CDS&E/Collaborative Research: The Integration of Data-Mining with Multiscale Engineering Computations
CDS
基本信息
- 批准号:1310173
- 负责人:
- 金额:$ 52.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-08-15 至 2017-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This collaborative research project aims at developing mathematical methods for the analysis/mining of large scale, high dimensional data that arise in engineering/physicochemical computations, and, more importantly, in exploiting these methods and algorithms to accelerate the computations themselves. This type of synergy between data mining and scientific computation has the potential to significantly enhance the way we extract knowledge from large scale modeling and simulation. The focus of the approach is the discovery a small number of key, intrinsic features of simulations characterized by very large numbers of degrees of freedom - and the exploitation of these key features to systematically design subsequent simulations. Another important feature of the work is the development of algorithms that "translate" between fine scale, detailed, and coarse scale, compact descriptions of the data, as well as algorithms for the fast incorporation of new data/information in previous computational frameworks. Deliverables of the effort will be the algorithms themselves, as well as documented illustrative examples of their application to large scale molecular and agent-based simulations.If successful, this research will create, document and make available a computational protocol for enhancing large scale scientific computations in the modeling of complex dynamical systems. Example applications include nanoscale self-assembly, such as micelle formation in materials computations, macromolecular foldling, large scale agent-based models of collective motion in ecology and cellular biology, as well as large scale, Partial Differential Equation simulations of engineering problems, like combustion. The results will be disseminated to allow their use by other researchers. The research will form the basis of cross-disciplinary education of graduate students in engineering and in mathematics, and of undergraduate research projects in these disciplines. It will also underpin the development of course materials in large scale data processing.
该合作研究项目旨在开发用于分析/挖掘工程/物理化学计算中出现的大规模高维数据的数学方法,更重要的是,利用这些方法和算法来加速计算本身。数据挖掘和科学计算之间的这种协同作用有可能显著增强我们从大规模建模和仿真中提取知识的方式。该方法的重点是发现以大量自由度为特征的模拟的少数关键内在特征,并利用这些关键特征系统地设计后续模拟。这项工作的另一个重要特征是开发了在精细尺度、详细尺度和粗糙尺度之间“转换”的算法,以及在以前的计算框架中快速合并新数据/信息的算法。该工作的交付成果将是算法本身,以及它们在大规模分子和基于代理的模拟中的应用的文档说明示例。如果成功,这项研究将创建、记录并提供一种计算协议,用于增强复杂动力系统建模中的大规模科学计算。应用实例包括纳米尺度的自组装,如材料计算中的胶束形成,大分子折叠,生态学和细胞生物学中的大规模基于主体的集体运动模型,以及大规模的工程问题的偏微分方程模拟,如燃烧。研究结果将被传播,以供其他研究人员使用。这项研究将成为工程和数学研究生跨学科教育的基础,以及这些学科的本科生研究项目的基础。它还将支持大规模数据处理课程材料的开发。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yannis Kevrekidis其他文献
Data-driven cold starting of good reservoirs
- DOI:
10.1016/j.physd.2024.134325 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Lyudmila Grigoryeva;Boumediene Hamzi;Felix P. Kemeth;Yannis Kevrekidis;G. Manjunath;Juan-Pablo Ortega;Matthys J. Steynberg - 通讯作者:
Matthys J. Steynberg
Yannis Kevrekidis的其他文献
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{{ truncateString('Yannis Kevrekidis', 18)}}的其他基金
Collaborative Research: CPS: Medium: Data Driven Modeling and Analysis of Energy Conversion Systems -- Manifold Learning and Approximation
合作研究:CPS:媒介:能量转换系统的数据驱动建模和分析——流形学习和逼近
- 批准号:
2223987 - 财政年份:2023
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
EAGER-DynamicData: Collaborative Research: Data-driven morphing of parsimonious models for the description of transient dynamics in complex systems
EAGER-DynamicData:协作研究:数据驱动的简约模型变形,用于描述复杂系统中的瞬态动力学
- 批准号:
1462241 - 财政年份:2015
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
UNS: Collaborative Research: Unique binding geometries: Engineering & Modeling of Sticky Patches on Lipid Nanoparticles for Effective Targeting of Otherwise Untargetable cells
UNS:合作研究:独特的结合几何形状:工程
- 批准号:
1510149 - 财政年份:2015
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
Collaborative Research: A Distributed Approximate Dynamic Programming Approach for Robust Adaptive Control of Multiscale Dynamical Systems
协作研究:多尺度动力系统鲁棒自适应控制的分布式近似动态规划方法
- 批准号:
1406224 - 财政年份:2014
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
CDS&E: Collaborative Research: Data-Driven Predictive Modeling of Flows Containing Aggregating Particles
CDS
- 批准号:
1404832 - 财政年份:2014
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
EAGER/Collaborative Research: Accelerating Innovation in Agent-Based Simulations: Application to Complex Socio-Behavioral Phenomena
EAGER/协作研究:加速基于代理的模拟创新:在复杂社会行为现象中的应用
- 批准号:
1002469 - 财政年份:2010
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
Collaborative Research: Multiscale Modeling of Solid Tumor
合作研究:实体瘤的多尺度建模
- 批准号:
0817891 - 财政年份:2008
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
Collaborative Research-Smoluchowski Equations: Analysis of Dynamics, Singularities and Statistics in Complex Fluid-Particle Mixtures.
协作研究-Smoluchowski 方程:复杂流体-粒子混合物中的动力学、奇异性和统计分析。
- 批准号:
0504099 - 财政年份:2005
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
Collaborative Research:ITR/AP: Enabling Microscopic Simulators to Perform System-Level Analysis
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- 批准号:
0205484 - 财政年份:2002
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
Evolution PDEs in Inhomogeneous Media: Low-Dimensional Dynamics, Computation and Applications
非均匀介质中的演化偏微分方程:低维动力学、计算和应用
- 批准号:
9711224 - 财政年份:1997
- 资助金额:
$ 52.5万 - 项目类别:
Standard Grant
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