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47th AIAA Fluid Dynamics Conference, 2017

作者： Barone, Matthew F. Fike, Jeffrey A. Chowdhary, Kamaljit S. Davis, Warren L. Ling, Julia Martin, Shawn Sandia National Labs AlbuquerqueNM87123 United States Aerosciences Department United States Extreme Scale Data Science and Analytics Department United States Scalable Analysis and Visualization Department United States Thermal/Fluids Science and Engineering Department United States Software Systems R&D Department United States

ISBN: (数字)9781624105005

ISBN: (纸本)9781624105005

We investigate a novel application of deep neural networks to modeling of errors in prediction of surface pressure fluctuations beneath a compressible, turbulent flow. In this context, the truth solution is given by Direct Numerical Simulation (DNS) data, while the predictive model is a wall-modeled Large Eddy Simulation (LES). The neural network provides a means to map relevant statistical flow-features within the LES solution to errors in prediction of wall pressure spectra. We simulate a number of flat plate turbulent boundary layers using both DNS and wall-modeled LES to build up a database with which to train the neural network. We then apply machine learning techniques to develop an optimized neural network model for the error in terms of relevant flow features. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Large eddy simulation

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Tracking the solid-electrolyte-interphase (SEI) formation on Amorphous Si and Sn anodes for li-ion batteries 11

Tracking the solid-electrolyte-interphase (SEI) formation on...

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11th Annual TechConnect World Innovation Conference and Expo, Held Jointly with the 20th Annual Nanotech Conference and Expo, and the 2017 National SBIR/STTR Conference

作者： Kim, J.R. Doucet, M. Browning, J.F. Veith, G.M. Neutron Data Analysis and Visualization Division Oak Ridge National Laboratory Oak RidgeTN United States Chemical and Engineering Materials Division Oak Ridge National Laboratory Oak RidgeTN United States Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9780997511796

Neutron reflectometry provides a detailed method in which to investigate the solid-electrolyte interphase (SEI) throughout its initial formation and under dynamic cycling conditions in lithium-ion batteries. Amorphous silicon (a-Si) and tin are investigated to demonstrate both the thickness and scattering length density of the SEI layer considering a fluoroethylene carbonate (FEC) electrolyte additive. Distinct differences and similarities between the two systems have been identified;both a-Si and Sn observe a reversible contraction/growth of the SEI layer throughout charge/discharge cycles originating from the buildup and dissolution of organic components at the electrolyte surface. a-Si observes a clear tendancy to form an initial Li2O/Li2CO3 layer based on a chemical reaction that occurs between the native oxide and the electrolyte prior to electrochemical cycling. Whereas the native tin oxide appears to remain intact, forming an SEI of different composition as a result.

关键词： Amorphous silicon

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HDF5-FastQuery: Accelerating Complex Queries on HDF datasets using Fast Bitmap Indices

HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets...

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International Working Conference on Scientific and Statistical database Management

作者： L. Gosink J. Shalf K. Stockinger Kesheng Wu W. Bethel Institute for Data Analysis and Visualization University of California슠Davis Davis CA USA Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA USA

Large scale scientific data is often stored in scientific data formats such as FITS, netCDF and HDF. These storage formats are of particular interest to the scientific user community since they provide multi-dimensional storage and retrieval. However, one of the drawbacks of these storage formats is that they do not support semantic indexing which is important for interactive data analysis where scientists look for features of interests such as "find all supernova explosions where energy > 10 5 and temperature > 10 6 ". In this paper we present a novel approach called HDF5-FastQuery to accelerate the data access of large HDF5 files by introducing multi-dimensional semantic indexing. Our implementation leverages an efficient indexing technology called bitmap indexing that has been widely used in the database community. Bitmap indices are especially well suited for interactive exploration of large-scale read-only data. Storing the bitmap indices into the HDF5 file has the following advantages: a) significant performance speedup of accessing subsets of multi-dimensional data and b) portability of the indices across multiple computer platforms. We present an API that simplifies the execution of queries on HDF5 files for general scientific applications and data analysis. The design is flexible enough to accommodate the use of arbitrary indexing technology for semantic range queries. We also provide a detailed performance analysis of HDF5-FastQuery for both synthetic and scientific data. The results demonstrate that our proposed approach for multi-dimensional queries is up to a factor of 2 faster than HDF5

关键词： Acceleration Indexing Large-scale systems data analysis Energy storage Explosions Temperature databases Application software Performance analysis

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Survey on Visual analysis of Event Sequence data

arXiv

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arXiv 2020年

作者： Guo, Yi Guo, Shunan Jin, Zhuochen Kaul, Smiti Gotz, David Cao, Nan Intelligent Big Data Visualization Lab Tongji University Shanghai China Visual Analysis and Communication Lab University of North Carolina Chapel HillNC United States

Event sequence data record series of discrete events in the time order of occurrence. They are commonly observed in a variety of applications ranging from electronic health records to network logs, with the characteristics of large-scale, high-dimensional and heterogeneous. This high complexity of event sequence data makes it difficult for analysts to manually explore and find patterns, resulting in ever-increasing needs for computational and perceptual aids from visual analytics techniques to extract and communicate insights from event sequence datasets. In this paper, we review the state-of-the-art visual analytics approaches, characterize them with our proposed design space, and categorize them based on analytical tasks and applications. From our review of relevant literature, we have also identified several remaining research challenges and future research opportunities. Copyright © 2020, The Authors. All rights reserved.

关键词： visualization

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ParaText: Scalable text modeling and analysis 10

ParaText: Scalable text modeling and analysis

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Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

作者： Dunlavy, Daniel M. Shead, Timothy M. Stanton, Eric T. Comp. Sci. and Informatics Sandia National Laboratories M/S 1318 P.O. Box 5800 Albuquerque NM 87185-1318 United States Data Analysis and Visualization Sandia National Laboratories M/S 1323 P.O. Box 5800 Albuquerque NM 87185-1323 United States

ISBN: (纸本)9781605589428

Automated analysis of unstructured text documents (e.g., web pages, newswire articles, research publications, business reports) is a key capability for solving important problems in areas including decision making, risk assessment, social net- work analysis, intelligence analysis, scholarly research and others. However, as data sizes continue to grow in these ar- eas, scalable processing, modeling, and semantic analysis of text collections becomes essential. In this paper, we present the ParaText text analysis engine, a distributed memory software framework for processing, modeling, and analyzing collections of unstructured text documents. Results on sev- eral document collections using hundreds of processors are presented to illustrate the exibility, extensibility, and scal- ability of the the entire process of text modeling from raw data ingestion to application analysis. © Copyright 2010 ACM.

关键词： Risk assessment

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Topology exploration with hierarchical landscapes

Topology exploration with hierarchical landscapes

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Workshop at SIGGRAPH Asia 2012, WASA 2012

作者： Demir, Dogan Beketayev, Kenes Weber, Gunther H. Bremer, Peer-Timo Pascucci, Valerio Hamann, Bernd Scientific Computing and Imaging Institute School of Computing University of Utah United States Computational Research Divisition Lawrence Berkeley National Laboratory United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States Institute for Data Analysis and Visualization Computer Science Department University of California Davis CA United States

ISBN: (纸本)9781450318358

Topological landscapes have been proposed as a visual metaphor for contour trees that does not require an understanding of the theory involved in defining contour trees. The idea is to create a representative terrain with the same topological structure as a given contour tree. This representation exploits the natural human ability to interpret topography and results in an intuitive visualization of otherwise abstract information. However, topological landscapes still suffer from some of the same limitations as traditional contour tree visualization. Most notable is the fact that for complex functions landscapes can quickly become highly complex, exceeding the limits of human comprehension as well as the available computing resources. To address this challenge, we propose a new framework for the dynamic creation and visualization of hierarchical topological landscapes. Our system provides an interactive visualization of complex functions by utilizing a hierarchical decomposition of the contour tree as well as focus+context type interactions. For three dimensional data, we link the landscape display to flexible isosurface extraction in order to correlate terrain features with their corresponding three dimensional counterparts. We demonstrate the utility and versatility of our approach on a variety of both low and high dimensional data sets. © 2012 ACM.

关键词： visualization

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The contour spectrum 97

The contour spectrum

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Proceedings of the 8th conference on visualization '97

作者： Chandrajit L. Bajaj Valerio Pascucci Daniel R. Schikore Shastra Lab & Center for Image Analysis and Data Visualization Department of Computer Sciences Purdue University West Lafayette IN and Department of Computer Science & TICAM University of Texas at Austin Austin TX P.O. Box 808 Mail Stop L-561 Livermore CA and Shastra Lab & Center for Image Analysis and Data Visualization Department of Computer Sciences Purdue University West Lafayette IN

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Three-dimensional simulations of geometrically complex subduction with large viscosity variations

Three-dimensional simulations of geometrically complex subdu...

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1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the Campus and Beyond, XSEDE12

作者： Jadamec, Margarete A. Billen, Magali I. Kreylos, Oliver Department of Geological Sciences Brown University 324 Brook Street Box 1846 Providence RI 02912 United States Department of Geology University of California Davis One Shields Avenue Davis CA 95616 United States Institute for Data Analysis and Visualization University of California Davis 2306 Academic Surge Building Davis CA 95616 United States

ISBN: (纸本)9781450316026

The incorporation of geologic realism into numerical models of subduction is becoming increasingly necessary as observational and experimental constraints indicate plate boundaries are inherently three-dimensional (3D) in nature and contain large viscosity variations. However, large viscosity variations occurring over short distances pose a challenge for computational codes, and models with complex 3D geometries require substantially greater numbers of elements, increasing the computational demands. We modified a community mantle convection code, CitcomCU, to model realistic subduction zones that use an arbitrarily shaped 3D plate boundary interface and incorporate the effects of a strain-rate dependent viscosity based on an experimentally derived flow law for olivine aggregates. Tests of this implementation on 3D models with a simple subduction zone geometry indicate that limiting the overall viscosity range in the model, as well as limiting the viscosity jump across an element, improves model runtime and convergence behavior, consistent with what has been shown previously. In addition, the choice of method and averaging scheme used to transfer the viscosity structure to the different levels in the multigrid solver can significantly improve model performance. These optimizations can improve model runtime by over 20%. 3D models of a subduction zone with a complex plate boundary geometry were then constructed, containing over 100 million finite element nodes with a local resolution of up to 2.35 km, and run on XSEDE. These complex 3D models, representative of the Alaska subduction zone-transform plate boundary, contain viscosity variations of up to seven orders of magnitude. The optimizations in solver parameters determined from the simple 3D models of subduction applied to the much larger and more complex models of an actual subduction zone improved model convergence behavior and reduced runtimes by on the order of 25%. One scientific result from 3D models of Alaska

关键词： Viscosity

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Understanding perspectives on sharing neutron data at oak ridge national laboratory

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data Science Journal 2017年 16卷

作者： Donaldson, Devan Ray Martin, Shawn Proffen, Thomas Department of Information and Library Science School of Informatics and Computing Indiana University BloomingtonIN United States Neutron Data Analysis and Visualization Oak Ridge National Laboratory PO Box 2008 Oak RidgeTN United States

Even though the importance of sharing data is frequently discussed, data sharing appears to be limited to a few fields, and practices within those fields are not well understood. This study examines perspectives on sharing neutron data collected at Oak Ridge National Laboratory’s neutron sources. Operation at user facilities has traditionally focused on making data accessible to those who create them. The recent emphasis on open data is shifting the focus to ensure that the data produced are reusable by others. This mixed methods research study included a series of surveys and focus group interviews in which 13 data consumers, data managers, and data producers answered questions about their perspectives on sharing neutron data. data consumers reported interest in reusing neutron data for comparison/verification of results against their own measurements and testing new theories using existing data. They also stressed the importance of establishing context for data, including how data are produced, how samples are prepared, units of measurement, and how temperatures are determined. data managers expressed reservations about reusing others’ data because they were not always sure if they could trust whether the people responsible for interpreting data did so correctly. data producers described concerns about their data being misused, competing with other users, and over-reliance on data producers to understand data. We present the Consumers Managers Producers (CMP) Model for understanding the interplay of each group regarding data sharing. We conclude with policy and system recommendations and discuss directions for future research. © 2017 The Author(s).

关键词： Managers

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visualization as a bridge between chemical and nuclear engineering simulations

Visualization as a bridge between chemical and nuclear engin...

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作者： Fogal, Thomas Xiao, Shanjie Yang, Xue Krüger, Jens Jevremovic, Tatjana Scientific Computing and Imaging Institute University of Utah United States Radiation Protection SLAC National Accelerator Laboratory United States Utah Nuclear Engineering Program University of Utah United States Interactive Visualization and Data Analysis Group DFKI Saarbrücken Germany Civil and Environmental Engineering University of Utah United States

ISBN: (纸本)9780816910656

Collaborating across disciplines can be a difficult task for a variety of reasons. One of which is the lack of common methodologies and tools for visualization and analysis. Tools developed in one group can rarely be applied directly to data from another group, due to differences in data formats, analysis methodologies, and learning curves associated with the advanced visualization systems necessary for modern scientific data. Despite these difficulties, multi-physics collaboration is key to developing and understanding the next generation of computational models, which couple the dynamic processes and scales of multiple disciplines. As a step towards integrative models, we propose a visualization and analysis system to serve as a common interconnect between chemical and nuclear engineering. This choice allows multiple organizations to fruitfully exchange data and example visualizations in a reproducible manner, providing a foundation for productive discussion. In this work, we demonstrate the utility of a visualization system as it applies to bridging simulation domains and providing for multidisciplinary research in nuclear and chemical engineering.

关键词： visualization

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