQ model estimates were generally comparable between the 36-km and 12-km simulations for the eastern US, with the 12-km simulation giving slightly higher estimates of SO_{4}^{=} wet deposition than the 36-km simulation on average. The result is a slightly larger normalized mean bias (NMB for the 12-km simulation; however both simulations had annual biases that were less than ±15 % for each of the five years. The model estimated SO_{4}^{=} wet deposition values improved when they were adjusted to account for biases in the model estimated precipitation. The CMAQ model underestimates NH_{4}^{+} wet deposition over the eastern US, with a slightly larger underestimation in the 36-km simulation. The largest underestimations occur in the winter and spring periods, while the summer and fall have slightly smaller underestimations of NH_{4}^{+} wet deposition. The underestimation in NH_{4}^{+} wet deposition is likely due in part to the poor temporal and spatial representation of ammonia (NH_{3} emissions, particularly those emissions associated with fertilizer applications and NH_{3} bi-directional exchange. The model performance for estimates of NO_{3}^{−} wet deposition are
Differential Geometry Based Multiscale Models
Wei, Guo-Wei
2010-01-01
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 atom-istic 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
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 Representations Phase II
National Research Council Canada - National Science Library
Bar-Yam, Yaneer
2004-01-01
.... Multiscale analysis provides an analytic tool that can be applied to evaluating force capabilities as well as the relevance of designs for technological innovations to support force structures and their modernization...
Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M.
2011-03-01
Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models.
1990-02-21
LIDS-P-1953 Multiscale System Theory Albert Benveniste IRISA-INRIA, Campus de Beaulieu 35042 RENNES CEDEX, FRANCE Ramine Nikoukhah INRIA...TITLE AND SUBTITLE Multiscale System Theory 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the development of a corresponding system theory and a theory of stochastic processes and their estimation. The research presented in this and several
Multiscale Simulations Using Particles
DEFF Research Database (Denmark)
Walther, Jens Honore
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...... 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....
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
Multiscale Biological Materials
DEFF Research Database (Denmark)
Frølich, Simon
of multiscale biological systems have been investigated and new research methods for automated Rietveld refinement and diffraction scattering computed tomography developed. The composite nature of biological materials was investigated at the atomic scale by looking at the consequences of interactions between...
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
Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol
2017-12-01
This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.
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 modelling of nanostructures
International Nuclear Information System (INIS)
Vvedensky, Dimitri D
2004-01-01
Most materials phenomena are manifestations of processes that are operative over a vast range of length and time scales. A complete understanding of the behaviour of materials thereby requires theoretical and computational tools that span the atomic-scale detail of first-principles methods and the more coarse-grained description provided by continuum equations. Recent efforts have focused on combining traditional methodologies-density functional theory, molecular dynamics, Monte Carlo methods and continuum descriptions-within a unified multiscale framework. This review covers the techniques that have been developed to model various aspects of materials behaviour with the ultimate aim of systematically coupling the atomistic to the continuum descriptions. The approaches described typically have been motivated by particular applications but can often be applied in wider contexts. The self-assembly of quantum dot ensembles will be used as a case study for the issues that arise and the methods used for all nanostructures. Although quantum dots can be obtained with all the standard growth methods and for a variety of material systems, their appearance is a quite selective process, involving the competition between equilibrium and kinetic effects, and the interplay between atomistic and long-range interactions. Most theoretical models have addressed particular aspects of the ordering kinetics of quantum dot ensembles, with far fewer attempts at a comprehensive synthesis of this inherently multiscale phenomenon. We conclude with an assessment of the current status of multiscale modelling strategies and highlight the main outstanding issues. (topical review)
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 computing in the exascale era
Alowayyed, S.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.
We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing
Directory of Open Access Journals (Sweden)
Y. Tang
2017-12-01
Full Text Available This study applies the Gridpoint Statistical Interpolation (GSI 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP, to improve surface PM2.5 predictions over the contiguous United States (CONUS by assimilating aerosol optical depth (AOD and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ modeling system. An optimal interpolation (OI method implemented earlier (Tang et al., 2015 for the CMAQ modeling system is also tested for the same period (July 2011 over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE. It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.
Multiscale principal component analysis
International Nuclear Information System (INIS)
Akinduko, A A; Gorban, A N
2014-01-01
Principal component analysis (PCA) is an important tool in exploring data. The conventional approach to PCA leads to a solution which favours the structures with large variances. This is sensitive to outliers and could obfuscate interesting underlying structures. One of the equivalent definitions of PCA is that it seeks the subspaces that maximize the sum of squared pairwise distances between data projections. This definition opens up more flexibility in the analysis of principal components which is useful in enhancing PCA. In this paper we introduce scales into PCA by maximizing only the sum of pairwise distances between projections for pairs of datapoints with distances within a chosen interval of values [l,u]. The resulting principal component decompositions in Multiscale PCA depend on point (l,u) on the plane and for each point we define projectors onto principal components. Cluster analysis of these projectors reveals the structures in the data at various scales. Each structure is described by the eigenvectors at the medoid point of the cluster which represent the structure. We also use the distortion of projections as a criterion for choosing an appropriate scale especially for data with outliers. This method was tested on both artificial distribution of data and real data. For data with multiscale structures, the method was able to reveal the different structures of the data and also to reduce the effect of outliers in the principal component analysis
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.
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.
A multiscale model for virus capsid dynamics.
Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei
2010-01-01
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.
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.
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.;
2014-01-01
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 onboard 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 integration of -omic, imaging, and clinical data in biomedical informatics.
Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei
2012-01-01
This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.
Multiscale scenarios for nature futures
CSIR Research Space (South Africa)
Rosa, IMD
2017-09-01
Full Text Available & Evolution, vol. 1: 1416-1419 Multiscale scenarios for nature futures Rosa IMD Pereira HM Ferrier S Alkemade R Acosta LA Akcakaya HR den Belder E Fazel AM Fujimori S Sitas NE ABSTRACT: Targets for human development are increasingly...
Multiscale mechanics of dynamical metamaterials
Geers, M.G.D.; Kouznetsova, V.; Sridhar, A.; Krushynska, A.; Kleiber, M.; Burczynski, T.; Wilde, K.; Gorski, J.; Winkelmann, K.; Smakosz, L.
2016-01-01
This contribution focuses on the computational multi-scale solution of wave propagation phenomena in dynamic metamaterials. Taking the Bloch-Floquet solution for the standard elastic case as a point of departure, an extended scheme is presented to solve for heterogeneous visco-elastic materials. The
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 THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
T. Buscheck
2005-01-01
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
The Magnetospheric Multiscale Mission
Burch, James
Magnetospheric Multiscale (MMS), a NASA four-spacecraft mission scheduled for launch in November 2014, 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. Among the important questions about reconnection that will be addressed are the following: Under what conditions can magnetic-field energy be converted to plasma energy by the annihilation of magnetic field through reconnection? How does reconnection vary with time, and what factors influence its temporal behavior? What microscale processes are responsible for reconnection? What determines the rate of reconnection? In order to accomplish its goals the MMS spacecraft must probe both those regions in which the magnetic fields are very nearly antiparallel and regions where a significant guide field exists. From previous missions we know the approximate speeds with which reconnection layers move through space to be from tens to hundreds of km/s. For electron skin depths of 5 to 10 km, the full 3D electron population (10 eV to above 20 keV) has to be sampled at rates greater than 10/s. The MMS Fast-Plasma Instrument (FPI) will sample electrons at greater than 30/s. Because the ion skin depth is larger, FPI will make full ion measurements at rates of greater than 6/s. 3D E-field measurements will be made by MMS once every ms. MMS will use an Active Spacecraft Potential Control device (ASPOC), which emits indium ions to neutralize the photoelectron current and keep the spacecraft from charging to more than +4 V. Because ion dynamics in Hall reconnection depend sensitively on ion mass, MMS includes a new-generation Hot Plasma Composition Analyzer (HPCA) that corrects problems with high proton fluxes that have prevented accurate ion-composition measurements near the dayside magnetospheric boundary. Finally, Energetic Particle Detector (EPD) measurements of electrons and
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
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.
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Multiscale Simulation of Breaking Wave Impacts
DEFF Research Database (Denmark)
Lindberg, Ole
compare reasonably well. The incompressible and inviscid ALE-WLS model is coupled with the potential flow model of Engsig-Karup et al. [2009], to perform multiscale calculation of breaking wave impacts on a vertical breakwater. The potential flow model provides accurate calculation of the wave...... with a potential flow model to provide multiscale calculation of forces from breaking wave impacts on structures....
Multivariate refined composite multiscale entropy analysis
International Nuclear Information System (INIS)
Humeau-Heurtier, Anne
2016-01-01
Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.
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.
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.
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
Grauer, Kit, Ed.
1995-01-01
Art in context of community is the theme of this newsletter. The theme is introduced in an editorial "Community-Enlarging the Definition" (Kit Grauer). Related articles include: (1) "The Children's Bridge is not Destroyed: Heart in the Middle of the World" (Emil Robert Tanay); (2) "Making Bridges: The Sock Doll…
Multi-scale graph-cut algorithm for efficient water-fat separation.
Berglund, Johan; Skorpil, Mikael
2017-09-01
To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Multiscale modelling for tokamak pedestals
Abel, I. G.
2018-04-01
Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a first-principles multiscale approach to the pedestal. We will present three separate sets of equations, covering the dynamics of edge localised modes (ELMs), the inter-ELM pedestal and pedestal turbulence, respectively. Precisely how these equations should be coupled to each other is covered in detail. This framework is completely self-consistent; it is derived from first principles by means of an asymptotic expansion of the fundamental Vlasov-Landau-Maxwell system in appropriate small parameters. The derivation exploits the narrowness of the pedestal region, the smallness of the thermal gyroradius and the low plasma (the ratio of thermal to magnetic pressures) typical of current pedestal operation to achieve its simplifications. The relationship between this framework and gyrokinetics is analysed, and possibilities to directly match our systems of equations onto multiscale gyrokinetics are explored. A detailed comparison between our model and other models in the literature is performed. Finally, the potential for matching this framework onto an open-field-line region is briefly discussed.
Multifunctional multiscale composites: Processing, modeling and characterization
Qiu, Jingjing
Carbon nanotubes (CNTs) demonstrate extraordinary properties and show great promise in enhancing out-of-plane properties of traditional polymer/fiber composites and enabling functionality. However, current manufacturing challenges hinder the realization of their potential. In the dissertation research, both experimental and computational efforts have been conducted to investigate effective manufacturing techniques of CNT integrated multiscale composites. The fabricated composites demonstrated significant improvements in physical properties, such as tensile strength, tensile modulus, inter-laminar shear strength, thermal dimension stability and electrical conductivity. Such multiscale composites were truly multifunctional with the addition of CNTs. Furthermore, a novel hierarchical multiscale modeling method was developed in this research. Molecular dynamic (MD) simulation offered reasonable explanation of CNTs dispersion and their motion in polymer solution. Bi-mode finite-extensible-nonlinear-elastic (FENE) dumbbell simulation was used to analyze the influence of CNT length distribution on the stress tensor and shear-rate-dependent viscosity. Based on the simulated viscosity profile and empirical equations from experiments, a macroscale flow simulation model on the finite element method (FEM) method was developed and validated to predict resin flow behavior in the processing of CNT-enhanced multiscale composites. The proposed multiscale modeling method provided a comprehensive understanding of micro/nano flow in both atomistic details and mesoscale. The simulation model can be used to optimize process design and control of the mold-filling process in multiscale composite manufacturing. This research provided systematic investigations into the CNT-based multiscale composites. The results from this study may be used to leverage the benefits of CNTs and open up new application opportunities for high-performance multifunctional multiscale composites. Keywords. Carbon
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 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. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Foundations for a multiscale collaborative Earth model
Afanasiev, M.; Peter, Daniel; Sager, K.; Simut, S.; Ermert, L.; Krischer, L.; Fichtner, A.
2015-01-01
. 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
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 Modeling of Wear Degradation
Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2016-01-01
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; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2015-01-01
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.
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.
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...
Multiphysics/multiscale multifluid computations
International Nuclear Information System (INIS)
Yadigaroglu, George
2014-01-01
Regarding experimentation, interesting examples of multi-scale approaches are found: the small-scale experiments to understand the mechanisms of counter-current flow limitations (CCFL) such as the growth of instabilities on films, droplet entrainment, etc; meso-scale experiments to quantify the CCFL conditions in typical geometries such as tubes and gaps between parallel plates, and finally full-scale experimentation in a typical reactor geometry - the UPTF tests. Another example is the mixing of the atmosphere produced by plumes and jets in a reactor containment: one needs first basic turbulence information that can be obtained at the microscopic level; follow medium-scale experiments to understand the behaviour of jets and plumes; finally reactor-scale tests can be conducted in facilities such as PANDA at PSI, in Switzerland to study the phenomena at large scale
Multiscale modelling of DNA mechanics
International Nuclear Information System (INIS)
Dršata, Tomáš; Lankaš, Filip
2015-01-01
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. (topical review)
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.
Integrated multi-scale modelling and simulation of nuclear fuels
International Nuclear Information System (INIS)
Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.
2015-01-01
This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)
A concurrent multiscale micromorphic molecular dynamics
International Nuclear Information System (INIS)
Li, Shaofan; Tong, Qi
2015-01-01
In this work, we have derived a multiscale micromorphic molecular dynamics (MMMD) from first principle to extend the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and continuum scale. The multiscale micromorphic molecular dynamics is a con-current three-scale dynamics that couples a fine scale molecular dynamics, a mesoscale micromorphic dynamics, and a macroscale nonlocal particle dynamics together. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics is the homogeneous and equilibrium case of the proposed multiscale micromorphic molecular dynamics. In specific, we have shown that the Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and its general inhomogeneous case, i.e., the three scale con-current multiscale micromorphic molecular dynamics can take into account of macroscale continuum mechanics boundary condition without the limitation of atomistic boundary condition or periodic boundary conditions. The discovered multiscale scale structure and the corresponding multiscale dynamics reveal a seamless transition from atomistic scale to continuum scale and the intrinsic coupling mechanism among them based on first principle formulation
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
Efendiev, Yalchin R.; Presho, Michael
2015-01-01
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.
Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment
Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D.; Coveney, P.V.; Hoekstra, A.G.
2014-01-01
We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and
Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.
2012-01-01
Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale
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.
State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels
International Nuclear Information System (INIS)
Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka
2015-10-01
The Nuclear Science Committee (NSC) of the Nuclear Energy Agency (NEA) has undertaken an ambitious programme to document state-of-the-art of modelling for nuclear fuels and structural materials. The project is being performed under the Working Party on Multi-Scale Modelling of Fuels and Structural Material for Nuclear Systems (WPMM), which has been established to assess the scientific and engineering aspects of fuels and structural materials, describing multi-scale models and simulations as validated predictive tools for the design of nuclear systems, fuel fabrication and performance. The WPMM's objective is to promote the exchange of information on models and simulations of nuclear materials, theoretical and computational methods, experimental validation and related topics. It also provides member countries with up-to-date information, shared data, models, and expertise. The goal is also to assess needs for improvement and address them by initiating joint efforts. The WPMM reviews and evaluates multi-scale modelling and simulation techniques currently employed in the selection of materials used in nuclear systems. It serves to provide advice to the nuclear community on the developments needed to meet the requirements of modelling for the design of different nuclear systems. The original WPMM mandate had three components (Figure 1), with the first component currently completed, delivering a report on the state-of-the-art of modelling of structural materials. The work on modelling was performed by three expert groups, one each on Multi-Scale Modelling Methods (M3), Multi-Scale Modelling of Fuels (M2F) and Structural Materials Modelling (SMM). WPMM is now composed of three expert groups and two task forces providing contributions on multi-scale methods, modelling of fuels and modelling of structural materials. This structure will be retained, with the addition of task forces as new topics are developed. The mandate of the Expert Group on Multi-Scale Modelling of
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.
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 mod...
Multiscale study of metal nanoparticles
Lee, Byeongchan
Extremely small structures with reduced dimensionality have emerged as a scientific motif for their interesting properties. In particular, metal nanoparticles have been identified as a fundamental material in many catalytic activities; as a consequence, a better understanding of structure-function relationship of nanoparticles has become crucial. The functional analysis of nanoparticles, reactivity for example, requires an accurate method at the electronic structure level, whereas the structural analysis to find energetically stable local minima is beyond the scope of quantum mechanical methods as the computational cost becomes prohibitingly high. The challenge is that the inherent length scale and accuracy associated with any single method hardly covers the broad scale range spanned by both structural and functional analyses. In order to address this, and effectively explore the energetics and reactivity of metal nanoparticles, a hierarchical multiscale modeling is developed, where methodologies of different length scales, i.e. first principles density functional theory, atomistic calculations, and continuum modeling, are utilized in a sequential fashion. This work has focused on identifying the essential information that bridges two different methods so that a successive use of different methods is seamless. The bond characteristics of low coordination systems have been obtained with first principles calculations, and incorporated into the atomistic simulation. This also rectifies the deficiency of conventional interatomic potentials fitted to bulk properties, and improves the accuracy of atomistic calculations for nanoparticles. For the systematic shape selection of nanoparticles, we have improved the Wulff-type construction using a semi-continuum approach, in which atomistic surface energetics and crystallinity of materials are added on to the continuum framework. The developed multiscale modeling scheme is applied to the rational design of platinum
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 Processes in Magnetic Reconnection
Surjalal Sharma, A.; Jain, Neeraj
The characteristic scales of the plasma processes in magnetic reconnection range from the elec-tron skin-depth to the magnetohydrodynamic (MHD) scale, and cross-scale coupling among them play a key role. Modeling these processes requires different physical models, viz. kinetic, electron-magnetohydrodynamics (EMHD), Hall-MHD, and MHD. The shortest scale processes are at the electron scale and these are modeled using an EMHD code, which provides many features of the multiscale behavior. In simulations using initial conditions consisting of pertur-bations with many scale sizes the reconnection takes place at many sites and the plasma flows from these interact with each other. This leads to thin current sheets with length less than 10 electron skin depths. The plasma flows also generate current sheets with multiple peaks, as observed by Cluster. The quadrupole structure of the magnetic field during reconnection starts on the electron scale and the interaction of inflow to the secondary sites and outflow from the dominant site generates a nested structure. In the outflow regions, the interaction of the electron outflows generated at the neighboring sites lead to the development of electron vortices. A signature of the nested structure of the Hall field is seen in Cluster observations, and more details of these features are expected from MMS.
Multiscale reconstruction for MR fingerprinting.
Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A
2016-06-01
To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Macrosystems ecology: novel methods and new understanding of multi-scale patterns and processes
Songlin Fei; Qinfeng Guo; Kevin Potter
2016-01-01
As the global biomes are increasinglyÂ threatened by human activities, understanding ofÂ macroscale patterns and processes is pressinglyÂ needed for effective management and policy making.Â Macrosystems ecology, which studies multiscale ecologicalpatterns and processes, has gained growingÂ interest in the research community. However, as aÂ relatively new field in...
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...
Hybrid numerical methods for multiscale simulations of subsurface biogeochemical processes
International Nuclear Information System (INIS)
Scheibe, T D; Tartakovsky, A M; Tartakovsky, D M; Redden, G D; Meakin, P
2007-01-01
Many subsurface flow and transport problems of importance today involve coupled non-linear flow, transport, and reaction in media exhibiting complex heterogeneity. In particular, problems involving biological mediation of reactions fall into this class of problems. Recent experimental research has revealed important details about the physical, chemical, and biological mechanisms involved in these processes at a variety of scales ranging from molecular to laboratory scales. However, it has not been practical or possible to translate detailed knowledge at small scales into reliable predictions of field-scale phenomena important for environmental management applications. A large assortment of numerical simulation tools have been developed, each with its own characteristic scale. Important examples include 1. molecular simulations (e.g., molecular dynamics); 2. simulation of microbial processes at the cell level (e.g., cellular automata or particle individual-based models); 3. pore-scale simulations (e.g., lattice-Boltzmann, pore network models, and discrete particle methods such as smoothed particle hydrodynamics); and 4. macroscopic continuum-scale simulations (e.g., traditional partial differential equations solved by finite difference or finite element methods). While many problems can be effectively addressed by one of these models at a single scale, some problems may require explicit integration of models across multiple scales. We are developing a hybrid multi-scale subsurface reactive transport modeling framework that integrates models with diverse representations of physics, chemistry and biology at different scales (sub-pore, pore and continuum). The modeling framework is being designed to take advantage of advanced computational technologies including parallel code components using the Common Component Architecture, parallel solvers, gridding, data and workflow management, and visualization. This paper describes the specific methods/codes being used at each
Deductive multiscale simulation using order parameters
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 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.
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.
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.
MULTISCALE SPARSE APPEARANCE MODELING AND SIMULATION OF PATHOLOGICAL DEFORMATIONS
Directory of Open Access Journals (Sweden)
Rami Zewail
2017-08-01
Full Text Available Machine learning and statistical modeling techniques has drawn much interest within the medical imaging research community. However, clinically-relevant modeling of anatomical structures continues to be a challenging task. This paper presents a novel method for multiscale sparse appearance modeling in medical images with application to simulation of pathological deformations in X-ray images of human spine. The proposed appearance model benefits from the non-linear approximation power of Contourlets and its ability to capture higher order singularities to achieve a sparse representation while preserving the accuracy of the statistical model. Independent Component Analysis is used to extract statistical independent modes of variations from the sparse Contourlet-based domain. The new model is then used to simulate clinically-relevant pathological deformations in radiographic images.
A multiscale approach to mutual information matching
Pluim, J.P.W.; Maintz, J.B.A.; Viergever, M.A.; Hanson, K.M.
1998-01-01
Methods based on mutual information have shown promising results for matching of multimodal brain images. This paper discusses a multiscale approach to mutual information matching, aiming for an acceleration of the matching process while considering the accuracy and robustness of the method. Scaling
Multiscale Lyapunov exponent for 2-microlocal functions
International Nuclear Information System (INIS)
Dhifaoui, Zouhaier; Kortas, Hedi; Ammou, Samir Ben
2009-01-01
The Lyapunov exponent is an important indicator of chaotic dynamics. Using wavelet analysis, we define a multiscale representation of this exponent which we demonstrate the scale-wise dependence for functions belonging to C x 0 s,s ' spaces. An empirical study involving simulated processes and financial time series corroborates the theoretical findings.
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 Phase Inversion of Seismic Data
Fu, Lei; Guo, Bowen; Sun, Yonghe; Schuster, Gerard T.
2017-01-01
-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
Multiscale Modeling of Poromechanics in Geologic Media
Castelletto, N.; Hajibeygi, H.; Klevtsov, S.; Tchelepi, H.
2017-12-01
We describe a hybrid MultiScale Finite Element-Finite Volume (h-MSFE-FV) framework for the simulation of single-phase Darcy flow through deformable porous media that exhibit highly heterogeneous poromechanical properties over a wide range of length scales. In such systems, high resolution characterizations are a key requirement to obtain reliable modeling predictions and motivate the development of multiscale solution strategies to cope with the computational burden. A coupled two-field fine-scale mixed FE-FV discretization of the governing equations, namely conservation laws of linear momentum and mass, is first implemented based on a displacement-pressure formulation. After imposing a coarse-scale grid on the given fine-scale problem, for the MSFE displacement stage, the coarse-scale basis functions are obtained by solving local equilibrium problems within coarse elements. Such MSFE stage is then coupled with the MSFV method for flow, in which a dual-coarse grid is introduced to obtain approximate but conservative multiscale solutions. Robustness and accuracy of the proposed multiscale framework is demonstrated using a variety of challenging test problems.
Multiscale empirical interpolation for solving nonlinear PDEs
Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Ghommem, Mehdi
2014-01-01
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
Multiscale information modelling for heart morphogenesis
Energy Technology Data Exchange (ETDEWEB)
Abdulla, T; Imms, R; Summers, R [Department of Electronic and Electrical Engineering, Loughborough University, Loughborough (United Kingdom); Schleich, J M, E-mail: T.Abdulla@lboro.ac.u [LTSI Signal and Image Processing Laboratory, University of Rennes 1, Rennes (France)
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 information modelling for heart morphogenesis
International Nuclear Information System (INIS)
Abdulla, T; Imms, R; Summers, R; Schleich, J M
2010-01-01
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 approach to equilibrating model polymer melts
DEFF Research Database (Denmark)
Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils
2016-01-01
We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...
Multiscale optimization of saturated poroelastic actuators
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe; Sigmund, Ole
A multiscale method for optimizing the material micro structure in a macroscopically heterogeneous saturated poroelastic media with respect to macro properties is presented. The method is based on topology optimization using the homogenization technique, here applied to the optimization of a bi...
Generalized multiscale finite element methods: Oversampling strategies
Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael
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
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.
Energy Technology Data Exchange (ETDEWEB)
Hulle, M
2007-07-01
The primary objective of this project is to investigate the effects of global change on the biodiversity of aphid communities in Western Europe. Biodiversity has been examined at 3 levels: total number of species, phenology and reproductive strategy. Data were provided by EXAMINE, the European suction traps network which has been now operating for 35 years. 392 different species have been identified. At each location, total number of species has been regularly increasing, one additional species being caught every 1 or 2 years depending on location. This is due to introduced species but also to warming which favours rare species. No general trend of increasing density has been detected, but phenological earliness of almost all species (annual date of first appearance in suction traps) is strongly correlated with temperature and especially with mean daily temperature (during more or less long periods of time lying principally in February and March) or number of days below 0 C. Strong relationships between aphid phenology and environmental variables have been found and there is strong discrimination between species with different life cycle strategies, and between species feeding on herbs and trees, suggesting the possible value of trait-based groupings in predicting responses to environmental changes. These preliminary results suggest that 1) biodiversity has increased during the last decades; 2) there is a pool of species among which some of them reach a detectable density only during years where temperatures are high enough; 3) a set of newly introduced species succeed in settling being favoured by warming and 4) phenology of aphids is expected to advance and their abundance to increase with temperature, and the possible role of natural enemies to regulate abundant species is discussed. (author)
Multiscale Polymer Composites: A Review of the Interlaminar Fracture Toughness Improvement
Directory of Open Access Journals (Sweden)
Vishwesh Dikshit
2017-10-01
Full Text Available Composite materials are prone to delamination as they are weaker in the thickness direction. Carbon nanotubes (CNTs are introduced as a multiscale reinforcement into the fiber reinforced polymer composites to suppress the delamination phenomenon. This review paper presents the detailed progress made by the scientific and research community to-date in improving the Mode I and Mode II interlaminar fracture toughness (ILFT by various methodologies including the effect of multiscale reinforcement. Methods of measuring the Mode I and Mode II fracture toughness of the composites along with the solutions to improve them are presented. The use of different methodologies and approaches along with their performance in enhancing the fracture toughness of the composites is summarized. The current state of polymer-fiber-nanotube composites and their future perspective are also deliberated.
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.
International Nuclear Information System (INIS)
Shadid, John Nicolas; Lehoucq, Richard B.; Christon, Mark Allen; Slepoy, Alexander; Bochev, Pavel Blagoveston; Collis, Samuel Scott; Wagner, Gregory John
2004-01-01
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.
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.
Chung, Eric; Efendiev, Yalchin R.; Leung, Wing; Ren, Jun
2015-01-01
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.
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.
Residual-driven online generalized multiscale finite element methods
Chung, Eric T.; Efendiev, Yalchin R.; Leung, Wing Tat
2015-01-01
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.
Multiscale Modeling of Point and Line Defects in Cubic Lattices
National Research Council Canada - National Science Library
Chung, P. W; Clayton, J. D
2007-01-01
.... This multiscale theory explicitly captures heterogeneity in microscopic atomic motion in crystalline materials, attributed, for example, to the presence of various point and line lattice defects...
Towards practical multiscale approach for analysis of reinforced concrete structures
Moyeda, Arturo; Fish, Jacob
2017-12-01
We present a novel multiscale approach for analysis of reinforced concrete structural elements that overcomes two major hurdles in utilization of multiscale technologies in practice: (1) coupling between material and structural scales due to consideration of large representative volume elements (RVE), and (2) computational complexity of solving complex nonlinear multiscale problems. The former is accomplished using a variant of computational continua framework that accounts for sizeable reinforced concrete RVEs by adjusting the location of quadrature points. The latter is accomplished by means of reduced order homogenization customized for structural elements. The proposed multiscale approach has been verified against direct numerical simulations and validated against experimental results.
Multiscale Cues Drive Collective Cell Migration
Nam, Ki-Hwan; Kim, Peter; Wood, David K.; Kwon, Sunghoon; Provenzano, Paolo P.; Kim, Deok-Ho
2016-07-01
To investigate complex biophysical relationships driving directed cell migration, we developed a biomimetic platform that allows perturbation of microscale geometric constraints with concomitant nanoscale contact guidance architectures. This permits us to elucidate the influence, and parse out the relative contribution, of multiscale features, and define how these physical inputs are jointly processed with oncogenic signaling. We demonstrate that collective cell migration is profoundly enhanced by the addition of contract guidance cues when not otherwise constrained. However, while nanoscale cues promoted migration in all cases, microscale directed migration cues are dominant as the geometric constraint narrows, a behavior that is well explained by stochastic diffusion anisotropy modeling. Further, oncogene activation (i.e. mutant PIK3CA) resulted in profoundly increased migration where extracellular multiscale directed migration cues and intrinsic signaling synergistically conspire to greatly outperform normal cells or any extracellular guidance cues in isolation.
Multiscale Study of Currents Affected by Topography
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Multiscale Study of Currents Affected by Topography ...the effects of topography on the ocean general and regional circulation with a focus on the wide range of scales of interactions. The small-scale...details of the topography and the waves, eddies, drag, and turbulence it generates (at spatial scales ranging from meters to mesoscale) interact in the
A multiscale approach to Brownian motors
International Nuclear Information System (INIS)
Pavliotis, G.A.
2005-01-01
The problem of Brownian motion in a periodic potential, under the influence of external forcing, which is either random or periodic in time, is studied in this Letter. Multiscale techniques are used to derive general formulae for the steady state particle current and the effective diffusion tensor. These formulae are then applied to calculate the effective diffusion coefficient for a Brownian particle in a periodic potential driven simultaneously by additive Gaussian white and colored noise. Our theoretical findings are supported by numerical simulations
Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut
Multiscale modeling of mucosal immune responses.
Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep
2015-01-01
Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T
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......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....
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®
Adaptive multiscale processing for contrast enhancement
Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.
1993-07-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.
Acoustics of multiscale sorptive porous materials
Venegas, R.; Boutin, C.; Umnova, O.
2017-08-01
This paper investigates sound propagation in multiscale rigid-frame porous materials that support mass transfer processes, such as sorption and different types of diffusion, in addition to the usual visco-thermo-inertial interactions. The two-scale asymptotic method of homogenization for periodic media is successively used to derive the macroscopic equations describing sound propagation through the material. This allowed us to conclude that the macroscopic mass balance is significantly modified by sorption, inter-scale (micro- to/from nanopore scales) mass diffusion, and inter-scale (pore to/from micro- and nanopore scales) pressure diffusion. This modification is accounted for by the dynamic compressibility of the effective saturating fluid that presents atypical properties that lead to slower speed of sound and higher sound attenuation, particularly at low frequencies. In contrast, it is shown that the physical processes occurring at the micro-nano-scale do not affect the macroscopic fluid flow through the material. The developed theory is exemplified by introducing an analytical model for multiscale sorptive granular materials, which is experimentally validated by comparing its predictions with acoustic measurements on granular activated carbons. Furthermore, we provide empirical evidence supporting an alternative method for measuring sorption and mass diffusion properties of multiscale sorptive materials using sound waves.
Multivariate multiscale entropy of financial markets
Lu, Yunfan; Wang, Jun
2017-11-01
In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.
Multiscale Phase Inversion of Seismic Data
Fu, Lei
2017-12-02
We present a scheme for multiscale phase inversion (MPI) of seismic data that is less sensitive to the unmodeled physics of wave propagation and a poor starting model than standard full waveform inversion (FWI). 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. The input data are also filtered into different narrow frequency bands for the MPI implementation. At low frequencies, we show that MPI with windowed reflections approximates wave equation inversion of the reflection traveltimes, except no traveltime picking is needed. Numerical results with synthetic acoustic data show that MPI is more robust than conventional multiscale FWI when the initial model is far from the true model. Results from synthetic viscoacoustic and elastic data show that MPI is less sensitive than FWI to some of the unmodeled physics. Inversion of marine data shows that MPI is more robust and produces modestly more accurate results than FWI for this data set.
Multiscale Persistent Functions for Biomolecular Structure Characterization
Energy Technology Data Exchange (ETDEWEB)
Xia, Kelin [Nanyang Technological University (Singapore). Division of Mathematical Sciences, School of Physical, Mathematical Sciences and School of Biological Sciences; Li, Zhiming [Central China Normal University, Wuhan (China). Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics; Mu, Lin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division
2017-11-02
Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first
Multiscale methods in computational fluid and solid mechanics
Borst, de R.; Hulshoff, S.J.; Lenz, S.; Munts, E.A.; Brummelen, van E.H.; Wall, W.; Wesseling, P.; Onate, E.; Periaux, J.
2006-01-01
First, an attempt is made towards gaining a more systematic understanding of recent progress in multiscale modelling in computational solid and fluid mechanics. Sub- sequently, the discussion is focused on variational multiscale methods for the compressible and incompressible Navier-Stokes
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…
Efficient algorithms for multiscale modeling in porous media
Wheeler, Mary F.; Wildey, Tim; Xue, Guangri
2010-01-01
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.
A complete categorization of multiscale models of infectious disease systems.
Garira, Winston
2017-12-01
Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.
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.
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.
Multiscale agent-based cancer modeling.
Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S
2009-04-01
Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.
Multi-scale Modelling of Segmentation
DEFF Research Database (Denmark)
Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri
2016-01-01
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......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...
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.
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.
Neural network based multiscale image restoration approach
de Castro, Ana Paula A.; da Silva, José D. S.
2007-02-01
This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.
Multiscale coherent structures in tokamak plasma turbulence
International Nuclear Information System (INIS)
Xu, G. S.; Wan, B. N.; Zhang, W.; Yang, Q. W.; Wang, L.; Wen, Y. Z.
2006-01-01
A 12-tip poloidal probe array is used on the HT-7 superconducting tokamak [Li, Wan, and Mao, Plasma Phys. Controlled Fusion 42, 135 (2000)] to measure plasma turbulence in the edge region. Some statistical analysis techniques are used to characterize the turbulence structures. It is found that the plasma turbulence is composed of multiscale coherent structures, i.e., turbulent eddies and there is self-similarity in a relative short scale range. The presence of the self-similarity is found due to the structural similarity of these eddies between different scales. These turbulent eddies constitute the basic convection cells, so the self-similar range is just the dominant scale range relevant to transport. The experimental results also indicate that the plasma turbulence is dominated by low-frequency and long-wavelength fluctuation components and its dispersion relation shows typical electron-drift-wave characteristics. Some large-scale coherent structures intermittently burst out and exhibit a very long poloidal extent, even longer than 6 cm. It is found that these large-scale coherent structures are mainly contributed by the low-frequency and long-wavelength fluctuating components and their presence is responsible for the observations of long-range correlations, i.e., the correlation in the scale range much longer than the turbulence decorrelation scale. These experimental observations suggest that the coexistence of multiscale coherent structures results in the self-similar turbulent state
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.
Multi-scale biomedical systems: measurement challenges
International Nuclear Information System (INIS)
Summers, R
2016-01-01
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. (paper)
Mammographic feature enhancement by multiscale analysis
International Nuclear Information System (INIS)
Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.
1994-01-01
This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients
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.
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.
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.
Analysis of complex time series using refined composite multiscale entropy
International Nuclear Information System (INIS)
Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang
2014-01-01
Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.
Multi-Scale Scattering Transform in Music Similarity Measuring
Wang, Ruobai
Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.
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.
Multi-scale salient feature extraction on mesh models
Yang, Yongliang; Shen, ChaoHui
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.
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
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
RBF Multiscale Collocation for Second Order Elliptic Boundary Value Problems
Farrell, Patricio; Wendland, Holger
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
A multiscale mortar multipoint flux mixed finite element method
Wheeler, Mary Fanett; Xue, Guangri; Yotov, Ivan
2012-01-01
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
Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction
Ghasemi, Mohammadreza; Yang, Yanfang; Gildin, Eduardo; Efendiev, Yalchin R.; Calo, Victor M.
2015-01-01
snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3
Multi-Scale Simulation of High Energy Density Ionic Liquids
National Research Council Canada - National Science Library
Voth, Gregory A
2007-01-01
The focus of this AFOSR project was the molecular dynamics (MD) simulation of ionic liquid structure, dynamics, and interfacial properties, as well as multi-scale descriptions of these novel liquids (e.g...
Multi-scale modeling strategies in materials science—The ...
Indian Academy of Sciences (India)
Unknown
Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.; Krauss, T. F.; Fratalocchi, Andrea
2012-01-01
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
Randomized Oversampling for Generalized Multiscale Finite Element Methods
Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian
2016-01-01
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
Toward the multiscale nature of stress corrosion cracking
Directory of Open Access Journals (Sweden)
Xiaolong Liu
2018-02-01
Full Text Available This article reviews the multiscale nature of stress corrosion cracking (SCC observed by high-resolution characterizations in austenite stainless steels and Ni-base superalloys in light water reactors (including boiling water reactors, pressurized water reactors, and supercritical water reactors with related opinions. A new statistical summary and comparison of observed degradation phenomena at different length scales is included. The intrinsic causes of this multiscale nature of SCC are discussed based on existing evidence and related opinions, ranging from materials theory to practical processing technologies. Questions of interest are then discussed to improve bottom-up understanding of the intrinsic causes. Last, a multiscale modeling and simulation methodology is proposed as a promising interdisciplinary solution to understand the intrinsic causes of the multiscale nature of SCC in light water reactors, based on a review of related supporting application evidence.
Multiscale model reduction for shale gas transport in fractured media
Akkutlu, I. Y.; Efendiev, Yalchin R.; Vasilyeva, Maria
2016-01-01
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
Distributed Multiscale Data Analysis and Processing for Sensor Networks
National Research Council Canada - National Science Library
Wagner, Raymond; Sarvotham, Shriram; Choi, Hyeokho; Baraniuk, Richard
2005-01-01
.... Second, the communication overhead of multiscale algorithms can become prohibitive. In this paper, we take a first step in addressing both shortcomings by introducing two new distributed multiresolution transforms...
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...
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.
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.
An approach to multiscale modelling with graph grammars.
Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried
2014-09-01
Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.
Long-term Stable Conservative Multiscale Methods for Vortex Flows
2017-10-31
Computing Department, Florida State (January 2016) - L. Rebholz, SIAM Southeast 2016, Special session on Recent advances in fluid flow and...Multiscale Methods for Vortex Flows (x) Material has been given an OPSEC review and it has been determined to be non sensitive and, except for...distribution is unlimited. UU UU UU UU 31-10-2017 1-Aug-2014 31-Jul-2017 Final Report: Long-term Stable Conservative Multiscale Methods for Vortex Flows
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....
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.
Multi-scale modeling of composites
DEFF Research Database (Denmark)
Azizi, Reza
A general method to obtain the homogenized response of metal-matrix composites is developed. It is assumed that the microscopic scale is sufficiently small compared to the macroscopic scale such that the macro response does not affect the micromechanical model. Therefore, the microscopic scale......-Mandel’s energy principle is used to find macroscopic operators based on micro-mechanical analyses using the finite element method under generalized plane strain condition. A phenomenologically macroscopic model for metal matrix composites is developed based on constitutive operators describing the elastic...... to plastic deformation. The macroscopic operators found, can be used to model metal matrix composites on the macroscopic scale using a hierarchical multi-scale approach. Finally, decohesion under tension and shear loading is studied using a cohesive law for the interface between matrix and fiber....
Quantifying multiscale inefficiency in electricity markets
Energy Technology Data Exchange (ETDEWEB)
Uritskaya, Olga Y. [Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, and Department of Economics and Management, St. Petersburg Polytechnic University, St. Petersburg (Russian Federation); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)
2008-11-15
One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)
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.
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.
Quantifying multiscale inefficiency in electricity markets
International Nuclear Information System (INIS)
Uritskaya, Olga Y.; Serletis, Apostolos
2008-01-01
One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)
Multiscale modeling of three-dimensional genome
Zhang, Bin; Wolynes, Peter
The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.
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.
Hybrid stochastic simplifications for multiscale gene networks
Directory of Open Access Journals (Sweden)
Debussche Arnaud
2009-09-01
Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.
MULTISCALE DYNAMICS OF SOLAR MAGNETIC STRUCTURES
International Nuclear Information System (INIS)
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.
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 sampling model for motion integration.
Sherbakov, Lena; Yazdanbakhsh, Arash
2013-09-30
Biologically plausible strategies for visual scene integration across spatial and temporal domains continues to be a challenging topic. The fundamental question we address is whether classical problems in motion integration, such as the aperture problem, can be solved in a model that samples the visual scene at multiple spatial and temporal scales in parallel. We hypothesize that fast interareal connections that allow feedback of information between cortical layers are the key processes that disambiguate motion direction. We developed a neural model showing how the aperture problem can be solved using different spatial sampling scales between LGN, V1 layer 4, V1 layer 6, and area MT. Our results suggest that multiscale sampling, rather than feedback explicitly, is the key process that gives rise to end-stopped cells in V1 and enables area MT to solve the aperture problem without the need for calculating intersecting constraints or crafting intricate patterns of spatiotemporal receptive fields. Furthermore, the model explains why end-stopped cells no longer emerge in the absence of V1 layer 6 activity (Bolz & Gilbert, 1986), why V1 layer 4 cells are significantly more end-stopped than V1 layer 6 cells (Pack, Livingstone, Duffy, & Born, 2003), and how it is possible to have a solution to the aperture problem in area MT with no solution in V1 in the presence of driving feedback. In summary, while much research in the field focuses on how a laminar architecture can give rise to complicated spatiotemporal receptive fields to solve problems in the motion domain, we show that one can reframe motion integration as an emergent property of multiscale sampling achieved concurrently within lamina and across multiple visual areas.
Parallel multiscale simulations of a brain aneurysm
International Nuclear Information System (INIS)
Grinberg, Leopold; Fedosov, Dmitry A.; Karniadakis, George Em
2013-01-01
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
Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media
Jiang, L.; Copeland, D.; Moulton, J. D.
2012-01-01
We develop a family of expanded mixed multiscale finite element methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed multiscale finite element formulation in the sense that four
Multi-scale approximation of Vlasov equation
International Nuclear Information System (INIS)
Mouton, A.
2009-09-01
One of the most important difficulties of numerical simulation of magnetized plasmas is the existence of multiple time and space scales, which can be very different. In order to produce good simulations of these multi-scale phenomena, it is recommended to develop some models and numerical methods which are adapted to these problems. Nowadays, the two-scale convergence theory introduced by G. Nguetseng and G. Allaire is one of the tools which can be used to rigorously derive multi-scale limits and to obtain new limit models which can be discretized with a usual numerical method: this procedure is so-called a two-scale numerical method. The purpose of this thesis is to develop a two-scale semi-Lagrangian method and to apply it on a gyrokinetic Vlasov-like model in order to simulate a plasma submitted to a large external magnetic field. However, the physical phenomena we have to simulate are quite complex and there are many questions without answers about the behaviour of a two-scale numerical method, especially when such a method is applied on a nonlinear model. In a first part, we develop a two-scale finite volume method and we apply it on the weakly compressible 1D isentropic Euler equations. Even if this mathematical context is far from a Vlasov-like model, it is a relatively simple framework in order to study the behaviour of a two-scale numerical method in front of a nonlinear model. In a second part, we develop a two-scale semi-Lagrangian method for the two-scale model developed by E. Frenod, F. Salvarani et E. Sonnendrucker in order to simulate axisymmetric charged particle beams. Even if the studied physical phenomena are quite different from magnetic fusion experiments, the mathematical context of the one-dimensional paraxial Vlasov-Poisson model is very simple for establishing the basis of a two-scale semi-Lagrangian method. In a third part, we use the two-scale convergence theory in order to improve M. Bostan's weak-* convergence results about the finite
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.
Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.
Chew, Yin Hoon; Wenden, Bénédicte; Flis, Anna; Mengin, Virginie; Taylor, Jasper; Davey, Christopher L; Tindal, Christopher; Thomas, Howard; Ougham, Helen J; de Reffye, Philippe; Stitt, Mark; Williams, Mathew; Muetzelfeldt, Robert; Halliday, Karen J; Millar, Andrew J
2014-09-30
Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.
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 Mathematics for Biomass Conversion to Renewable Hydrogen
Energy Technology Data Exchange (ETDEWEB)
Plechac, Petr [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Mathematics; Univ. of Delaware, Newark, DE (United States). Dept. of Mathematics; Vlachos, Dionisios [Univ. of Delaware, Newark, DE (United States). Dept. of Chemical and Biomolecular Engineering; Katsoulakis, Markos [Univ. of Massachusetts, Amherst, MA (United States). Dept. of Mathematics
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.
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.
2D deblending using the multi-scale shaping scheme
Li, Qun; Ban, Xingan; Gong, Renbin; Li, Jinnuo; Ge, Qiang; Zu, Shaohuan
2018-01-01
Deblending can be posed as an inversion problem, which is ill-posed and requires constraint to obtain unique and stable solution. In blended record, signal is coherent, whereas interference is incoherent in some domains (e.g., common receiver domain and common offset domain). Due to the different sparsity, coefficients of signal and interference locate in different curvelet scale domains and have different amplitudes. Take into account the two differences, we propose a 2D multi-scale shaping scheme to constrain the sparsity to separate the blended record. In the domain where signal concentrates, the multi-scale scheme passes all the coefficients representing signal, while, in the domain where interference focuses, the multi-scale scheme suppresses the coefficients representing interference. Because the interference is suppressed evidently at each iteration, the constraint of multi-scale shaping operator in all scale domains are weak to guarantee the convergence of algorithm. We evaluate the performance of the multi-scale shaping scheme and the traditional global shaping scheme by using two synthetic and one field data examples.
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.
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 image restoration in nulear medicine
International Nuclear Information System (INIS)
Jammal, G.
2001-01-01
This work develops, analyzes and validates a new multiscale restoration framework for denoising and deconvolution in photon limited imagery. Denoising means the estimation of the intensity of a Poisson process from a single observation of the counts, whereas deconvolution refers to the recovery of an object related through a linear system of equations to the intensity function of the Poisson data. The developed framework has been named DeQuant in analogy to Denoising when the noise is of Quantum nature. DeQuant works according to the following scheme. (1) It starts by testing the statistical significance of the wavelet coefficients of the Poisson process, based on the knowledge of their probability density function. (2) A regularization constraint assigns a new value to the non significant coefficients enabling therewith to reduce artifacts and incorporate realistic prior information into the estimation process. Finally, (3) the application of the inverse wavelet transform yields the restored object. The whole procedure is iterated before obtaining the final estimate. The validation of DeQuant on nuclear medicine images showed excellent results. The obtained estimates enable a greater diagnostic confidence in clinical nuclear medicine since they give the physician the access to the diagnosis relevant information with a measure of the significance of the detected structures [de
Multiscale Reconstruction for Magnetic Resonance Fingerprinting
Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.
2015-01-01
Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462
Predicting FLDs Using a Multiscale Modeling Scheme
Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.
2017-09-01
The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.
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.
A multiscale modeling approach for biomolecular systems
Energy Technology Data Exchange (ETDEWEB)
Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)
2015-04-15
This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.
Multiscale wavelet representations for mammographic feature analysis
Laine, Andrew F.; Song, Shuwu
1992-12-01
This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).
Multiscale modeling of polyisoprene on graphite
International Nuclear Information System (INIS)
Pandey, Yogendra Narayan; Brayton, Alexander; Doxastakis, Manolis; Burkhart, Craig; Papakonstantopoulos, George J.
2014-01-01
The local dynamics and the conformational properties of polyisoprene next to a smooth graphite surface constructed by graphene layers are studied by a multiscale methodology. First, fully atomistic molecular dynamics simulations of oligomers next to the surface are performed. Subsequently, Monte Carlo simulations of a systematically derived coarse-grained model generate numerous uncorrelated structures for polymer systems. A new reverse backmapping strategy is presented that reintroduces atomistic detail. Finally, multiple extensive fully atomistic simulations with large systems of long macromolecules are employed to examine local dynamics in proximity to graphite. Polyisoprene repeat units arrange close to a parallel configuration with chains exhibiting a distribution of contact lengths. Efficient Monte Carlo algorithms with the coarse-grain model are capable of sampling these distributions for any molecular weight in quantitative agreement with predictions from atomistic models. Furthermore, molecular dynamics simulations with well-equilibrated systems at all length-scales support an increased dynamic heterogeneity that is emerging from both intermolecular interactions with the flat surface and intramolecular cooperativity. This study provides a detailed comprehensive picture of polyisoprene on a flat surface and consists of an effort to characterize such systems in atomistic detail
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.
Fast Plasma Investigation for Magnetospheric Multiscale
Pollock, C.; Moore, T.; Coffey, V.; Dorelli J.; Giles, B.; Adrian, M.; Chandler, M.; Duncan, C.; Figueroa-Vinas, A.; Garcia, K.;
2016-01-01
The Fast Plasma Investigation (FPI) was developed for flight on the Magnetospheric Multiscale (MMS) mission to measure the differential directional flux of magnetospheric electrons and ions with unprecedented time resolution to resolve kinetic-scale plasma dynamics. This increased resolution has been accomplished by placing four dual 180-degree top hat spectrometers for electrons and four dual 180-degree top hat spectrometers for ions around the periphery of each of four MMS spacecraft. Using electrostatic field-of-view deflection, the eight spectrometers for each species together provide 4pi-sr-field-of-view with, at worst, 11.25-degree sample spacing. Energy/charge sampling is provided by swept electrostatic energy/charge selection over the range from 10 eVq to 30000 eVq. The eight dual spectrometers on each spacecraft are controlled and interrogated by a single block redundant Instrument Data Processing Unit, which in turn interfaces to the observatory's Instrument Suite Central Instrument Data processor. This paper described the design of FPI, its ground and in-flight calibration, its operational concept, and its data products.
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].
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.
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...
Generalized multiscale finite element method. Symmetric interior penalty coupling
Efendiev, Yalchin R.; Galvis, Juan; Lazarov, Raytcho D.; Moon, M.; Sarkis, Marcus V.
2013-01-01
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.
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.
Integrated multiscale biomaterials experiment and modelling: a perspective
Buehler, Markus J.; Genin, Guy M.
2016-01-01
Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126
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.
Study on high density multi-scale calculation technique
International Nuclear Information System (INIS)
Sekiguchi, S.; Tanaka, Y.; Nakada, H.; Nishikawa, T.; Yamamoto, N.; Yokokawa, M.
2004-01-01
To understand degradation of nuclear materials under irradiation, it is essential to know as much about each phenomenon observed from multi-scale points of view; they are micro-scale in atomic-level, macro-level in structural scale and intermediate level. In this study for application to meso-scale materials (100A ∼ 2μm), computer technology approaching from micro- and macro-scales was developed including modeling and computer application using computational science and technology method. And environmental condition of grid technology for multi-scale calculation was prepared. The software and MD (molecular dynamics) stencil for verifying the multi-scale calculation were improved and their movement was confirmed. (A. Hishinuma)
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.
Generalized multiscale finite element methods (GMsFEM)
Efendiev, Yalchin R.; Galvis, Juan; Hou, Thomasyizhao
2013-01-01
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.
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.
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.
Multiscale approach to the physics of radiation damage with ions
Energy Technology Data Exchange (ETDEWEB)
Surdutovich, Eugene [Physics Department, Oakland University, 2200 N. Squirrel Rd., Rochester MI 48309 (United States); Solov' yov, Andrey V. [Frankfurt Institute for Advanced Studies, Goethe University, Ruth-Moufang-Str. 1, Frankfurt am Main 60438 (Germany)
2013-04-19
We review 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 radiation damage scenario occurring on a range of temporal, spatial, and energy scales. We briefly overview its history and present the current stage of its development. The differences of the multiscale approach from other methods of understanding and assessment of radiation damage are discussed as well as its relationship to other branches of physics, chemistry and biology.
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.
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'. © 2016 The Author(s).
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.
Multiscale entropy based study of the pathological time series
International Nuclear Information System (INIS)
Wang Jun; Ma Qianli
2008-01-01
This paper studies the multiscale entropy (MSE) of electrocardiogram's ST segment and compares the MSE results of ST segment with that of electrocardiogram in the first time. Electrocardiogram complexity changing characteristics has important clinical significance for early diagnosis. Study shows that the average MSE values and the varying scope fluctuation could be more effective to reveal the heart health status. Particularly the multiscale values varying scope fluctuation is a more sensitive parameter for early heart disease detection and has a clinical diagnostic significance. (general)
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 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.
Multi-scale magnetic field intermittence in the plasma sheet
Directory of Open Access Journals (Sweden)
Z. Vörös
2003-09-01
Full Text Available This paper demonstrates that intermittent magnetic field fluctuations in the plasma sheet exhibit transitory, localized, and multi-scale features. We propose a multifractal-based algorithm, which quantifies intermittence on the basis of the statistical distribution of the "strength of burstiness", estimated within a sliding window. Interesting multi-scale phenomena observed by the Cluster spacecraft include large-scale motion of the current sheet and bursty bulk flow associated turbulence, interpreted as a cross-scale coupling (CSC process.Key words. Magnetospheric physics (magnetotail; plasma sheet – Space plasma physics (turbulence
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...
Multiscale modeling of emergent materials: biological and soft matter
DEFF Research Database (Denmark)
Murtola, Teemu; Bunker, Alex; Vattulainen, Ilpo
2009-01-01
In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the c......In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed...
Multiscale simulation of water flow past a C540 fullerene
DEFF Research Database (Denmark)
Walther, Jens Honore; Praprotnik, Matej; Kotsalis, Evangelos M.
2012-01-01
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 Nav......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...
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
Integrated multiscale modeling of molecular computing devices
International Nuclear Information System (INIS)
Cummings, Peter T; Leng Yongsheng
2005-01-01
Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic
A multiscale approach to mapping seabed sediments.
Directory of Open Access Journals (Sweden)
Benjamin Misiuk
Full Text Available Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman's ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58. Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.
Quantum theory of multiscale coarse-graining.
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A
2018-03-14
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
First results from the Magnetospheric Multiscale mission
Lavraud, B.
2017-12-01
Since its launch in March 2015, NASA's Magnetospheric Multiscale mission (MMS) provides a wealth of unprecedented high resolution measurements of space plasma properties and dynamics in the near-Earth environment. MMS was designed in the first place to study the fundamental process of collision-less magnetic reconnection. The two first results reviewed here pertain to this topic and highlight how the extremely high resolution MMS data (electrons, in particular, with full three dimensional measurements at 30 ms in burst mode) have permitted to tackle electron dynamics in unprecedented details. The first result demonstrates how electrons become demagnetized and scattered near the magnetic reconnection X line as a result of increased magnetic field curvature, together with a decrease in its magnitude. The second result demonstrates that electrons form crescent-shaped, agyrotropic distribution functions very near the X line, suggestive of the existence of a perpendicular current aligned with the local electric field and consistent with the energy conversion expected in magnetic reconnection (such that J\\cdot E > 0). Aside from magnetic reconnection, we show how MMS contributes to topics such as wave properties and their interaction with particles. Thanks again to extremely high resolution measurements, the lossless and periodical energy exchange between wave electromagnetic fields and particles, as expected in the case of kinetic Alfvén waves, was confirmed. Although not discussed, MMS has the potential to solve many other outstanding issues in collision-less plasma physics, for example regarding shock or turbulence acceleration, with obvious broader impacts in astrophysics in general.
Quantum theory of multiscale coarse-graining
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W.; Voth, Gregory A.
2018-03-01
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
Multiscale peak detection in wavelet space.
Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng
2015-12-07
Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .
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
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
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...
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
Efendiev, Yalchin R.; Galvis, J.; Presho, M.; Zhou, J.
2014-01-01
. 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
Multiscale Modeling of Wear Degradation in Cylinder Liners
Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro
2014-01-01
both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology
Multiscale approach to the physics of radiation damage with ions
International Nuclear Information System (INIS)
Surdutovich, E.; Solov'yov, A.
2014-01-01
The multiscale approach to the assessment of bio-damage resulting upon irradiation of biological media with ions is reviewed, explained and compared to other approaches. The processes of ion propagation in the medium concurrent with ionization and excitation of molecules, transport of secondary products, dynamics of the medium, and biological damage take place on a number of different temporal, spatial and energy scales. The multiscale approach, a physical phenomenon-based analysis of the scenario that leads to radiation damage, has been designed to consider all relevant effects on a variety of scales and develop an approach to the quantitative assessment of biological damage as a result of irradiation with ions. Presently, physical and chemical effects are included in the scenario while the biological effects such as DNA repair are only mentioned. This paper explains the scenario of radiation damage with ions, overviews its major parts, and applies the multiscale approach to different experimental conditions. On the basis of this experience, the recipe for application of the multiscale approach is formulated. The recipe leads to the calculation of relative biological effectiveness. (authors)
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.
Multiscale Path Metrics for the Analysis of Discrete Geometric Structures
2017-11-30
Report: Multiscale Path Metrics for the Analysis of Discrete Geometric Structures The views, opinions and/or findings contained in this report are those...Analysis of Discrete Geometric Structures Report Term: 0-Other Email: tomasi@cs.duke.edu Distribution Statement: 1-Approved for public release
Multiscale analysis of structure development in expanded starch snacks
van der Sman, R. G. M.; Broeze, J.
2014-11-01
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 moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.
On a multiscale approach for filter efficiency simulations
Iliev, Oleg
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.
Multi-scale and multi-orientation medical image analysis
Haar Romenij, ter B.M.; Deserno, T.M.
2011-01-01
Inspired by multi-scale and multi-orientation mechanisms recognized in the first stages of our visual system, this chapter gives a tutorial overview of the basic principles. Images are discrete, measured data. The optimal aperture for an observation with as little artefacts as possible, is derived
Multiscale Modeling of Fracture Processes in Cementitious Materials
Qian, Z.
2012-01-01
Concrete is a composite construction material, which is composed primarily of coarse aggregates, sands and cement paste. The fracture processes in concrete are complicated, because of the multiscale and multiphase nature of the material. In the past decades, comprehensive effort has been put to
Multiscale time-dependent density functional theory: Demonstration for plasmons.
Jiang, Jiajian; Abi Mansour, Andrew; Ortoleva, Peter J
2017-08-07
Plasmon properties are of significant interest in pure and applied nanoscience. While time-dependent density functional theory (TDDFT) can be used to study plasmons, it becomes impractical for elucidating the effect of size, geometric arrangement, and dimensionality in complex nanosystems. In this study, a new multiscale formalism that addresses this challenge is proposed. This formalism is based on Trotter factorization and the explicit introduction of a coarse-grained (CG) structure function constructed as the Weierstrass transform of the electron wavefunction. This CG structure function is shown to vary on a time scale much longer than that of the latter. A multiscale propagator that coevolves both the CG structure function and the electron wavefunction is shown to bring substantial efficiency over classical propagators used in TDDFT. This efficiency follows from the enhanced numerical stability of the multiscale method and the consequence of larger time steps that can be used in a discrete time evolution. The multiscale algorithm is demonstrated for plasmons in a group of interacting sodium nanoparticles (15-240 atoms), and it achieves improved efficiency over TDDFT without significant loss of accuracy or space-time resolution.
Hybrid continuum–molecular modelling of multiscale internal gas flows
International Nuclear Information System (INIS)
Patronis, Alexander; Lockerby, Duncan A.; Borg, Matthew K.; Reese, Jason M.
2013-01-01
We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al. (2013) [28] for the simulation of micro/nano flows of high-aspect ratio. The major new extensions are: (1) incorporation of fluid compressibility; (2) implementation using the direct simulation Monte Carlo (DSMC) method for dilute rarefied gas flows, and (3) application to a broader range of geometries, including periodic, non-periodic, pressure-driven, gravity-driven and shear-driven internal flows. The multiscale method is applied to micro-scale gas flows through a periodic converging–diverging channel (driven by an external acceleration) and a non-periodic channel with a bend (driven by a pressure difference), as well as the flow between two eccentric cylinders (with the inner rotating relative to the outer). In all these cases there exists a wide variation of Knudsen number within the geometries, as well as substantial compressibility despite the Mach number being very low. For validation purposes, our multiscale simulation results are compared to those obtained from full-scale DSMC simulations: very close agreement is obtained in all cases for all flow variables considered. Our multiscale simulation is an order of magnitude more computationally efficient than the full-scale DSMC for the first and second test cases, and two orders of magnitude more efficient for the third case
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.
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 basis
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...
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 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...
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...
Musical Instrument Identification using Multiscale Mel-frequency Cepstral Coefficients
DEFF Research Database (Denmark)
Sturm, Bob L.; Morvidone, Marcela; Daudet, Laurent
2010-01-01
We investigate the benefits of evaluating Mel-frequency cepstral coefficients (MFCCs) over several time scales in the context of automatic musical instrument identification for signals that are monophonic but derived from real musical settings. We define several sets of features derived from MFCC...... multiscale decompositions perform significantly better than features computed using a single time-resolution....
Fast 2D Simulation of Superconductors: a Multiscale Approach
DEFF Research Database (Denmark)
Rodriguez Zermeno, Victor Manuel; Sørensen, Mads Peter; Pedersen, Niels Falsig
2009-01-01
This work presents a method to calculate AC losses in thin conductors such as the commercially available second generation superconducting wires through a multiscale meshing technique. The main idea is to use large aspect ratio elements to accurately simulate thin material layers. For a single thin...
Control algorithm for multiscale flow simulations of water
DEFF Research Database (Denmark)
Kotsalis, E. M.; Walther, Jens Honore; Kaxiras, E.
2009-01-01
We present a multiscale algorithm to couple atomistic water models with continuum incompressible flow simulations via a Schwarz domain decomposition approach. The coupling introduces an inhomogeneity in the description of the atomistic domain and prevents the use of periodic boundary conditions...
Hypoglycemia-Related Electroencephalogram Changes Assessed by Multiscale Entropy
DEFF Research Database (Denmark)
Fabris, C.; Sparacino, G.; Sejling, A. S.
2014-01-01
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...
Elimination of intermediate species in multiscale stochastic reaction networks
DEFF Research Database (Denmark)
Cappelletti, Daniele; Wiuf, Carsten
2016-01-01
such as the substrate-enzyme complex in the Michaelis-Menten mechanism. Such species are virtually in all real-world networks, they are typically short-lived, degraded at a fast rate and hard to observe experimentally. We provide conditions under which the Markov process of a multiscale reaction network...
Efficient topology optimisation of multiscale and multiphysics problems
DEFF Research Database (Denmark)
Alexandersen, Joe
The aim of this Thesis is to present efficient methods for optimising high-resolution problems of a multiscale and multiphysics nature. The Thesis consists of two parts: one treating topology optimisation of microstructural details and the other treating topology optimisation of conjugate heat...
Computer-Aided Multiscale Modelling for Chemical Process Engineering
DEFF Research Database (Denmark)
Morales Rodriguez, Ricardo; Gani, Rafiqul
2007-01-01
Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework...
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...
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
Multiscale equation-free algorithms for molecular dynamics
Abi Mansour, Andrew
Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.
Multiscale modeling of transdermal drug delivery
Rim, Jee Eun
2006-04-01
This study addresses the modeling of transdermal diffusion of drugs, to better understand the permeation of molecules through the skin, and especially the stratum corneum, which forms the main permeation barrier of the skin. In transdermal delivery of systemic drugs, the drugs diffuse from a patch placed on the skin through the epidermis to the underlying blood vessels. The epidermis is the outermost layer of the skin and can be further divided into the stratum corneum (SC) and the viable epidermis layers. The SC consists of keratinous cells (corneocytes) embedded in the lipid multi-bilayers of the intercellular space. It is widely accepted that the barrier properties of the skin mostly arises from the ordered structure of the lipid bilayers. The diffusion path, at least for lipophilic molecules, seems to be mainly through the lipid bilayers. Despite the advantages of transdermal drug delivery compared to other drug delivery routes such as oral dosing and injections, the low percutaneous permeability of most compounds is a major difficulty in the wide application of transdermal drug delivery. In fact, many transdermal drug formulations include one or more permeation enhancers that increase the permeation of the drug significantly. During the last two decades, many researchers have studied percutaneous absorption of drugs both experimentally and theoretically. However, many are based on pharmacokinetic compartmental models, in which steady or pseudo-steady state conditions are assumed, with constant diffusivity and partitioning for single component systems. This study presents a framework for studying the multi-component diffusion of drugs coupled with enhancers through the skin by considering the microstructure of the stratum corneum (SC). A multiscale framework of modeling the transdermal diffusion of molecules is presented, by first calculating the microscopic diffusion coefficient in the lipid bilayers of the SC using molecular dynamics (MD). Then a
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
Multiscale decomposition for heterogeneous land-atmosphere systems
Liu, Shaofeng; Shao, Yaping; Hintz, Michael; Lennartz-Sassinek, Sabine
2015-02-01
The land-atmosphere system is characterized by pronounced land surface heterogeneity and vigorous atmospheric turbulence both covering a wide range of scales. The multiscale surface heterogeneities and multiscale turbulent eddies interact nonlinearly with each other. Understanding these multiscale processes quantitatively is essential to the subgrid parameterizations for weather and climate models. In this paper, we propose a method for surface heterogeneity quantification and turbulence structure identification. The first part of the method is an orthogonal transform in the probability density function (PDF) domain, in contrast to the orthogonal wavelet transforms which are performed in the physical space. As the basis of the whole method, the orthogonal PDF transform (OPT) is used to asymptotically reconstruct the original signals by representing the signal values with multilevel approximations. The "patch" idea is then applied to these reconstructed fields in order to recognize areas at the land surface or in turbulent flows that are of the same characteristics. A patch here is a connected area with the same approximation. For each recognized patch, a length scale is then defined to build the energy spectrum. The OPT and related energy spectrum analysis, as a whole referred to as the orthogonal PDF decomposition (OPD), is applied to two-dimensional heterogeneous land surfaces and atmospheric turbulence fields for test. The results show that compared to the wavelet transforms, the OPD can reconstruct the original signal more effectively, and accordingly, its energy spectrum represents the signal's multiscale variation more accurately. The method we propose in this paper is of general nature and therefore can be of interest for problems of multiscale process description in other geophysical disciplines.
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.
Validation of community models: 3. Tracing field lines in heliospheric models
MacNeice, Peter; Elliott, Brian; Acebal, Ariel
2011-10-01
Forecasting hazardous gradual solar energetic particle (SEP) bursts at Earth requires accurately modeling field line connections between Earth and the locations of coronal or interplanetary shocks that accelerate the particles. We test the accuracy of field lines reconstructed using four different models of the ambient coronal and inner heliospheric magnetic field, through which these shocks must propagate, including the coupled Wang-Sheeley-Arge (WSA)/ENLIL model. Evaluating the WSA/ENLIL model performance is important since it is the most sophisticated model currently available to space weather forecasters which can model interplanetary coronal mass ejections and, when coupled with particle acceleration and transport models, will provide a complete model for gradual SEP bursts. Previous studies using a simpler Archimedean spiral approach above 2.5 solar radii have reported poor performance. We test the accuracy of the model field lines connecting Earth to the Sun at the onset times of 15 impulsive SEP bursts, comparing the foot points of these field lines with the locations of surface events believed to be responsible for the SEP bursts. We find the WSA/ENLIL model performance is no better than the simplest spiral model, and the principal source of error is the model's inability to reproduce sufficient low-latitude open flux. This may be due to the model's use of static synoptic magnetograms, which fail to account for transient activity in the low corona, during which reconnection events believed to initiate the SEP acceleration may contribute short-lived open flux at low latitudes. Time-dependent coronal models incorporating these transient events may be needed to significantly improve Earth/Sun field line forecasting.
Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence
Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem
2017-04-01
Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings
A posteriori error analysis of multiscale operator decomposition methods for multiphysics models
International Nuclear Information System (INIS)
Estep, D; Carey, V; Tavener, S; Ginting, V; Wildey, T
2008-01-01
Multiphysics, multiscale models present significant challenges in computing accurate solutions and for estimating the error in information computed from numerical solutions. In this paper, we describe recent advances in extending the techniques of a posteriori error analysis to multiscale operator decomposition solution methods. While the particulars of the analysis vary considerably with the problem, several key ideas underlie a general approach being developed to treat operator decomposition multiscale methods. We explain these ideas in the context of three specific examples
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....... Multiscale composites with exfoliated nanoreinforcement and aligned nanoplatelets ensure the better fatigue resistance than those with intercalated/clustered and randomly oriented nanoreinforcement....
Li, Xin; Liu, Shaomin; Xiao, Qin; Ma, Mingguo; Jin, Rui; Che, Tao; Wang, Weizhen; Hu, Xiaoli; Xu, Ziwei; Wen, Jianguang; Wang, Liangxu
2017-01-01
We introduce a multiscale dataset obtained from Heihe Watershed Allied Telemetry Experimental Research (HiWATER) in an oasis-desert area in 2012. Upscaling of eco-hydrological processes on a heterogeneous surface is a grand challenge. Progress in this field is hindered by the poor availability of multiscale observations. HiWATER is an experiment designed to address this challenge through instrumentation on hierarchically nested scales to obtain multiscale and multidisciplinary data. The HiWAT...
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.
Multiscale analysis of surface morphologies by curvelet and contourlet transforms
International Nuclear Information System (INIS)
Li, Linfu; Zhang, Xiangchao; Zhang, Hao; He, Xiaoying; Xu, Min
2015-01-01
The surface topographies of precision components are critical to their functionalities. However, it is challenging to characterize the topographies of complex surfaces, especially for structured surfaces. The wavelet families are promising for the multiscale geometry analysis of nonstochastic surfaces. The second-generation curvelet transform provides a sparse representation and good multiscale decomposition for curve singularities. However, the contourlet expansion, composed of bases oriented along various directions in multiple scales with smaller redundancy rates, has a remarkable capability of representing borderlines. In this paper they are both adopted for the characterization of surface topographies. Different components can be extracted according to their scales and morphological characteristics; as a result, the corresponding manufacturing processes and functionalities can be analyzed specifically. Numerical experiments are given to demonstrate the capabilities of these methods in sparse representation and effective extraction of geometry features of different nonstochastic surfaces. (paper)
The Multiscale Material Point Method for Simulating Transient Responses
Chen, Zhen; Su, Yu-Chen; Zhang, Hetao; Jiang, Shan; Sewell, Thomas
2015-06-01
To effectively simulate multiscale transient responses such as impact and penetration without invoking master/slave treatment, the multiscale material point method (Multi-MPM) is being developed in which molecular dynamics at nanoscale and dissipative particle dynamics at mesoscale might be concurrently handled within the framework of the original MPM at microscale (continuum level). The proposed numerical scheme for concurrently linking different scales is described in this paper with simple examples for demonstration. It is shown from the preliminary study that the mapping and re-mapping procedure used in the original MPM could coarse-grain the information at fine scale and that the proposed interfacial scheme could provide a smooth link between different scales. Since the original MPM is an extension from computational fluid dynamics to solid dynamics, the proposed Multi-MPM might also become robust for dealing with multiphase interactions involving failure evolution. This work is supported in part by DTRA and NSFC.
Multiscale correlations in highly resolved Large Eddy Simulations
Biferale, Luca; Buzzicotti, Michele; Linkmann, Moritz
2017-11-01
Understanding multiscale turbulent statistics is one of the key challenges for many modern applied and fundamental problems in fluid dynamics. One of the main obstacles is the existence of anomalously strong non Gaussian fluctuations, which become more and more important with increasing Reynolds number. In order to assess the performance of LES models in reproducing these extreme events with reasonable accuracy, it is helpful to further understand the statistical properties of the coupling between the resolved and the subgrid scales. We present analytical and numerical results focussing on the multiscale correlations between the subgrid stress and the resolved velocity field obtained both from LES and filtered DNS data. Furthermore, a comparison is carried out between LES and DNS results concerning the scaling behaviour of higher-order structure functions using both Smagorinsky or self-similar Fourier sub-grid models. ERC AdG Grant No 339032 NewTURB.
Multiscale Modeling of Composites: Toward Virtual Testing … and Beyond
LLorca, J.; González, C.; Molina-Aldareguía, J. M.; Lópes, C. S.
2013-02-01
Recent developments in the area of multiscale modeling of fiber-reinforced polymers are presented. The overall strategy takes advantage of the separation of length scales between different entities (ply, laminate, and component) found in composite structures. This allows us to carry out multiscale modeling by computing the properties of one entity (e.g., individual plies) at the relevant length scale, homogenizing the results into a constitutive model, and passing this information to the next length scale to determine the mechanical behavior of the larger entity (e.g., laminate). As a result, high-fidelity numerical simulations of the mechanical behavior of composite coupons and small components are nowadays feasible starting from the matrix, fiber, and interface properties and spatial distribution. Finally, the roadmap is outlined for extending the current strategy to include functional properties and processing into the simulation scheme.
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.
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.
Global sensitivity analysis of multiscale properties of porous materials
Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.
2018-02-01
Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.
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.
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.
Versatile Micromechanics Model for Multiscale Analysis of Composite Structures
Kwon, Y. W.; Park, M. S.
2013-08-01
A general-purpose micromechanics model was developed so that the model could be applied to various composite materials such as reinforced by particles, long fibers and short fibers as well as those containing micro voids. Additionally, the model can be used with hierarchical composite materials. The micromechanics model can be used to compute effective material properties like elastic moduli, shear moduli, Poisson's ratios, and coefficients of thermal expansion for the various composite materials. The model can also calculate the strains and stresses at the constituent material level such as fibers, particles, and whiskers from the composite level stresses and strains. The model was implemented into ABAQUS using the UMAT option for multiscale analysis. An extensive set of examples are presented to demonstrate the reliability and accuracy of the developed micromechanics model for different kinds of composite materials. Another set of examples is provided to study the multiscale analysis of composite structures.
Information theory and stochastics for multiscale nonlinear systems
Majda, Andrew J; Grote, Marcus J
2005-01-01
This book introduces mathematicians to the fascinating emerging mathematical interplay between ideas from stochastics and information theory and important practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena. After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of com...
Formalizing Knowledge in Multi-Scale Agent-Based Simulations.
Somogyi, Endre; Sluka, James P; Glazier, James A
2016-10-01
Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.
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 Methods for Accurate, Efficient, and Scale-Aware Models
Energy Technology Data Exchange (ETDEWEB)
Larson, Vincent [Univ. of Wisconsin, Milwaukee, WI (United States)
2017-07-14
The goal of UWM’s portion of the Multiscale project was to develop a unified cloud parameterization that could simulate all cloud types --- including stratocumulus, shallow cumulus, and deep cumulus --- using the single equation set implemented in CLUBB. An advantage of a unified parameterization methodology is that it avoids the difficult task of interfacing different cloud parameterizations for different cloud types. To interface CLUBB’s clouds to the microphysics, a Monte Carlo interface, SILHS, was further developed.
Nonlinear dynamics of the complex multi-scale network
Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.
2018-04-01
In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.
Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.
Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan
2017-04-07
In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.
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 eddy simulation for moist atmospheric convection: Preliminary investigation
Energy Technology Data Exchange (ETDEWEB)
Stechmann, Samuel N., E-mail: stechmann@wisc.edu [Department of Mathematics, University of Wisconsin-Madison (United States); Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison (United States)
2014-08-15
A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes.
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 eddy simulation for moist atmospheric convection: Preliminary investigation
International Nuclear Information System (INIS)
Stechmann, Samuel N.
2014-01-01
A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes
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.
Multiscale structural study using scanning X-ray microscope
International Nuclear Information System (INIS)
Ohsumi, Hiroyuki; Arima, Taka-hisa
2016-01-01
Correspondence between structures at the atomic- and meso-scales can be given by scanning X-ray microscopy integrated with polarized X-ray diffractometry. Symmetry is the common structural feature available across multiple hierarchies. This article introduces a symmetry evaluation technique based on polarized X-ray diffractometry and describes two embodiments: chirality domain observation and antiferromagnetic domain observation. Multiscale structural studies would play an important role in uncovering universality of hierarchical structure. (author)
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 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.
Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems
Liu, Xuan; Furrer, David; Kosters, Jared; Holmes, Jack
2018-01-01
Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost
Multiscale methods in turbulent combustion: strategies and computational challenges
International Nuclear Information System (INIS)
Echekki, Tarek
2009-01-01
A principal challenge in modeling turbulent combustion flows is associated with their complex, multiscale nature. Traditional paradigms in the modeling of these flows have attempted to address this nature through different strategies, including exploiting the separation of turbulence and combustion scales and a reduced description of the composition space. The resulting moment-based methods often yield reasonable predictions of flow and reactive scalars' statistics under certain conditions. However, these methods must constantly evolve to address combustion at different regimes, modes or with dominant chemistries. In recent years, alternative multiscale strategies have emerged, which although in part inspired by the traditional approaches, also draw upon basic tools from computational science, applied mathematics and the increasing availability of powerful computational resources. This review presents a general overview of different strategies adopted for multiscale solutions of turbulent combustion flows. Within these strategies, some specific models are discussed or outlined to illustrate their capabilities and underlying assumptions. These strategies may be classified under four different classes, including (i) closure models for atomistic processes, (ii) multigrid and multiresolution strategies, (iii) flame-embedding strategies and (iv) hybrid large-eddy simulation-low-dimensional strategies. A combination of these strategies and models can potentially represent a robust alternative strategy to moment-based models; but a significant challenge remains in the development of computational frameworks for these approaches as well as their underlying theories. (topical review)
Multiscale geometric modeling of macromolecules II: Lagrangian representation
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-01-01
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-EM, 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, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599
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.
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.
Numerical Simulations of a Multiscale Model of Stratified Langmuir Circulation
Malecha, Ziemowit; Chini, Gregory; Julien, Keith
2012-11-01
Langmuir circulation (LC), a prominent form of wind and surface-wave driven shear turbulence in the ocean surface boundary layer (BL), is commonly modeled using the Craik-Leibovich (CL) equations, a phase-averaged variant of the Navier-Stokes (NS) equations. Although surface-wave filtering renders the CL equations more amenable to simulation than are the instantaneous NS equations, simulations in wide domains, hundreds of times the BL depth, currently earn the ``grand challenge'' designation. To facilitate simulations of LC in such spatially-extended domains, we have derived multiscale CL equations by exploiting the scale separation between submesoscale and BL flows in the upper ocean. The numerical algorithm for simulating this multiscale model resembles super-parameterization schemes used in meteorology, but retains a firm mathematical basis. We have validated our algorithm and here use it to perform multiscale simulations of the interaction between LC and upper ocean density stratification. ZMM, GPC, KJ gratefully acknowledge funding from NSF CMG Award 0934827.
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.
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.
Introduction and application of the multiscale coefficient of variation analysis.
Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh
2017-10-01
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.
Multi-scale simulation for homogenization of cement media
International Nuclear Information System (INIS)
Abballe, T.
2011-01-01
To solve diffusion problems on cement media, two scales must be taken into account: a fine scale, which describes the micrometers wide microstructures present in the media, and a work scale, which is usually a few meters long. Direct numerical simulations are almost impossible because of the huge computational resources (memory, CPU time) required to assess both scales at the same time. To overcome this problem, we present in this thesis multi-scale resolution methods using both Finite Volumes and Finite Elements, along with their efficient implementations. More precisely, we developed a multi-scale simulation tool which uses the SALOME platform to mesh domains and post-process data, and the parallel calculation code MPCube to solve problems. This SALOME/MPCube tool can solve automatically and efficiently multi-scale simulations. Parallel structure of computer clusters can be use to dispatch the more time-consuming tasks. We optimized most functions to account for cement media specificities. We presents numerical experiments on various cement media samples, e.g. mortar and cement paste. From these results, we manage to compute a numerical effective diffusivity of our cement media and to reconstruct a fine scale solution. (author) [fr
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.
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.
Multiscale modeling of radiation effects in nuclear reactor structural materials
Energy Technology Data Exchange (ETDEWEB)
Kwon, Junhyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
Most problems in irradiated materials originate from the atomic collision of high-energy particles and lattice atoms. This collision leads to displacement cascades through the energy transfer reaction and causes various types of defects such as vacancies, interstitials, and clusters. The behavior of the point defects created in the displacement cascades is important because these defects play a major role in a microstructural evolution and further affect the changes in material properties. Rapid advances have been made in the computational capabilities for a realistic simulation of complex physical phenomena, such as irradiation and aging effects. At the same time, progress has been made in understanding the effect of radiation in metals, especially iron-based alloys. In this work, we present some of our ongoing work in this area, which illustrates a multiscale modeling for evaluating a microstructural evolution and mechanical property changes during irradiation. Multiscale modeling approaches are briefly presented here in the following order: nuclear interaction, atomic-level interaction, atomistic modeling, microstructural evolution modeling and mechanical property modeling. This is one of many possible methods for classifying techniques. The effort in developing physical multiscale models applied to radiation damage has been focused on a single crystal or single-grain materials.
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.
Atomistic to Continuum Multiscale and Multiphysics Simulation of NiTi Shape Memory Alloy
Gur, Sourav
Shape memory alloys (SMAs) are materials that show reversible, thermo-elastic, diffusionless, displacive (solid to solid) phase transformation, due to the application of temperature and/ or stress (/strain). Among different SMAs, NiTi is a popular one. NiTi shows reversible phase transformation, the shape memory effect (SME), where irreversible deformations are recovered upon heating, and superelasticity (SE), where large strains imposed at high enough temperatures are fully recovered. Phase transformation process in NiTi SMA is a very complex process that involves the competition between developed internal strain and phonon dispersion instability. In NiTi SMA, phase transformation occurs over a wide range of temperature and/ or stress (strain) which involves, evolution of different crystalline phases (cubic austenite i.e. B2, different monoclinic variant of martensite i.e. B19', and orthorhombic B19 or BCO structures). Further, it is observed from experimental and computational studies that the evolution kinetics and growth rate of different phases in NiTi SMA vary significantly over a wide spectrum of spatio-temporal scales, especially with length scales. At nano-meter length scale, phase transformation temperatures, critical transformation stress (or strain) and phase fraction evolution change significantly with sample or simulation cell size and grain size. Even, below a critical length scale, the phase transformation process stops. All these aspects make NiTi SMA very interesting to the science and engineering research community and in this context, the present focuses on the following aspects. At first this study address the stability, evolution and growth kinetics of different phases (B2 and variants of B19'), at different length scales, starting from the atomic level and ending at the continuum macroscopic level. The effects of simulation cell size, grain size, and presence of free surface and grain boundary on the phase transformation process
Multiscale modelling and experimentation of hydrogen embrittlement in aerospace materials
Jothi, Sathiskumar
Pulse plated nickel and nickel based superalloys have been used extensively in the Ariane 5 space launcher engines. Large structural Ariane 5 space launcher engine components such as combustion chambers with complex microstructures have usually been manufactured using electrodeposited nickel with advanced pulse plating techniques with smaller parts made of nickel based superalloys joined or welded to the structure to fabricate Ariane 5 space launcher engines. One of the major challenges in manufacturing these space launcher components using newly developed materials is a fundamental understanding of how different materials and microstructures react with hydrogen during welding which can lead to hydrogen induced cracking. The main objective of this research has been to examine and interpret the effects of microstructure on hydrogen diffusion and hydrogen embrittlement in (i) nickel based superalloy 718, (ii) established and (iii) newly developed grades of pulse plated nickel used in the Ariane 5 space launcher engine combustion chamber. Also, the effect of microstructures on hydrogen induced hot and cold cracking and weldability of three different grades of pulse plated nickel were investigated. Multiscale modelling and experimental methods have been used throughout. The effect of microstructure on hydrogen embrittlement was explored using an original multiscale numerical model (exploiting synthetic and real microstructures) and a wide range of material characterization techniques including scanning electron microscopy, 2D and 3D electron back scattering diffraction, in-situ and ex-situ hydrogen charged slow strain rate tests, thermal spectroscopy analysis and the Varestraint weldability test. This research shows that combined multiscale modelling and experimentation is required for a fundamental understanding of microstructural effects in hydrogen embrittlement in these materials. Methods to control the susceptibility to hydrogen induced hot and cold cracking and
Sun, S.; Kou, J.; Yu, B.
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.
Chinese Medical Question Answer Matching Using End-to-End Character-Level Multi-Scale CNNs
Directory of Open Access Journals (Sweden)
Sheng Zhang
2017-07-01
Full Text Available This paper focuses mainly on the problem of Chinese medical question answer matching, which is arguably more challenging than open-domain question answer matching in English due to the combination of its domain-restricted nature and the language-specific features of Chinese. We present an end-to-end character-level multi-scale convolutional neural framework in which character embeddings instead of word embeddings are used to avoid Chinese word segmentation in text preprocessing, and multi-scale convolutional neural networks (CNNs are then introduced to extract contextual information from either question or answer sentences over different scales. The proposed framework can be trained with minimal human supervision and does not require any handcrafted features, rule-based patterns, or external resources. To validate our framework, we create a new text corpus, named cMedQA, by harvesting questions and answers from an online Chinese health and wellness community. The experimental results on the cMedQA dataset show that our framework significantly outperforms several strong baselines, and achieves an improvement of top-1 accuracy by up to 19%.
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
Carmeliet, J.; Descamps, F.; Houvenaghel, G.
1999-01-01
A multiscale network model is presented to model unsaturated moisture transfer in hygroscopic capillary-porous materials showing a broad pore-size distribution. Both capillary effects and water sorption phenomena, water vapour and liquid water transfer are considered. The multiscale approach is
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.
Horowitz, F. G.; Gaede, O.
2014-12-01
Wavelet multiscale edge analysis of potential fields (a.k.a. "worms") has been known since Moreau et al. (1997) and was independently derived by Hornby et al. (1999). The technique is useful for producing a scale-explicit overview of the structures beneath a gravity or magnetic survey, including establishing the location and estimating the attitude of surface features, as well as incorporating information about the geometric class (point, line, surface, volume, fractal) of the underlying sources — in a fashion much like traditional structural indices from Euler solutions albeit with better areal coverage. Hornby et al. (2002) show that worms form the locally highest concentration of horizontal edges of a given strike — which in conjunction with the results from Mallat and Zhong (1992) induces a (non-unique!) inversion where the worms are physically interpretable as lateral boundaries in a source distribution that produces a close approximation of the observed potential field. The technique has enjoyed widespread adoption and success in the Australian mineral exploration community — including "ground truth" via successfully drilling structures indicated by the worms. Unfortunately, to our knowledge, all implementations of the code to calculate the worms/multiscale edges (including Horowitz' original research code) are either part of commercial software packages, or have copyright restrictions that impede the use of the technique by the wider community. The technique is completely described mathematically in Hornby et al. (1999) along with some later publications. This enables us to re-implement from scratch the code required to calculate and visualize the worms. We are freely releasing the results under an (open source) BSD two-clause software license. A git repository is available at . We will give an overview of the technique, show code snippets using the codebase, and present visualization results for example datasets (including the Surat basin of Australia
Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.
Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L
2008-06-01
Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.
Jiang, Lijian; Efendiev, Yalchin; Ginting, Victor
2010-01-01
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.
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.
Recent progress in modelling 3D lithospheric deformation
Kaus, B. J. P.; Popov, A.; May, D. A.
2012-04-01
Modelling 3D lithospheric deformation remains a challenging task, predominantly because the variations in rock types, as well as nonlinearities due to for example plastic deformation result in sharp and very large jumps in effective viscosity contrast. As a result, there are only a limited number of 3D codes available, most of which are using direct solvers which are computationally and memory-wise very demanding. As a result, the resolutions for typical model runs are quite modest, despite the use of hundreds of processors (and using much larger computers is unlikely to bring much improvement in this situation). For this reason we recently developed a new 3D deformation code,called LaMEM: Lithosphere and Mantle Evolution Model. LaMEM is written on top of PETSc, and as a result it runs on massive parallel machines and we have a large number of iterative solvers available (including geometric and algebraic multigrid methods). As it remains unclear which solver combinations work best under which conditions, we have implemented most currently suggested methods (such as schur complement reduction or Fully coupled iterations). In addition, we can use either a finite element discretization (with Q1P0, stabilized Q1Q1 or Q2P-1 elements) or a staggered finite difference discretization for the same input geometry, which is based on a marker and cell technique). This gives us he flexibility to test various solver methodologies on the same model setup, in terms of accuracy, speed, memory usage etc. Here, we will report on some features of LaMEM, on recent code additions, as well as on some lessons we learned which are important for modelling 3D lithospheric deformation. Specifically we will discuss: 1) How we combine a particle-and-cell method to make it work with both a finite difference and a (lagrangian, eulerian or ALE) finite element formulation, with only minor code modifications code 2) How finite difference and finite element discretizations compare in terms of
Activation of the marine ecosystem model 3D CEMBS for the Baltic Sea in operational mode
Dzierzbicka-Glowacka, Lidia; Jakacki, Jaromir; Janecki, Maciej; Nowicki, Artur
2013-04-01
The paper presents a new marine ecosystem model 3D CEMBS designed for the Baltic Sea. The ecosystem model is incorporated into the 3D POPCICE ocean-ice model. The Current Baltic Sea model is based on the Community Earth System Model (CESM from the National Center for Atmospheric Research) which was adapted for the Baltic Sea as a coupled sea-ice model. It consists of the Community Ice Code (CICE model, version 4.0) and the Parallel Ocean Program (version 2.1). The ecosystem model is a biological submodel of the 3D CEMBS. It consists of eleven mass conservation equations. There are eleven partial second-order differential equations of the diffusion type with the advective term for phytoplankton, zooplankton, nutrients, dissolved oxygen, and dissolved and particulate organic matter. This model is an effective tool for solving the problem of ecosystem bioproductivity. The model is forced by 48-hour atmospheric forecasts provided by the UM model from the Interdisciplinary Centre for Mathematical and Computational Modelling of Warsaw University (ICM). The study was financially supported by the Polish State Committee of Scientific Research (grants: No N N305 111636, N N306 353239). The partial support for this study was also provided by the project Satellite Monitoring of the Baltic Sea Environment - SatBaltyk founded by European Union through European Regional Development Fund contract no. POIG 01.01.02-22-011/09. Calculations were carried out at the Academy Computer Centre in Gdańsk.
Multiscale Currents Observed by MMS in the Flow Braking Region
Nakamura, Rumi; Varsani, Ali; Genestreti, Kevin J.; Le Contel, Olivier; Nakamura, Takuma; Baumjohann, Wolfgang; Nagai, Tsugunobu; Artemyev, Anton; Birn, Joachim; Sergeev, Victor A.; Apatenkov, Sergey; Ergun, Robert E.; Fuselier, Stephen A.; Gershman, Daniel J.; Giles, Barbara J.; Khotyaintsev, Yuri V.; Lindqvist, Per-Arne; Magnes, Werner; Mauk, Barry; Petrukovich, Anatoli; Russell, Christopher T.; Stawarz, Julia; Strangeway, Robert J.; Anderson, Brian; Burch, James L.; Bromund, Ken R.; Cohen, Ian; Fischer, David; Jaynes, Allison; Kepko, Laurence; Le, Guan; Plaschke, Ferdinand; Reeves, Geoff; Singer, Howard J.; Slavin, James A.; Torbert, Roy B.; Turner, Drew L.
2018-02-01
We present characteristics of current layers in the off-equatorial near-Earth plasma sheet boundary observed with high time-resolution measurements from the Magnetospheric Multiscale mission during an intense substorm associated with multiple dipolarizations. The four Magnetospheric Multiscale spacecraft, separated by distances of about 50 km, were located in the southern hemisphere in the dusk portion of a substorm current wedge. They observed fast flow disturbances (up to about 500 km/s), most intense in the dawn-dusk direction. Field-aligned currents were observed initially within the expanding plasma sheet, where the flow and field disturbances showed the distinct pattern expected in the braking region of localized flows. Subsequently, intense thin field-aligned current layers were detected at the inner boundary of equatorward moving flux tubes together with Earthward streaming hot ions. Intense Hall current layers were found adjacent to the field-aligned currents. In particular, we found a Hall current structure in the vicinity of the Earthward streaming ion jet that consisted of mixed ion components, that is, hot unmagnetized ions, cold E × B drifting ions, and magnetized electrons. Our observations show that both the near-Earth plasma jet diversion and the thin Hall current layers formed around the reconnection jet boundary are the sites where diversion of the perpendicular currents take place that contribute to the observed field-aligned current pattern as predicted by simulations of reconnection jets. Hence, multiscale structure of flow braking is preserved in the field-aligned currents in the off-equatorial plasma sheet and is also translated to ionosphere to become a part of the substorm field-aligned current system.
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 geometric modeling of macromolecules I: Cartesian representation
Energy Technology Data Exchange (ETDEWEB)
Xia, Kelin [Department of Mathematics, Michigan State University, MI 48824 (United States); Feng, Xin [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Chen, Zhan [Department of Mathematics, Michigan State University, MI 48824 (United States); Tong, Yiying [Department of Computer Science and Engineering, Michigan State University, MI 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, MI 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824 (United States)
2014-01-15
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
Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis
International Nuclear Information System (INIS)
2015-01-01
Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.
Multiscale Embedded Gene Co-expression Network Analysis.
Directory of Open Access Journals (Sweden)
Won-Min Song
2015-11-01
Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
Multiscale Embedded Gene Co-expression Network Analysis.
Song, Won-Min; Zhang, Bin
2015-11-01
Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
The set of prime numbers: Multiscale analysis and numeric accelerators
International Nuclear Information System (INIS)
Iovane, Gerardo
2009-01-01
In this work, we show that the prime numbers follow a multiscale distribution. Indeed they can be classified thanks to tree structures, which are expressed in terms of two maximal subsets of N and using multilayer selection rules, acting on these sets of prime candidates. Consequently, the prime numbers follow a specific deterministic rules. Indeed, a numeric accelerator for generating primes can be realized in terms of the above mentioned specific rules. From the comparison with the Fibonacci numbers a beautiful harmony comes in terms of the Golden Mean which is relevant to high energy physics and E-Infinity theory too.
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.
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.
Multivariate and multiscale data assimilation in terrestrial systems: a review.
Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry
2012-11-26
More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a
Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review
Directory of Open Access Journals (Sweden)
Harry Vereecken
2012-11-01
Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a
Fast Decentralized Averaging via Multi-scale Gossip
Tsianos, Konstantinos I.; Rabbat, Michael G.
We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.
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.
Multiscale Modeling of Carbon Nanotube-Epoxy Nanocomposites
Fasanella, Nicholas A.
Epoxy-composites are widely used in the aerospace industry. In order to improve upon stiffness and thermal conductivity; carbon nanotube additives to epoxies are being explored. This dissertation presents multiscale modeling techniques to study the engineering properties of single walled carbon nanotube (SWNT)-epoxy nanocomposites, consisting of pristine and covalently functionalized systems. Using Molecular Dynamics (MD), thermomechanical properties were calculated for a representative polymer unit cell. Finite Element (FE) and orientation distribution function (ODF) based methods were used in a multiscale framework to obtain macroscale properties. An epoxy network was built using the dendrimer growth approach. The epoxy model was verified by matching the experimental glass transition temperature, density, and dilatation. MD, via the constant valence force field (CVFF), was used to explore the mechanical and dilatometric effects of adding pristine and functionalized SWNTs to epoxy. Full stiffness matrices and linear coefficient of thermal expansion vectors were obtained. The Green-Kubo method was used to investigate the thermal conductivity as a function of temperature for the various nanocomposites. Inefficient phonon transport at the ends of nanotubes is an important factor in the thermal conductivity of the nanocomposites, and for this reason discontinuous nanotubes were modeled in addition to long nanotubes. To obtain continuum-scale elastic properties from the MD data, multiscale modeling was considered to give better control over the volume fraction of nanotubes, and investigate the effects of nanotube alignment. Two methods were considered; an FE based method, and an ODF based method. The FE method probabilistically assigned elastic properties of elements from the MD lattice results based on the desired volume fraction and alignment of the nanotubes. For the ODF method, a distribution function was generated based on the desired amount of nanotube alignment
3D Multiscale Modelling of Angiogenesis and Vascular Tumour Growth
Perfahl, H.; Byrne, H. M.; Chen, T.; Estrella, V.; Alarcó n, T.; Lapin, A.; Gatenby, R. A.; Gillies, R. J.; Lloyd, M. C.; Maini, P. K.; Reuss, M.; Owen, M. R.
2012-01-01
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.
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.
Multi-scale modeling of spin transport in organic semiconductors
Hemmatiyan, Shayan; Souza, Amaury; Kordt, Pascal; McNellis, Erik; Andrienko, Denis; Sinova, Jairo
In this work, we present our theoretical framework to simulate simultaneously spin and charge transport in amorphous organic semiconductors. By combining several techniques e.g. molecular dynamics, density functional theory and kinetic Monte Carlo, we are be able to study spin transport in the presence of anisotropy, thermal effects, magnetic and electric field effects in a realistic morphologies of amorphous organic systems. We apply our multi-scale approach to investigate the spin transport in amorphous Alq3 (Tris(8-hydroxyquinolinato)aluminum) and address the underlying spin relaxation mechanism in this system as a function of temperature, bias voltage, magnetic field and sample thickness.
An automated vessel segmentation of retinal images using multiscale vesselness
International Nuclear Information System (INIS)
Ben Abdallah, M.; Malek, J.; Tourki, R.; Krissian, K.
2011-01-01
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.
Multiscale technicolour and the Zbb-bar vertex
International Nuclear Information System (INIS)
Chong-Xing Yue; Yu-Ping Kuang; Gong-Ru Lu
1997-01-01
Correction to the Z→bb-bar branching ratio (R b ) in the multiscale walking technicolour model (MWTCM) is examined. For the original MWTCM, the correction is too large to explain the recent LEP data in most of the parameter space. We show that the branching ratio R b in the topcolour assisted MWTCM can be in agreement with the LEP data for a certain range of the parameters and the flavour diagonal ETC boson exchange gives very small contribution to the parameter T. (author)
Expected Navigation Flight Performance for the Magnetospheric Multiscale (MMS) Mission
Olson, Corwin; Wright, Cinnamon; Long, Anne
2012-01-01
The Magnetospheric Multiscale (MMS) mission consists of four formation-flying spacecraft placed in highly eccentric elliptical orbits about the Earth. The primary scientific mission objective is to study magnetic reconnection within the Earth s magnetosphere. The baseline navigation concept is the independent estimation of each spacecraft state using GPS pseudorange measurements (referenced to an onboard Ultra Stable Oscillator) and accelerometer measurements during maneuvers. State estimation for the MMS spacecraft is performed onboard each vehicle using the Goddard Enhanced Onboard Navigation System, which is embedded in the Navigator GPS receiver. This paper describes the latest efforts to characterize expected navigation flight performance using upgraded simulation models derived from recent analyses.
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...
Cheng, Anning; Xu, Kuan-Man
2015-01-01
Five-year simulation experiments with a multi-scale modeling Framework (MMF) with a advanced intermediately prognostic higher-order turbulence closure (IPHOC) in its cloud resolving model (CRM) component, also known as SPCAM-IPHOC (super parameterized Community Atmospheric Model), are performed to understand the fast tropical (30S-30N) cloud response to an instantaneous doubling of CO2 concentration with SST held fixed at present-day values. SPCAM-IPHOC has substantially improved the low-level representation compared with SPCAM. It is expected that the cloud responses to greenhouse warming in SPCAM-IPHOC is more realistic. The change of rising motion, surface precipitation, cloud cover, and shortwave and longwave cloud radiative forcing in SPCAM-IPHOC from the greenhouse warming will be presented in the presentation.
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
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.
Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling
Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.
2016-01-01
This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510
A multiscale quantum mechanics/electromagnetics method for device simulations.
Yam, ChiYung; Meng, Lingyi; Zhang, Yu; Chen, GuanHua
2015-04-07
Multiscale modeling has become a popular tool for research applying to different areas including materials science, microelectronics, biology, chemistry, etc. In this tutorial review, we describe a newly developed multiscale computational method, incorporating quantum mechanics into electronic device modeling with the electromagnetic environment included through classical electrodynamics. In the quantum mechanics/electromagnetics (QM/EM) method, the regions of the system where active electron scattering processes take place are treated quantum mechanically, while the surroundings are described by Maxwell's equations and a semiclassical drift-diffusion model. The QM model and the EM model are solved, respectively, in different regions of the system in a self-consistent manner. Potential distributions and current densities at the interface between QM and EM regions are employed as the boundary conditions for the quantum mechanical and electromagnetic simulations, respectively. The method is illustrated in the simulation of several realistic systems. In the case of junctionless field-effect transistors, transfer characteristics are obtained and a good agreement between experiments and simulations is achieved. Optical properties of a tandem photovoltaic cell are studied and the simulations demonstrate that multiple QM regions are coupled through the classical EM model. Finally, the study of a carbon nanotube-based molecular device shows the accuracy and efficiency of the QM/EM method.
Cloud Detection by Fusing Multi-Scale Convolutional Features
Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang
2018-04-01
Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
Multiscale Morphology of Nanoporous Copper Made from Intermetallic Phases
International Nuclear Information System (INIS)
Egle, Tobias; Harvard University, Cambridge, MA; Barroo, Cédric; Janvelyan, Nare; Baumgaertel, Andreas C.
2017-01-01
Many application-relevant properties of nanoporous metals critically depend on their multiscale architecture. For example, the intrinsically high step-edge density of curved surfaces at the nanoscale provides highly reactive sites for catalysis, whereas the macroscale pore and grain morphology determines the macroscopic properties, such as mass transport, electrical conductivity, or mechanical properties. Here, in this work, we systematically study the effects of alloy composition and dealloying conditions on the multiscale morphology of nanoporous copper (np-Cu) made from various commercial Zn–Cu precursor alloys. Using a combination of X-ray diffraction, electron backscatter diffraction, and focused ion beam cross-sectional analysis, our results reveal that the macroscopic grain structure of the starting alloy surprisingly survives the dealloying process, despite a change in crystal structure from body-centered cubic (Zn–Cu starting alloy) to face-centered cubic (Cu). The nanoscale structure can be controlled by the acid used for dealloying with HCl leading to a larger and more faceted ligament morphology compared to that of H_3PO_4. Finally, anhydrous ethanol dehydrogenation was used as a probe reaction to test the effect of the nanoscale ligament morphology on the apparent activation energy of the reaction.
A wavelet multiscale denoising algorithm for magnetic resonance (MR) images
International Nuclear Information System (INIS)
Yang, Xiaofeng; Fei, Baowei
2011-01-01
Based on the Radon transform, a wavelet multiscale denoising method is proposed for MR images. The approach explicitly accounts for the Rician nature of MR data. Based on noise statistics we apply the Radon transform to the original MR images and use the Gaussian noise model to process the MR sinogram image. A translation invariant wavelet transform is employed to decompose the MR 'sinogram' into multiscales in order to effectively denoise the images. Based on the nature of Rician noise we estimate noise variance in different scales. For the final denoised sinogram we apply the inverse Radon transform in order to reconstruct the original MR images. Phantom, simulation brain MR images, and human brain MR images were used to validate our method. The experiment results show the superiority of the proposed scheme over the traditional methods. Our method can reduce Rician noise while preserving the key image details and features. The wavelet denoising method can have wide applications in MRI as well as other imaging modalities
Multi-scale window specification over streaming trajectories
Directory of Open Access Journals (Sweden)
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.
Multiscale functions, scale dynamics, and applications to partial differential equations
Cresson, Jacky; Pierret, Frédéric
2016-05-01
Modeling phenomena from experimental data always begins with a choice of hypothesis on the observed dynamics such as determinism, randomness, and differentiability. Depending on these choices, different behaviors can be observed. The natural question associated to the modeling problem is the following: "With a finite set of data concerning a phenomenon, can we recover its underlying nature? From this problem, we introduce in this paper the definition of multi-scale functions, scale calculus, and scale dynamics based on the time scale calculus [see Bohner, M. and Peterson, A., Dynamic Equations on Time Scales: An Introduction with Applications (Springer Science & Business Media, 2001)] which is used to introduce the notion of scale equations. These definitions will be illustrated on the multi-scale Okamoto's functions. Scale equations are analysed using scale regimes and the notion of asymptotic model for a scale equation under a particular scale regime. The introduced formalism explains why a single scale equation can produce distinct continuous models even if the equation is scale invariant. Typical examples of such equations are given by the scale Euler-Lagrange equation. We illustrate our results using the scale Newton's equation which gives rise to a non-linear diffusion equation or a non-linear Schrödinger equation as asymptotic continuous models depending on the particular fractional scale regime which is considered.
Multiscale high-order/low-order (HOLO) algorithms and applications
International Nuclear Information System (INIS)
Chacón, L.; Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W.; Willert, J.A.; Womeldorff, G.
2017-01-01
We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.
Dynamics of a neural system with a multiscale architecture
Breakspear, Michael; Stam, Cornelis J
2005-01-01
The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448
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.
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 modeling for sustainable chemical production.
Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J
2013-09-01
With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Multiscale spatial and temporal estimation of the b-value
García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.
2017-12-01
The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.
Refined generalized multiscale entropy analysis for physiological signals
Liu, Yunxiao; Lin, Youfang; Wang, Jing; Shang, Pengjian
2018-01-01
Multiscale entropy analysis has become a prevalent complexity measurement and been successfully applied in various fields. However, it only takes into account the information of mean values (first moment) in coarse-graining procedure. Then generalized multiscale entropy (MSEn) considering higher moments to coarse-grain a time series was proposed and MSEσ2 has been implemented. However, the MSEσ2 sometimes may yield an imprecise estimation of entropy or undefined entropy, and reduce statistical reliability of sample entropy estimation as scale factor increases. For this purpose, we developed the refined model, RMSEσ2, to improve MSEσ2. Simulations on both white noise and 1 / f noise show that RMSEσ2 provides higher entropy reliability and reduces the occurrence of undefined entropy, especially suitable for short time series. Besides, we discuss the effect on RMSEσ2 analysis from outliers, data loss and other concepts in signal processing. We apply the proposed model to evaluate the complexity of heartbeat interval time series derived from healthy young and elderly subjects, patients with congestive heart failure and patients with atrial fibrillation respectively, compared to several popular complexity metrics. The results demonstrate that RMSEσ2 measured complexity (a) decreases with aging and diseases, and (b) gives significant discrimination between different physiological/pathological states, which may facilitate clinical application.
The optimal filtering of a class of dynamic multiscale systems
Institute of Scientific and Technical Information of China (English)
PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai
2004-01-01
This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.
Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems
Stanton, L. G.; Glosli, J. N.; Murillo, M. S.
2018-04-01
Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.
Multiscale modelling approaches for assessing cosmetic ingredients safety.
Bois, Frédéric Y; Ochoa, Juan G Diaz; Gajewska, Monika; Kovarich, Simona; Mauch, Klaus; Paini, Alicia; Péry, Alexandre; Benito, Jose Vicente Sala; Teng, Sophie; Worth, Andrew
2017-12-01
The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Multiscale high-order/low-order (HOLO) algorithms and applications
Energy Technology Data Exchange (ETDEWEB)
Chacón, L., E-mail: chacon@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Willert, J.A. [Institute for Defense Analyses, Alexandria, VA 22311 (United States); Womeldorff, G. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2017-02-01
We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.
Multiscale CNNs for Brain Tumor Segmentation and Diagnosis
Directory of Open Access Journals (Sweden)
Liya Zhao
2016-01-01
Full Text Available 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.
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.
International Nuclear Information System (INIS)
Tang Shaojie; Tang Xiangyang
2012-01-01
Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation of interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of “salt-and-pepper” noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain
Aerosol-cloud interactions in a multi-scale modeling framework
Lin, G.; Ghan, S. J.
2017-12-01
Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the
Bednarcyk, Brett A.; Arnold, Steven M.
2012-01-01
A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.
DEFF Research Database (Denmark)
Zhukovsky, Sergei; Orlov, Alexey A.; Babicheva, Viktoriia E.
2014-01-01
) on a larger, wavelength scale, the propagation of volume plasmon polaritons in the resulting multiscale hyperbolic metamaterials is subject to photonic-band-gap phenomena. A great degree of control over such plasmons can be exerted by varying the superstructure geometry. When this geometry is periodic, stop......, fractal Cantor-like multiscale metamaterials are found to exhibit characteristic self-similar spectral signatures in the volume plasmonic band. Multiscale hyperbolic metamaterials are shown to be a promising platform for large-wave-vector bulk plasmonic waves, whether they are considered for use as a kind...
Wilkinson, Mark; Owen, Gareth; Geris, Josie; Soulsby, Chris; Quinn, Paul
2015-04-01
Many communities across the world face the increasing challenge of balancing water quantity and quality issues with accommodating new growth and urban development. Urbanisation is typically associated with detrimental changes in water quality, sediment delivery, and effects on water storage and flow pathways (e.g. increases in flooding). In particular for mixed rural and urban catchments where the spatio-temporal variability of hydrological responses is high, there remains a key research challenge in evaluating the timing and magnitude of storage and flow pathways at multiple scales. This is of crucial importance for appropriate catchment management, for example to aid the design of Green Infrastructure (GI) to mitigate the risk of flooding, among other multiple benefits. The aim of this work was to (i) explore spatio-temporal storm runoff generation characteristics in multi-scale catchment experiments that contain rural and urban land use zones, and (ii) assess the (preliminary) impact of Sustainable Drainage (SuDs) as GI on high flow and flood characteristics. Our key research catchment, the Ouseburn in Northern England (55km2), has rural headwaters (15%) and an urban zone (45%) concentrated in the lower catchment area. There is an intermediate and increasingly expanding peri-urban zone (currently 40%), which is defined here as areas where rural and urban features coexist, alongside GIs. Such a structure is typical for most catchments with urban developments. We monitored spatial precipitation and multiscale nested (five gauges) runoff response, in addition to the storage dynamics in GIs for a period of 6 years (2007-2013). For a range of events, we examined the multiscale nested runoff characteristics (lag time and magnitude) of the rural and urban flow components, assessed how these integrated with changing land use and increasing scale, and discussed the implications for flood management in the catchment. The analyses indicated three distinctly different
EPOS-WP16: A coherent and collaborative network of Solid Earth Multi-scale laboratories
Calignano, Elisa; Rosenau, Matthias; Lange, Otto; Spiers, Chris; Willingshofer, Ernst; Drury, Martyn; van Kan-Parker, Mirjam; Elger, Kirsten; Ulbricht, Damian; Funiciello, Francesca; Trippanera, Daniele; Sagnotti, Leonardo; Scarlato, Piergiorgio; Tesei, Telemaco; Winkler, Aldo
2017-04-01
Laboratory facilities are an integral part of Earth Science research. The diversity of methods employed in such infrastructures reflects the multi-scale nature of the Earth system and is essential for the understanding of its evolution, for the assessment of geo-hazards and for the sustainable exploitation of geo-resources. In the frame of EPOS (European Plate Observing System), the Working Package 16 represents a developing community of European Geoscience Multi-scale laboratories. The participant and collaborating institutions (Utrecht University, GFZ, RomaTre University, INGV, NERC, CSIC-ICTJA, CNRS, LMU, C4G-UBI, ETH, CNR*) embody several types of laboratory infrastructures, engaged in different fields of interest of Earth Science: from high temperature and pressure experimental facilities, to electron microscopy, micro-beam analysis, analogue tectonic and geodynamic modelling and paleomagnetic laboratories. The length scales encompassed by these infrastructures range from the nano- and micrometre levels (electron microscopy and micro-beam analysis) to the scale of experiments on centimetres-sized samples, and to analogue model experiments simulating the reservoir scale, the basin scale and the plate scale. The aim of WP16 is to provide two services by the year 2019: first, providing virtual access to data from laboratories (data service) and, second, providing physical access to laboratories (transnational access, TNA). Regarding the development of a data service, the current status is such that most data produced by the various laboratory centres and networks are available only in limited "final form" in publications, many data remain inaccessible and/or poorly preserved. Within EPOS the TCS Multi-scale laboratories is collecting and harmonizing available and emerging laboratory data on the properties and process controlling rock system behaviour at all relevant scales, in order to generate products accessible and interoperable through services for supporting
A multi-scale correlative investigation of ductile fracture
International Nuclear Information System (INIS)
Daly, M.; Burnett, T.L.; Pickering, E.J.; Tuck, O.C.G.; Léonard, F.; Kelley, R.; Withers, P.J.; Sherry, A.H.
2017-01-01
The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 μm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It is found that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 μm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 μm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN
Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
International Nuclear Information System (INIS)
Kovalenko, Andriy
2014-01-01
Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology
Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems
Kovalenko, Andriy
2014-08-01
Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology
A bidirectional coupling procedure applied to multiscale respiratory modeling
Energy Technology Data Exchange (ETDEWEB)
Kuprat, A.P., E-mail: andrew.kuprat@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Kabilan, S., E-mail: senthil.kabilan@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Carson, J.P., E-mail: james.carson@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Corley, R.A., E-mail: rick.corley@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States); Einstein, D.R., E-mail: daniel.einstein@pnnl.gov [Fundamental and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA (United States)
2013-07-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Multiscale study on stochastic reconstructions of shale samples
Lili, J.; Lin, M.; Jiang, W. B.
2016-12-01
Shales are known to have multiscale pore systems, composed of macroscale fractures, micropores, and nanoscale pores within gas or oil-producing organic material. Also, shales are fissile and laminated, and the heterogeneity in horizontal is quite different from that in vertical. Stochastic reconstructions are extremely useful in situations where three-dimensional information is costly and time consuming. Thus the purpose of our paper is to reconstruct stochastically equiprobable 3D models containing information from several scales. In this paper, macroscale and microscale images of shale structure in the Lower Silurian Longmaxi are obtained by X-ray microtomography and nanoscale images are obtained by scanning electron microscopy. Each image is representative for all given scales and phases. Especially, the macroscale is four times coarser than the microscale, which in turn is four times lower in resolution than the nanoscale image. Secondly, the cross correlation-based simulation method (CCSIM) and the three-step sampling method are combined together to generate stochastic reconstructions for each scale. It is important to point out that the boundary points of pore and matrix are selected based on multiple-point connectivity function in the sampling process, and thus the characteristics of the reconstructed image can be controlled indirectly. Thirdly, all images with the same resolution are developed through downscaling and upscaling by interpolation, and then we merge multiscale categorical spatial data into a single 3D image with predefined resolution (the microscale image). 30 realizations using the given images and the proposed method are generated. The result reveals that the proposed method is capable of preserving the multiscale pore structure, both vertically and horizontally, which is necessary for accurate permeability prediction. The variogram curves and pore-size distribution for both original 3D sample and the generated 3D realizations are compared
A bidirectional coupling procedure applied to multiscale respiratory modeling
Kuprat, A. P.; Kabilan, S.; Carson, J. P.; Corley, R. A.; Einstein, D. R.
2013-07-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton's method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a "pressure-drop" residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Adaptive Multiscale Modeling of Geochemical Impacts on Fracture Evolution
Molins, S.; Trebotich, D.; Steefel, C. I.; Deng, H.
2016-12-01
Understanding fracture evolution is essential for many subsurface energy applications, including subsurface storage, shale gas production, fracking, CO2 sequestration, and geothermal energy extraction. Geochemical processes in particular play a significant role in the evolution of fractures through dissolution-driven widening, fines migration, and/or fracture sealing due to precipitation. One obstacle to understanding and exploiting geochemical fracture evolution is that it is a multiscale process. However, current geochemical modeling of fractures cannot capture this multi-scale nature of geochemical and mechanical impacts on fracture evolution, and is limited to either a continuum or pore-scale representation. Conventional continuum-scale models treat fractures as preferential flow paths, with their permeability evolving as a function (often, a cubic law) of the fracture aperture. This approach has the limitation that it oversimplifies flow within the fracture in its omission of pore scale effects while also assuming well-mixed conditions. More recently, pore-scale models along with advanced characterization techniques have allowed for accurate simulations of flow and reactive transport within the pore space (Molins et al., 2014, 2015). However, these models, even with high performance computing, are currently limited in their ability to treat tractable domain sizes (Steefel et al., 2013). Thus, there is a critical need to develop an adaptive modeling capability that can account for separate properties and processes, emergent and otherwise, in the fracture and the rock matrix at different spatial scales. Here we present an adaptive modeling capability that treats geochemical impacts on fracture evolution within a single multiscale framework. Model development makes use of the high performance simulation capability, Chombo-Crunch, leveraged by high resolution characterization and experiments. The modeling framework is based on the adaptive capability in Chombo
A bidirectional coupling procedure applied to multiscale respiratory modeling
International Nuclear Information System (INIS)
Kuprat, A.P.; Kabilan, S.; Carson, J.P.; Corley, R.A.; Einstein, D.R.
2013-01-01
In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFDs) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the modified Newton’s method with nonlinear Krylov accelerator developed by Carlson and Miller [1], Miller [2] and Scott and Fenves [3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a “pressure-drop” residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD–ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural
Siddiq, A.; El Sayed, Tamer S.
2013-01-01
We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline
Heat and mass transfer intensification and shape optimization a multi-scale approach
2013-01-01
Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes. A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...
Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics
Tavener, Simon; Wildey, Tim
2013-01-01
In this paper we derive a posteriori error estimates for linear functionals of the solution to an elliptic problem discretized using a multiscale nonoverlapping domain decomposition method. The error estimates are based on the solution
Multiscale Lattice Boltzmann method for flow simulations in highly heterogenous porous media
Li, Jun; Brown, Donald; Calo, Victor M.; Efendiev, Yalchin R.; Illiev, Oleg
2013-01-01
.g., water and oil) are modeled using cohesive or repulsive forces, respectively. The relative permeability can be computed using pore-scale simulations and seamlessly applied for intermediate and Darcy-scale simulations. A multiscale LBM that can reduce
Jiang, Lijian; Efendiev, Yalchin; Mishev, IIya
2009-01-01
The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information
Energy Technology Data Exchange (ETDEWEB)
Dorland, William [University of Maryland
2014-11-18
The Center for Multiscale Plasma Dynamics (CMPD) was a five-year Fusion Science Center. The University of Maryland (UMD) and UCLA were the host universities. This final technical report describes the physics results from the UMD CMPD.
Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.
Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di
2018-03-06
Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.
A constrained approach to multiscale stochastic simulation of chemically reacting systems
Cotter, Simon L.; Zygalakis, Konstantinos C.; Kevrekidis, Ioannis G.; Erban, Radek
2011-01-01
Stochastic simulation of coupled chemical reactions is often computationally intensive, especially if a chemical system contains reactions occurring on different time scales. In this paper, we introduce a multiscale methodology suitable to address
Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process
Park, J. B.; Yoo, J.-H.; Grigoropoulos, C. P.
2012-01-01
A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes
A spectral multiscale hybridizable discontinuous Galerkin method for second order elliptic problems
Efendiev, Yalchin R.
2015-08-01
We design a multiscale model reduction framework within the hybridizable discontinuous Galerkin finite element method. Our approach uses local snapshot spaces and local spectral decomposition following the concept of Generalized Multiscale Finite Element Methods. We propose several multiscale finite element spaces on the coarse edges that provide a reduced dimensional approximation for numerical traces within the HDG framework. We provide a general framework for systematic construction of multiscale trace spaces. Using local snapshots, we avoid high dimensional representation of trace spaces and use some local features of the solution space in constructing a low dimensional trace space. We investigate the solvability and numerically study the performance of the proposed method on a representative number of numerical examples.
A spectral multiscale hybridizable discontinuous Galerkin method for second order elliptic problems
Efendiev, Yalchin R.; Lazarov, Raytcho D.; Moon, Minam; Shi, Ke
2015-01-01
of multiscale trace spaces. Using local snapshots, we avoid high dimensional representation of trace spaces and use some local features of the solution space in constructing a low dimensional trace space. We investigate the solvability and numerically study
The Feasibility of Multiscale Modeling of Tunnel Fires Using FDS 6
DEFF Research Database (Denmark)
Vermesi, Izabella; Colella, Francesco; Rein, Guillermo
2014-01-01
The HVAC component of FDS 6 was used to divide a 1.2km tunnel into a 3D near fire area and a 1D area further away from the fire in order to investigate the feasibility of multiscale modeling of tunnel fires with this new feature in FDS. The two sub-models were coupled directly. The results were...... compared with reference works on multiscale modeling and the outcome is considered positive, with a deviation of less than 5% in magnitude of relevant parameters, yet with a significant reduction of the simulation runtime. As such, the multiscale method is deemed feasible for simulating tunnel fires in FDS......6. However, the simplifications that are made in this work require further investigation in order to take full advantage of the potential of this computational method. INTRODUCTION Multiscale modeling for tunnel flows and fires has previously been studied using RANS general purpose CFD software...
Multiscale aspects of the visual system and their use for scale invariant object recognition
Petkov, N; vanDeemter, J; Karsch, F; Monien, B; Satz, H
1997-01-01
Psychophysical, neuroanatomical and neurophysiological evidence for multiscale aspects of the visual system is considered. The stack model and its relation to the image pyramid are discussed. The results of a straightforward implementation on a parallel supercomputer are presented. The high
Definability and stability of multiscale decompositions for manifold-valued data
Grohs, Philipp; Wallner, Johannes
2012-01-01
are based on upscaling operators which are either interpolating or midpoint-interpolating. For definable multiscale decompositions we obtain a stability result. © 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Farrell, Patricio; Pestana, Jennifer
2015-01-01
. However, the benefit of a guaranteed symmetric positive definite block system comes at a high computational cost. This cost can be alleviated somewhat by considering compactly supported RBFs and a multiscale technique. But the condition number and sparsity
Multiscale modeling of nerve agent hydrolysis mechanisms: a tale of two Nobel Prizes
Field, Martin J.; Wymore, Troy W.
2014-10-01
The 2013 Nobel Prize in Chemistry was awarded for the development of multiscale models for complex chemical systems, whereas the 2013 Peace Prize was given to the Organisation for the Prohibition of Chemical Weapons for their efforts to eliminate chemical warfare agents. This review relates the two by introducing the field of multiscale modeling and highlighting its application to the study of the biological mechanisms by which selected chemical weapon agents exert their effects at an atomic level.
A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media
Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.
2017-12-01
Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.
Multiscale Space-Time Computational Methods for Fluid-Structure Interactions
2015-09-13
thermo-fluid analysis of a ground vehicle and its tires ST-SI Computational Analysis of a Vertical - Axis Wind Turbine We have successfully...of a vertical - axis wind turbine . Multiscale Compressible-Flow Computation with Particle Tracking We have successfully tested the multiscale...Tezduyar, Spenser McIntyre, Nikolay Kostov, Ryan Kolesar, Casey Habluetzel. Space–time VMS computation of wind - turbine rotor and tower aerodynamics
Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests
2016-02-02
interfacial fracture ) in CFRP was recently found in the fuselages of Dreamliner 787, and two types of cracks were found in the rib feet brackets...AFRL-AFOSR-UK-TR-2016-0003 Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests Zhenjun Yang UNIVERSITY OF MANCHESTER...Multiscale Stochastic Fracture Mechanics of Composites Informed by In-situ XCT Tests 5a. CONTRACT NUMBER EOARD 12-2100 5b. GRANT NUMBER F8655-12-1
Definability and stability of multiscale decompositions for manifold-valued data
Grohs, Philipp
2012-06-01
We discuss multiscale representations of discrete manifold-valued data. As it turns out that we cannot expect general manifold analogs of biorthogonal wavelets to possess perfect reconstruction, we focus our attention on those constructions which are based on upscaling operators which are either interpolating or midpoint-interpolating. For definable multiscale decompositions we obtain a stability result. © 2012 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Multi-Scale Models for the Scale Interaction of Organized Tropical Convection
Yang, Qiu
Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.
Multiscale vision model for event detection and reconstruction in two-photon imaging data
DEFF Research Database (Denmark)
Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke
2014-01-01
on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....
Multiscale 3D characterization with dark-field x-ray microscopy
DEFF Research Database (Denmark)
Simons, Hugh; Jakobsen, Anders Clemen; Ahl, Sonja Rosenlund
2016-01-01
Dark-field x-ray microscopy is a new way to three-dimensionally map lattice strain and orientation in crystalline matter. It is analogous to dark-field electron microscopy in that an objective lens magnifies diffracting features of the sample; however, the use of high-energy synchrotron x-rays me......, multiscale phenomena in situ is a key step toward formulating and validating multiscale models that account for the entire heterogeneity of materials....
Activation of the operational ecohydrodynamic model (3D CEMBS - the ecosystem module
Directory of Open Access Journals (Sweden)
Jaromir Jakacki
2013-08-01
Full Text Available The paper describes the ecohydrodynamic predictive model - the ecosystem module - for assessing the state of the Baltic marine environment and the Baltic ecosystem. The Baltic Sea model 3D CEMBS (the Coupled Ecosystem Model of the Baltic Sea is based on the Community Earth System Model, which was adopted for the Baltic Sea as a coupled sea-ice-ecosystem model. The 3D CEMBS model uses: (i hydrodynamic equations describing water movement, (ii thermodynamic equations, (iii equations describing the concentration distribution of chemical variables in the sea, and (iv equations describing the exchange of matter between individual groups of organisms and their environment that make allowance for the kinetics of biochemical processes. The ecosystem model consists of 11 main components: three classes of phytoplankton (small phytoplankton, large phytoplankton represented mainly by diatoms and summer species, mostly cyanobacteria expressed in units of carbon and chlorophyll a as separate variables, zooplankton, pelagic detritus, dissolved oxygen and nutrients (nitrate, ammonium, phosphate and silicate. In operational mode, 48-hour atmospheric forecasts provided by the UM model from the Interdisciplinary Centre for Mathematical and Computational Modelling of Warsaw University (ICM are used. All model forecasts are available on the website http://deep.iopan.gda.pl/CEMBaltic/new_lay/index.php. The results presented in this paper show that the 3D CEMBS model is operating correctly.
Multiscale Multiphysics Developments for Accident Tolerant Fuel Concepts
International Nuclear Information System (INIS)
Gamble, K. A.; Hales, J. D.; Yu, J.; Zhang, Y.; Bai, X.; Andersson, D.; Patra, A.; Wen, W.; Tome, C.; Baskes, M.; Martinez, E.; Stanek, C. R.; Miao, Y.; Ye, B.; Hofman, G. L.; Yacout, A. M.; Liu, W.
2015-01-01
U 3 Si 2 and iron-chromium-aluminum (Fe-Cr-Al) alloys are two of many proposed accident-tolerant fuel concepts for the fuel and cladding, respectively. The behavior of these materials under normal operating and accident reactor conditions is not well known. As part of the Department of Energy's Accident Tolerant Fuel High Impact Problem program significant work has been conducted to investigate the U 3 Si 2 and FeCrAl behavior under reactor conditions. This report presents the multiscale and multiphysics effort completed in fiscal year 2015. The report is split into four major categories including Density Functional Theory Developments, Molecular Dynamics Developments, Mesoscale Developments, and Engineering Scale Developments. The work shown here is a compilation of a collaborative effort between Idaho National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory and Anatech Corp.
Cellular potts models multiscale extensions and biological applications
Scianna, Marco
2013-01-01
A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...
A Multi-Scale Settlement Matching Algorithm Based on ARG
Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia
2016-06-01
Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Critical behavior of the contact process in a multiscale network
Ferreira, Silvio C.; Martins, Marcelo L.
2007-09-01
Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barabási-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak’s duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.
Detecting fine scratches on smooth surfaces with multiscale wavelet representation
International Nuclear Information System (INIS)
Yao, Li; Wan, Yan; Yao, Ming; Xu, Bugao
2012-01-01
This paper presents a set of image-processing algorithms for automatic detection of fine scratches on smooth surfaces, such as automobile paint surfaces. The scratches to be detected have random directions, inconspicuous gray levels and background noise. The multiscale wavelet transform was used to extract texture features, and a controlled edge fusion model was employed to merge the detailed (horizontal, vertical and diagonal) wavelet coefficient maps. Based on the fused detail map, multivariate statistics were applied to synthesize features in multiple scales and directions, and an optimal threshold was set to separate scratches from the background. The experimental results of 24 automobile paint surface showed that the presented algorithms can effectively suppress background noise and detect scratches accurately. (paper)
Correlations of multiscale entropy in the FX market
Stosic, Darko; Stosic, Dusan; Ludermir, Teresa; Stosic, Tatijana
2016-09-01
The regularity of price fluctuations in exchange rates plays a crucial role in FX market dynamics. Distinct variations in regularity arise from economic, social and political events, such as interday trading and financial crisis. This paper applies a multiscale time-dependent entropy method on thirty-three exchange rates to analyze price fluctuations in the FX. Correlation matrices of entropy values, termed entropic correlations, are in turn used to describe global behavior of the market. Empirical results suggest a weakly correlated market with pronounced collective behavior at bi-weekly trends. Correlations arise from cycles of low and high regularity in long-term trends. Eigenvalues of the correlation matrix also indicate a dominant European market, followed by shifting American, Asian, African, and Pacific influences. As a result, we find that entropy is a powerful tool for extracting important information from the FX market.
Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics
Directory of Open Access Journals (Sweden)
Gonzalo Bailador del Pozo
2011-11-01
Full Text Available 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.
Framework for adaptive multiscale analysis of nonhomogeneous point processes.
Helgason, Hannes; Bartroff, Jay; Abry, Patrice
2011-01-01
We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.
Generalized multiscale finite element methods. nonlinear elliptic equations
Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian; Presho, Michael
2013-01-01
In this paper we use the Generalized Multiscale Finite Element Method (GMsFEM) framework, introduced in [26], in order to solve nonlinear elliptic equations with high-contrast coefficients. The proposed solution method involves linearizing the equation so that coarse-grid quantities of previous solution iterates can be regarded as auxiliary parameters within the problem formulation. With this convention, we systematically construct respective coarse solution spaces that lend themselves to either continuous Galerkin (CG) or discontinuous Galerkin (DG) global formulations. Here, we use Symmetric Interior Penalty Discontinuous Galerkin approach. Both methods yield a predictable error decline that depends on the respective coarse space dimension, and we illustrate the effectiveness of the CG and DG formulations by offering a variety of numerical examples. © 2014 Global-Science Press.
An augmented Lagrangian multi-scale dictionary learning algorithm
Directory of Open Access Journals (Sweden)
Ye Meng
2011-01-01
Full Text Available Abstract Learning overcomplete dictionaries for sparse signal representation has become a hot topic fascinated by many researchers in the recent years, while most of the existing approaches have a serious problem that they always lead to local minima. In this article, we present a novel augmented Lagrangian multi-scale dictionary learning algorithm (ALM-DL, which is achieved by first recasting the constrained dictionary learning problem into an AL scheme, and then updating the dictionary after each inner iteration of the scheme during which majorization-minimization technique is employed for solving the inner subproblem. Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima. Numerical tests for synthetic data and denoising applications on real images demonstrate the superior performance of the proposed approach.
Multi-scale Dynamical Processes in Space and Astrophysical Plasmas
Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research
2012-01-01
Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...
Multiscale deep features learning for land-use scene recognition
Yuan, Baohua; Li, Shijin; Li, Ning
2018-01-01
The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.
Multiscale modelling of hydrogen behaviour on beryllium (0001 surface
Directory of Open Access Journals (Sweden)
Ch. Stihl
2016-12-01
Full Text Available Beryllium is proposed to be a neutron multiplier and plasma facing material in future fusion devices. Therefore, it is crucial to acquire an understanding of the microscopic mechanisms of tritium accumulation and release as a result of transmutation processes that Be undergoes under neutron irradiation. A multiscale simulation of ad- and desorption of hydrogen isotopes on the beryllium (0001 surface is developed. It consists of ab initio calculations of certain H adsorption configurations, a suitable cluster expansion approximating the energies of arbitrary configurations, and a kinetic Monte Carlo method for dynamic simulations of adsorption and desorption. The processes implemented in the kinetic Monte Carlo simulation are deduced from further ab initio calculations comprising both, static relaxation as well as molecular dynamics runs. The simulation is used to reproduce experimental data and the results are compared and discussed. Based on the observed results, proposals for a refined model are made.
Model-to-model interface for multiscale materials modeling
Energy Technology Data Exchange (ETDEWEB)
Antonelli, Perry Edward [Iowa State Univ., Ames, IA (United States)
2017-12-17
A low-level model-to-model interface is presented that will enable independent models to be linked into an integrated system of models. The interface is based on a standard set of functions that contain appropriate export and import schemas that enable models to be linked with no changes to the models themselves. These ideas are presented in the context of a specific multiscale material problem that couples atomistic-based molecular dynamics calculations to continuum calculations of fluid ow. These simulations will be used to examine the influence of interactions of the fluid with an adjacent solid on the fluid ow. The interface will also be examined by adding it to an already existing modeling code, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and comparing it with our own molecular dynamics code.
All-Particle Multiscale Computation of Hypersonic Rarefied Flow
Jun, E.; Burt, J. M.; Boyd, I. D.
2011-05-01
This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.
HAM-Based Adaptive Multiscale Meshless Method for Burgers Equation
Directory of Open Access Journals (Sweden)
Shu-Li Mei
2013-01-01
Full Text Available Based on the multilevel interpolation theory, we constructed a meshless adaptive multiscale interpolation operator (MAMIO with the radial basis function. Using this operator, any nonlinear partial differential equations such as Burgers equation can be discretized adaptively in physical spaces as a nonlinear matrix ordinary differential equation. In order to obtain the analytical solution of the system of ODEs, the homotopy analysis method (HAM proposed by Shijun Liao was developed to solve the system of ODEs by combining the precise integration method (PIM which can be employed to get the analytical solution of linear system of ODEs. The numerical experiences show that HAM is not sensitive to the time step, and so the arithmetic error is mainly derived from the discrete in physical space.
Plant trait detection with multi-scale spectrometry
Gamon, J. A.; Wang, R.
2017-12-01
Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.
Multiscale Computation. Needs and Opportunities for BER Science
Energy Technology Data Exchange (ETDEWEB)
Scheibe, Timothy D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2015-01-01
The Environmental Molecular Sciences Laboratory (EMSL), a scientific user facility managed by Pacific Northwest National Laboratory for the U.S. Department of Energy, Office of Biological and Environmental Research (BER), conducted a one-day workshop on August 26, 2014 on the topic of “Multiscale Computation: Needs and Opportunities for BER Science.” Twenty invited participants, from various computational disciplines within the BER program research areas, were charged with the following objectives; Identify BER-relevant models and their potential cross-scale linkages that could be exploited to better connect molecular-scale research to BER research at larger scales and; Identify critical science directions that will motivate EMSL decisions regarding future computational (hardware and software) architectures.
Multi-scale evaluations of submarine groundwater discharge
Directory of Open Access Journals (Sweden)
M. Taniguchi
2015-03-01
Full Text Available Multi-scale evaluations of submarine groundwater discharge (SGD have been made in Saijo, Ehime Prefecture, Shikoku Island, Japan, by using seepage meters for point scale, 222Rn tracer for point and coastal scales, and a numerical groundwater model (SEAWAT for coastal and basin scales. Daily basis temporal changes in SGD are evaluated by continuous seepage meter and 222Rn mooring measurements, and depend on sea level changes. Spatial evaluations of SGD were also made by 222Rn along the coast in July 2010 and November 2011. The area with larger 222Rn concentration during both seasons agreed well with the area with larger SGD calculated by 3D groundwater numerical simulations.
A Multi-Scale Settlement Matching Algorithm Based on ARG
Directory of Open Access Journals (Sweden)
H. Yue
2016-06-01
Full Text Available Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.
Pricing perpetual American options under multiscale stochastic elasticity of variance
International Nuclear Information System (INIS)
Yoon, Ji-Hun
2015-01-01
Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk
Stochastic scalar mixing models accounting for turbulent frequency multiscale fluctuations
International Nuclear Information System (INIS)
Soulard, Olivier; Sabel'nikov, Vladimir; Gorokhovski, Michael
2004-01-01
Two new scalar micromixing models accounting for a turbulent frequency scale distribution are investigated. These models were derived by Sabel'nikov and Gorokhovski [Second International Symposium on Turbulence and Shear FLow Phenomena, Royal Institute of technology (KTH), Stockholm, Sweden, June 27-29, 2001] using a multiscale extension of the classical interaction by exchange with the mean (IEM) and Langevin models. They are, respectively, called Extended IEM (EIEM) and Extended Langevin (ELM) models. The EIEM and ELM models are tested against DNS results in the case of the decay of a homogeneous scalar field in homogeneous turbulence. This comparison leads to a reformulation of the law governing the mixing frequency distribution. Finally, the asymptotic behaviour of the modeled PDF is discussed
Multiscale experimental mechanics of hierarchical carbon-based materials.
Espinosa, Horacio D; Filleter, Tobin; Naraghi, Mohammad
2012-06-05
Investigation of the mechanics of natural materials, such as spider silk, abalone shells, and bone, has provided great insight into the design of materials that can simultaneously achieve high specific strength and toughness. Research has shown that their emergent mechanical properties are owed in part to their specific self-organization in hierarchical molecular structures, from nanoscale to macroscale, as well as their mixing and bonding. To apply these findings to manmade materials, researchers have devoted significant efforts in developing a fundamental understanding of multiscale mechanics of materials and its application to the design of novel materials with superior mechanical performance. These efforts included the utilization of some of the most promising carbon-based nanomaterials, such as carbon nanotubes, carbon nanofibers, and graphene, together with a variety of matrix materials. At the core of these efforts lies the need to characterize material mechanical behavior across multiple length scales starting from nanoscale characterization of constituents and their interactions to emerging micro- and macroscale properties. In this report, progress made in experimental tools and methods currently used for material characterization across multiple length scales is reviewed, as well as a discussion of how they have impacted our current understanding of the mechanics of hierarchical carbon-based materials. In addition, insight is provided into strategies for bridging experiments across length scales, which are essential in establishing a multiscale characterization approach. While the focus of this progress report is in experimental methods, their concerted use with theoretical-computational approaches towards the establishment of a robust material by design methodology is also discussed, which can pave the way for the development of novel materials possessing unprecedented mechanical properties. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Multiscale estimation of excess mass from gravity data
Castaldo, Raffaele; Fedi, Maurizio; Florio, Giovanni
2014-06-01
We describe a multiscale method to estimate the excess mass of gravity anomaly sources, based on the theory of source moments. Using a multipole expansion of the potential field and considering only the data along the vertical direction, a system of linear equations is obtained. The choice of inverting data along a vertical profile can help us to reduce the interference effects due to nearby anomalies and will allow a local estimate of the source parameters. A criterion is established allowing the selection of the optimal highest altitude of the vertical profile data and truncation order of the series expansion. The inversion provides an estimate of the total anomalous mass and of the depth to the centre of mass. The method has several advantages with respect to classical methods, such as the Gauss' method: (i) we need just a 1-D inversion to obtain our estimates, being the inverted data sampled along a single vertical profile; (ii) the resolution may be straightforward enhanced by using vertical derivatives; (iii) the centre of mass is also estimated, besides the excess mass; (iv) the method is very robust versus noise; (v) the profile may be chosen in such a way to minimize the effects from interfering anomalies or from side effects due to the a limited area extension. The multiscale estimation of excess mass method can be successfully used in various fields of application. Here, we analyse the gravity anomaly generated by a sulphide body in the Skelleftea ore district, North Sweden, obtaining source mass and volume estimates in agreement with the known information. We show also that these estimates are substantially improved with respect to those obtained with the classical approach.
Multiscale modeling of alloy solidification using a database approach
Tan, Lijian; Zabaras, Nicholas
2007-11-01
sample problems. The efficiency of the proposed multiscale framework is demonstrated with numerical examples that consider a large number of crystals. A computationally intensive fully-resolved microscale analysis is also performed to evaluate the accuracy of the multiscale framework.
Big data-enabled multiscale serviceability analysis for aging bridges☆
Directory of Open Access Journals (Sweden)
Yu Liang
2016-08-01
Full Text Available This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge serviceability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method (e.g., association rule learning or structural mechanics modeling and simulation.
What is at stake in multi-scale approaches
International Nuclear Information System (INIS)
Jamet, Didier
2008-01-01
Full text of publication follows: Multi-scale approaches amount to analyzing physical phenomena at small space and time scales in order to model their effects at larger scales. This approach is very general in physics and engineering; one of the best examples of success of this approach is certainly statistical physics that allows to recover classical thermodynamics and to determine the limits of application of classical thermodynamics. Getting access to small scale information aims at reducing the models' uncertainty but it has a cost: fine scale models may be more complex than larger scale models and their resolution may require the development of specific and possibly expensive methods, numerical simulation techniques and experiments. For instance, in applications related to nuclear engineering, the application of computational fluid dynamics instead of cruder models is a formidable engineering challenge because it requires resorting to high performance computing. Likewise, in two-phase flow modeling, the techniques of direct numerical simulation, where all the interfaces are tracked individually and where all turbulence scales are captured, are getting mature enough to be considered for averaged modeling purposes. However, resolving small scale problems is a necessary step but it is not sufficient in a multi-scale approach. An important modeling challenge is to determine how to treat small scale data in order to get relevant information for larger scale models. For some applications, such as single-phase turbulence or transfers in porous media, this up-scaling approach is known and is now used rather routinely. However, in two-phase flow modeling, the up-scaling approach is not as mature and specific issues must be addressed that raise fundamental questions. This will be discussed and illustrated. (author)
Toward a global multi-scale heliophysics observatory
Semeter, J. L.
2017-12-01
We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.
ANALYSIS/MODEL COVER SHEET, MULTISCALE THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
Buscheck, T.A.
2001-01-01
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 andO 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 impact of fuel consumption on air quality
Energy Technology Data Exchange (ETDEWEB)
Hidy, G.M. [Envair/Aerochem, Placitas, NM (USA)
2002-04-01
Energy production from combustion of fossil fuels tends to dominate the emissions of criteria pollutants. Emissions derive both from large stationary sources with tall stacks such as fossil-fuelled power plants, and from the ground level use of fuels in transportation. Management of these sources presents a challenge in the light of multi-scale processes that influence ambient concentration and exposure patterns. Directly emitted pollutants and those resulting from atmospheric chemistry, like O{sub 3} and sulfate, nitrate and some organic material in fine particles, are affected by phenomena extending over a range of less than a meter to 10{sup 7} meters in spatial scale, and minutes to many years in temporal scale. Their environmental effects have an analogous wide range of descriptive spatial and temporal scale. Pollution phenomena can be thought of in terms of three major groupings: neighbourhood - urban, regional, and continental - global. Currently, decision-makers are developing emission reduction strategies that conceptually integrate considerations over this entire range of scales. In keeping with conceptual integration, recent studies and analyses are bridging different spatial and temporal scales in observations and in mathematical descriptions. Some examples of contemporary issues falling within different scales are described that illustrate approaches to add insight for developing regulatory strategies. A key element in the technical approaches is the application of air quality and exposure modeling using spatially nested descriptions of atmospheric phenomena. The reliability of multi-scale models remains a concern so that analyses for US regulatory applications combine the results of modeling with observations, and knowledge of spatially and temporally differentiated emissions. 32 refs., 3 tabs.
Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction
Ghasemi, Mohammadreza
2015-02-23
In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.
Yin, Yi; Shang, Pengjian
2013-12-01
We use multiscale detrended fluctuation analysis (MSDFA) and multiscale detrended cross-correlation analysis (MSDCCA) to investigate auto-correlation (AC) and cross-correlation (CC) in the US and Chinese stock markets during 1997-2012. The results show that US and Chinese stock indices differ in terms of their multiscale AC structures. Stock indices in the same region also differ with regard to their multiscale AC structures. We analyze AC and CC behaviors among indices for the same region to determine similarity among six stock indices and divide them into four groups accordingly. We choose S&P500, NQCI, HSI, and the Shanghai Composite Index as representative samples for simplicity. MSDFA and MSDCCA results and average MSDFA spectra for local scaling exponents (LSEs) for individual series are presented. We find that the MSDCCA spectrum for LSE CC between two time series generally tends to be greater than the average MSDFA LSE spectrum for individual series. We obtain detailed multiscale structures and relations for CC between the four representatives. MSDFA and MSDCCA with secant rolling windows of different sizes are then applied to reanalyze the AC and CC. Vertical and horizontal comparisons of different window sizes are made. The MSDFA and MSDCCA results for the original window size are confirmed and some new interesting characteristics and conclusions regarding multiscale correlation structures are obtained.
Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J
2014-01-01
The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.
Physics-based hybrid method for multiscale transport in porous media
Yousefzadeh, Mehrdad; Battiato, Ilenia
2017-09-01
Despite advancements in the development of multiscale models for flow and reactive transport in porous media, the accurate, efficient and physics-based coupling of multiple scales in hybrid models remains a major theoretical and computational challenge. Improving the predictivity of macroscale predictions by means of multiscale algorithms relative to classical at-scale models is the primary motivation for the development of multiscale simulators. Yet, very few are the quantitative studies that explicitly address the predictive capability of multiscale coupling algorithms as it is still generally not possible to have a priori estimates of the errors that are present when complex flow processes are modeled. We develop a nonintrusive pore-/continuum-scale hybrid model whose coupling error is bounded by the upscaling error, i.e. we build a predictive tightly coupled multiscale scheme. This is accomplished by slightly enlarging the subdomain where continuum-scale equations are locally invalid and analytically defining physics-based coupling conditions at the interfaces separating the two computational sub-domains, while enforcing state variable and flux continuity. The proposed multiscale coupling approach retains the advantages of domain decomposition approaches, including the use of existing solvers for each subdomain, while it gains flexibility in the choice of the numerical discretization method and maintains the coupling errors bounded by the upscaling error. We implement the coupling in finite volumes and test the proposed method by modeling flow and transport through a reactive channel and past an array of heterogeneously reactive cylinders.
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi
2017-09-01
It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.
Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.
2016-12-01
Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.
DEFF Research Database (Denmark)
Zhukovsky, Sergei; Lavrinenko, Andrei; Sipe, J. E.
2013-01-01
, wavelength scale, the propagation of bulk plasmon polaritons in the resulting multiscale HMM is subject to photonic band gap phenomena. A great degree of control over such plasmons can be exerted by varying the superstructure geometry. As an example, Bragg reflection and Fabry-Pérot resonances...... are demonstrated in multiscale HMMs with periodic superstructures. More complicated, aperiodically ordered superstructures are also considered, with fractal Cantor-like multiscale HMMs exhibiting characteristic self-similar spectral signatures in the high-k band. The multiscale HMM concept is shown...
Chun, Chan; Haohua, Wen; Lanyuan, Lu; Jun, Fan
2016-01-01
Membrane curvature is no longer thought of as a passive property of the membrane; rather, it is considered as an active, regulated state that serves various purposes in the cell such as between cells and organelle definition. While transport is usually mediated by tiny membrane bubbles known as vesicles or membrane tubules, such communication requires complex interplay between the lipid bilayers and cytosolic proteins such as members of the Bin/Amphiphysin/Rvs (BAR) superfamily of proteins. With rapid developments in novel experimental techniques, membrane remodeling has become a rapidly emerging new field in recent years. Molecular dynamics (MD) simulations are important tools for obtaining atomistic information regarding the structural and dynamic aspects of biological systems and for understanding the physics-related aspects. The availability of more sophisticated experimental data poses challenges to the theoretical community for developing novel theoretical and computational techniques that can be used to better interpret the experimental results to obtain further functional insights. In this review, we summarize the general mechanisms underlying membrane remodeling controlled or mediated by proteins. While studies combining experiments and molecular dynamics simulations recall existing mechanistic models, concurrently, they extend the role of different BAR domain proteins during membrane remodeling processes. We review these recent findings, focusing on how multiscale molecular dynamics simulations aid in understanding the physical basis of BAR domain proteins, as a representative of membrane-remodeling proteins. Project supported by the National Natural Science Foundation of China (Grant No. 21403182) and the Research Grants Council of Hong Kong, China (Grant No. CityU 21300014).
A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation
Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.
2016-12-01
Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.
Directory of Open Access Journals (Sweden)
Fridolin Simon. Brand
2013-06-01
Full Text Available Alpine regions in Europe, in particular, face demanding local challenges, e.g., the decline in the agriculture and timber industries, and are also prone to global changes, such as in climate, with potentially severe impacts on tourism. We focus on the Visp region in the Upper Valais, Switzerland, and ask how the process of stakeholder involvement in research practice can contribute to a better understanding of the specific challenges and future development of mountainous regions under global change. Based on a coupled human-environment system (HES perspective, we carried out a formative scenario analysis to develop a set of scenarios for the future directions of the Visp region. In addition, we linked these regional scenarios to context scenarios developed at the global and Swiss levels via an external consistency analysis. This method allows the coupling of both the scenario building process and the scenarios as such. We used a functional-dynamic approach to theory-practice cooperation, i.e., the involvement of key stakeholders from, for example, tourism, forestry, and administration, differed in type and intensity during the steps of the research process. In our study, we experienced strong problem awareness among the stakeholders concerning the impacts of global change and local challenges. The guiding research question was commonly defined and problem ownership was more or less balanced. We arrived at six multiscale scenarios that open up future trajectories for the Visp region, and present generic strategies to cope with global and local challenges. The results show that local identity, spatial planning, community budget, and demographic development are important steering elements in the region's future development. We suggest that method-guided transdisciplinary processes result in a richer picture and a more systemic understanding, which enable a discussion of critical and surprising issues.
Understanding protected area resilience: a multi-scale, social-ecological approach
Cumming, Graeme S.; Allen, Craig R.; Ban, Natalie C.; Biggs, Duan; Biggs, Harry C.; Cumming, David H.M; De Vos, Alta; Epstein, Graham; Etienne, Michel; Maciejewski, Kristine; Mathevet, Raphael; Moore, Christine; Nenadovic, Mateja; Schoon, Michael
2015-01-01
Protected areas (PAs) remain central to the conservation of biodiversity. Classical PAs were conceived as areas that would be set aside to maintain a natural state with minimal human influence. However, global environmental change and growing cross-scale anthropogenic influences mean that PAs can no longer be thought of as ecological islands that function independently of the broader social-ecological system in which they are located. For PAs to be resilient (and to contribute to broader social-ecological resilience), they must be able to adapt to changing social and ecological conditions over time in a way that supports the long-term persistence of populations, communities, and ecosystems of conservation concern. We extend Ostrom's social-ecological systems framework to consider the long-term persistence of PAs, as a form of land use embedded in social-ecological systems, with important cross-scale feedbacks. Most notably, we highlight the cross-scale influences and feedbacks on PAs that exist from the local to the global scale, contextualizing PAs within multi-scale social-ecological functional landscapes. Such functional landscapes are integral to understand and manage individual PAs for long-term sustainability. We illustrate our conceptual contribution with three case studies that highlight cross-scale feedbacks and social-ecological interactions in the functioning of PAs and in relation to regional resilience. Our analysis suggests that while ecological, economic, and social processes are often directly relevant to PAs at finer scales, at broader scales, the dominant processes that shape and alter PA resilience are primarily social and economic.
Multiscale Seismic Inversion in the Data and Image Domains
Zhang, Sanzong
2015-12-01
I present a general methodology for inverting seismic data in either the data or image domains. It partially overcomes one of the most serious problems with current waveform inversion methods, which is the tendency to converge to models far from the actual one. The key idea is to develop a multiscale misfit function that is composed of both a simplified version of the data and one associated with the complex part of the data. Misfit functions based on simple data are characterized by many fewer local minima so that a gradient optimization method can make quick progress in getting to the general vicinity of the actual model. Once we are near the actual model, we then use the gradient based on the more complex data. Below, we describe two implementations of this multiscale strategy: wave equation traveltime inversion in the data domain and generalized differential semblance optimization in the image domain. • Wave Equation Traveltime Inversion in the Data Domain (WT): The main difficulty with iterative waveform inversion is that it tends to get stuck in local minima associated with the waveform misfit function. To mitigate this problem and avoid the need to fit amplitudes in the data, we present a waveequation method that inverts the traveltimes of reflection events, and so is less prone to the local minima problem. Instead of a waveform misfit function, the penalty function is a crosscorrelation of the downgoing direct wave and the upgoing reflection wave at the trial image point. The time lag which maximizes the crosscorrelation amplitude represents the reflection-traveltime residual that is back-projected along the reflection wavepath to update the velocity. Shot- and angle-domain crosscorrelation functions are introduced to estimate the reflection-traveltime residual by semblance analysis and scanning. In theory, only the traveltime information is inverted and there is no need to precisely fit the amplitudes or assume a high-frequency approximation. Results
Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials
Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar
2015-01-01
The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition
Torbick, N.; Salas, W.; Qi, J.; Huang, X.
2017-12-01
In the Lower Mekong River Basin (LMRB), population growth and transitioning economies, shifting climate, and intense pressures for resources are driving tradeoffs among the water-enegery-food (WEF) nexus. Rice production and irrigation, wetlands habitat, and damn constructions are intertwinned across the region. There are 11 major hydropower dams on the main stem of the Lower Mekong River and many smaller dams in the basin. At the same time increased pressure for food production has amplified cropping intensity and irrigation infrastructure projects. These human acitivies are impacting inundation patterns and phenology of wetland and lake ecosystems. We are mapping rice, wetlands, and lake inundation dynamics using multi-scale satellite remote sensing. New opportunities exist for moderate scale, near-daily mapping of rice, wetland, shrimp, and lake hydroperiod with multi-source imaging and BigData computational approaches on the NAS cloud. Primarily we rely on Sentinel-1 IW and PALSAR-2 ScanSAR to map inundation dynamics at 10m resolution including under canopy conditions using double bounce properties. As part of this effort we are assessing different damn impacts at case studies in Thailand, Cambodia, Laos, and Vietnam with high resolution commercial imagery, social surveys, and socioeconomic models. These dams are currently regulated individually without coordination. As a result, their operation has outsized impacts on lake and wetland ecologies, negatively affecting the associated ecosystem services that local communities have relied on. All new products are shared openly with the science community. Case study illustrations will be presented.
Multiscale forward electromagnetic model of uterine contractions during pregnancy
International Nuclear Information System (INIS)
La Rosa, Patricio S; Eswaran, Hari; Preissl, Hubert; Nehorai, Arye
2012-01-01
Analyzing and monitoring uterine contractions during pregnancy is relevant to the field of reproductive health assessment. Its clinical importance is grounded in the need to reliably predict the onset of labor at term and pre-term. Preterm births can cause health problems or even be fatal for the fetus. Currently, there are no objective methods for consistently predicting the onset of labor based on sensing of the mechanical or electrophysiological aspects of uterine contractions. Therefore, modeling uterine contractions could help to better interpret such measurements and to develop more accurate methods for predicting labor. In this work, we develop a multiscale forward electromagnetic model of myometrial contractions during pregnancy. In particular, we introduce a model of myometrial current source densities and compute its magnetic field and action potential at the abdominal surface, using Maxwell’s equations and a four-compartment volume conductor geometry. To model the current source density at the myometrium we use a bidomain approach. We consider a modified version of the Fitzhugh-Nagumo (FHN) equation for modeling ionic currents in each myocyte, assuming a plateau-type transmembrane potential, and we incorporate the anisotropic nature of the uterus by designing conductivity-tensor fields. We illustrate our modeling approach considering a spherical uterus and one pacemaker located in the fundus. We obtained a travelling transmembrane potential depolarizing from −56 mV to −16 mV and an average potential in the plateau area of −25 mV with a duration, before hyperpolarization, of 35 s, which is a good approximation with respect to the average recorded transmembrane potentials at term reported in the technical literature. Similarly, the percentage of myometrial cells contracting as a function of time had the same symmetric properties and duration as the intrauterine pressure waveforms of a pregnant human myometrium at term. We introduced a multiscale
Multiscale study on hydrogen mobility in metallic fusion divertor material
International Nuclear Information System (INIS)
Heinola, K.
2010-01-01
For achieving efficient fusion energy production, the plasma-facing wall materials of the fusion reactor should ensure long time operation. In the next step fusion device, ITER, the first wall region facing the highest heat and particle load, i.e. the divertor area, will mainly consist of tiles based on tungsten. During the reactor operation, the tungsten material is slowly but inevitably saturated with tritium. Tritium is the relatively short-lived hydrogen isotope used in the fusion reaction. The amount of tritium retained in the wall materials should be minimized and its recycling back to the plasma must be unrestrained, otherwise it cannot be used for fueling the plasma. A very expensive and thus economically not viable solution is to replace the first walls quite often. A better solution is to heat the walls to temperatures where tritium is released. Unfortunately, the exact mechanisms of hydrogen release in tungsten are not known. In this thesis both experimental and computational methods have been used for studying the release and retention of hydrogen in tungsten. The experimental work consists of hydrogen implantations into pure polycrystalline tungsten, the determination of the hydrogen concentrations using ion beam analyses (IBA) and monitoring the out-diffused hydrogen gas with thermodesorption spectrometry (TDS) as the tungsten samples are heated at elevated temperatures. Combining IBA methods with TDS, the retained amount of hydrogen is obtained as well as the temperatures needed for the hydrogen release. With computational methods the hydrogen-defect interactions and implantation-induced irradiation damage can be examined at the atomic level. The method of multiscale modelling combines the results obtained from computational methodologies applicable at different length and time scales. Electron density functional theory calculations were used for determining the energetics of the elementary processes of hydrogen in tungsten, such as diffusivity and
Linear theory for filtering nonlinear multiscale systems with model error.
Berry, Tyrus; Harlim, John
2014-07-08
In this paper, we study filtering of multiscale dynamical systems with model error arising from limitations in resolving the smaller scale processes. In particular, the analysis assumes the availability of continuous-time noisy observations of all components of the slow variables. Mathematically, this paper presents new results on higher order asymptotic expansion of the first two moments of a conditional measure. In particular, we are interested in the application of filtering multiscale problems in which the conditional distribution is defined over the slow variables, given noisy observation of the slow variables alone. From the mathematical analysis, we learn that for a continuous time linear model with Gaussian noise, there exists a unique choice of parameters in a linear reduced model for the slow variables which gives the optimal filtering when only the slow variables are observed. Moreover, these parameters simultaneously give the optimal equilibrium statistical estimates of the underlying system, and as a consequence they can be estimated offline from the equilibrium statistics of the true signal. By examining a nonlinear test model, we show that the linear theory extends in this non-Gaussian, nonlinear configuration as long as we know the optimal stochastic parametrization and the correct observation model. However, when the stochastic parametrization model is inappropriate, parameters chosen for good filter performance may give poor equilibrium statistical estimates and vice versa; this finding is based on analytical and numerical results on our nonlinear test model and the two-layer Lorenz-96 model. Finally, even when the correct stochastic ansatz is given, it is imperative to estimate the parameters simultaneously and to account for the nonlinear feedback of the stochastic parameters into the reduced filter estimates. In numerical experiments on the two-layer Lorenz-96 model, we find that the parameters estimated online , as part of a filtering
Bouma, J.; Vos, de J.A.; Sonneveld, M.P.W.; Heuvelink, G.B.M.; Stoorvogel, J.J.
2008-01-01
Many research and scientific organizations emphasize the importance of science for society in their strategic plans. This is certainly true for land use studies being discussed in this chapter as new environmental policies are introduced at European and national level. Such policies reflect concerns
A stochastic multiscale framework for modeling flow through random heterogeneous porous media
International Nuclear Information System (INIS)
Ganapathysubramanian, B.; Zabaras, N.
2009-01-01
Flow through porous media is ubiquitous, occurring from large geological scales down to the microscopic scales. Several critical engineering phenomena like contaminant spread, nuclear waste disposal and oil recovery rely on accurate analysis and prediction of these multiscale phenomena. Such analysis is complicated by inherent uncertainties as well as the limited information available to characterize the system. Any realistic modeling of these transport phenomena has to resolve two key issues: (i) the multi-length scale variations in permeability that these systems exhibit, and (ii) the inherently limited information available to quantify these property variations that necessitates posing these phenomena as stochastic processes. A stochastic variational multiscale formulation is developed to incorporate uncertain multiscale features. A stochastic analogue to a mixed multiscale finite element framework is used to formulate the physical stochastic multiscale process. Recent developments in linear and non-linear model reduction techniques are used to convert the limited information available about the permeability variation into a viable stochastic input model. An adaptive sparse grid collocation strategy is used to efficiently solve the resulting stochastic partial differential equations (SPDEs). The framework is applied to analyze flow through random heterogeneous media when only limited statistics about the permeability variation are given
A generalized multiscale finite element method for elastic wave propagation in fractured media
Chung, Eric T.
2016-02-26
In this paper, we consider elastic wave propagation in fractured media applying a linear-slip model to represent the effects of fractures on the wavefield. Fractured media, typically, are highly heterogeneous due to multiple length scales. Direct numerical simulations for wave propagation in highly heterogeneous fractured media can be computationally expensive and require some type of model reduction. We develop a multiscale model reduction technique that captures the complex nature of the media (heterogeneities and fractures) in the coarse scale system. The proposed method is based on the generalized multiscale finite element method, where the multiscale basis functions are constructed to capture the fine-scale information of the heterogeneous, fractured media and effectively reduce the degrees of freedom. These multiscale basis functions are coupled via the interior penalty discontinuous Galerkin method, which provides a block-diagonal mass matrix. The latter is needed for fast computation in an explicit time discretization, which is used in our simulations. Numerical results are presented to show the performance of the presented multiscale method for fractured media. We consider several cases where fractured media contain fractures of multiple lengths. Our numerical results show that the proposed reduced-order models can provide accurate approximations for the fine-scale solution.
Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis
Directory of Open Access Journals (Sweden)
Data Iranata
2010-05-01
Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.
Fast online generalized multiscale finite element method using constraint energy minimization
Chung, Eric T.; Efendiev, Yalchin; Leung, Wing Tat
2018-02-01
Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.
Directory of Open Access Journals (Sweden)
Antonio Canale
2017-06-01
Full Text Available msBP is an R package that implements a new method to perform Bayesian multiscale nonparametric inference introduced by Canale and Dunson (2016. The method, based on mixtures of multiscale beta dictionary densities, overcomes the drawbacks of Pólya trees and inherits many of the advantages of Dirichlet process mixture models. The key idea is that an infinitely-deep binary tree is introduced, with a beta dictionary density assigned to each node of the tree. Using a multiscale stick-breaking characterization, stochastically decreasing weights are assigned to each node. The result is an infinite mixture model. The package msBP implements a series of basic functions to deal with this family of priors such as random densities and numbers generation, creation and manipulation of binary tree objects, and generic functions to plot and print the results. In addition, it implements the Gibbs samplers for posterior computation to perform multiscale density estimation and multiscale testing of group differences described in Canale and Dunson (2016.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
Energy Technology Data Exchange (ETDEWEB)
Donald Estep; Michael Holst; Simon Tavener
2010-02-08
This project was concerned with the accurate computational error estimation for numerical solutions of multiphysics, multiscale systems that couple different physical processes acting across a large range of scales relevant to the interests of the DOE. Multiscale, multiphysics models are characterized by intimate interactions between different physics across a wide range of scales. This poses significant computational challenges addressed by the proposal, including: (1) Accurate and efficient computation; (2) Complex stability; and (3) Linking different physics. The research in this project focused on Multiscale Operator Decomposition methods for solving multiphysics problems. The general approach is to decompose a multiphysics problem into components involving simpler physics over a relatively limited range of scales, and then to seek the solution of the entire system through some sort of iterative procedure involving solutions of the individual components. MOD is a very widely used technique for solving multiphysics, multiscale problems; it is heavily used throughout the DOE computational landscape. This project made a major advance in the analysis of the solution of multiscale, multiphysics problems.
Multiscale Pressure-Balanced Structures in Three-dimensional Magnetohydrodynamic Turbulence
Energy Technology Data Exchange (ETDEWEB)
Yang, Liping; Zhang, Lei; Feng, Xueshang [SIGMA Weather Group, State Key Laboratory for Space Weather, National Space Science Center, Chinese Academy of Sciences, 100190, Beijing (China); He, Jiansen; Tu, Chuanyi; Wang, Linghua [School of Earth and Space Sciences, Peking University, 100871 Beijing (China); Li, Shengtai [Theoretical Division, MS B284, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Marsch, Eckart [Institute for Experimental and Applied Physics, Christian Albrechts University at Kiel, D-24118 Kiel (Germany); Wang, Xin, E-mail: jshept@gmail.com [School of Space and Environment, Beihang University, 100191 Beijing (China)
2017-02-10
Observations of solar wind turbulence indicate the existence of multiscale pressure-balanced structures (PBSs) in the solar wind. In this work, we conduct a numerical simulation to investigate multiscale PBSs and in particular their formation in compressive magnetohydrodynamic turbulence. By the use of the higher-order Godunov code Athena, a driven compressible turbulence with an imposed uniform guide field is simulated. The simulation results show that both the magnetic pressure and the thermal pressure exhibit a turbulent spectrum with a Kolmogorov-like power law, and that in many regions of the simulation domain they are anticorrelated. The computed wavelet cross-coherence spectra of the magnetic pressure and the thermal pressure, as well as their space series, indicate the existence of multiscale PBSs, with the small PBSs being embedded in the large ones. These multiscale PBSs are likely to be related to the highly oblique-propagating slow-mode waves, as the traced multiscale PBS is found to be traveling in a certain direction at a speed consistent with that predicted theoretically for a slow-mode wave propagating in the same direction.
A generalized multiscale finite element method for elastic wave propagation in fractured media
Chung, Eric T.; Efendiev, Yalchin R.; Gibson, Richard L.; Vasilyeva, Maria
2016-01-01
In this paper, we consider elastic wave propagation in fractured media applying a linear-slip model to represent the effects of fractures on the wavefield. Fractured media, typically, are highly heterogeneous due to multiple length scales. Direct numerical simulations for wave propagation in highly heterogeneous fractured media can be computationally expensive and require some type of model reduction. We develop a multiscale model reduction technique that captures the complex nature of the media (heterogeneities and fractures) in the coarse scale system. The proposed method is based on the generalized multiscale finite element method, where the multiscale basis functions are constructed to capture the fine-scale information of the heterogeneous, fractured media and effectively reduce the degrees of freedom. These multiscale basis functions are coupled via the interior penalty discontinuous Galerkin method, which provides a block-diagonal mass matrix. The latter is needed for fast computation in an explicit time discretization, which is used in our simulations. Numerical results are presented to show the performance of the presented multiscale method for fractured media. We consider several cases where fractured media contain fractures of multiple lengths. Our numerical results show that the proposed reduced-order models can provide accurate approximations for the fine-scale solution.
A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control
Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.
2014-01-01
Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569