Decision Support for Flow in Porous Media: Optimal Sampling for Data Assimilation
多孔介质流动的决策支持:数据同化的最佳采样
基本信息
- 批准号:9870005
- 负责人:
- 金额:$ 18.21万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:1998
- 资助国家:美国
- 起止时间:1998-09-01 至 2002-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This research features a novel concept for addressing environmental engineering problems that takes into account the heterogeneous nature of the soil medium. The emphasis of the research is on developing and implementing new simulation techniques the output of which can be readily utilized in decision making as related to ensuring a sustainable environment. In particular, the output will permit a very efficient simulation of statistically consistent realizations of fate of pollutants in the ground. Additionally, the simulation technique will provide the optimal location for the sampling of hydraulic properties in a heterogeneous porous medium. Optimality, in this case, is construed to imply good predictive capability of the mathematical model under incomplete information. The concept hinges upon representing uncertain material properties as a combination of their various scales multiplied by random coefficients. This will be achieved by relying on the Karhunen-Loeve expansion that takes into account the probabilistic structure of the field, as well as the finite extent of the domain over which the problem is defined. The solution process is represented as a nonlinear functional expansion with respect to these scales of heterogeneity. The coefficients in this expansion are calculated by solving a linear system of algebraic equations. Once this expansion is obtained, the sensitivity of the predicted solution will be analytically evaluated. The sensitivity of the solution with respect to the values of the random hydraulic parameters at various spatial locations can be readily evaluated, and the optimal location of samples identified. This formulation affords a theoretical rigor which is believed to be essential to progress in the field of stochastic hydrology and reliability of ground-water flow systems. It permits an optimal representation of the random processes involved using a minimum number of random variables. The research will complement current work by the Principal Investigator on stochastic model development for ground water flow and extend its applicability to decision support.
这项研究的特点是一个新的概念,解决环境工程问题,考虑到土壤介质的异质性。 研究的重点是开发和实施新的模拟技术,其输出可以很容易地用于决策,以确保可持续的环境。 特别是,输出将允许一个非常有效的模拟统计一致的实现污染物在地面上的命运。 此外,模拟技术将提供最佳的位置,在非均质多孔介质中的水力特性的采样。 在这种情况下,最优性被解释为在不完全信息下数学模型具有良好的预测能力。 这个概念取决于将不确定的材料属性表示为它们的各种尺度乘以随机系数的组合。这将通过依赖于Karhunen-Loeve展开来实现,该展开考虑了场的概率结构以及定义问题的域的有限范围。 的解决方案的过程表示为一个非线性的功能扩展这些尺度的异质性。 这种展开式中的系数是通过求解线性代数方程组来计算的。 一旦获得该展开,将分析评估预测解的灵敏度。 可以很容易地评估在不同的空间位置的随机水力参数的值的解决方案的灵敏度,并确定样本的最佳位置。 这个公式提供了一个理论上的严谨性,这被认为是必不可少的随机水文学和地下水流系统的可靠性领域的进展。 它允许使用最少数量的随机变量的随机过程的最佳表示。 这项研究将补充首席研究员目前在地下水流随机模型开发方面的工作,并将其适用性扩展到决策支持。
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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Roger Ghanem其他文献
Damage detection and localization in sealed spent nuclear fuel dry storage canisters using multi-task machine learning classifiers
使用多任务机器学习分类器对密封乏燃料干储存桶进行损伤检测与定位
- DOI:
10.1016/j.ress.2024.110446 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:11.000
- 作者:
Anna Arcaro;Bozhou Zhuang;Bora Gencturk;Roger Ghanem - 通讯作者:
Roger Ghanem
Transient anisotropic kernel for probabilistic learning on manifolds
- DOI:
10.1016/j.cma.2024.117453 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Christian Soize;Roger Ghanem - 通讯作者:
Roger Ghanem
Switching diffusions for multiscale uncertainty quantification
多尺度不确定性量化的切换扩散
- DOI:
10.1016/j.ijnonlinmec.2024.104793 - 发表时间:
2024 - 期刊:
- 影响因子:3.2
- 作者:
Zheming Gou;Xiaohui Tu;Sergey V. Lototsky;Roger Ghanem - 通讯作者:
Roger Ghanem
Effect of experimental noise on internal damage detection of sealed spent nuclear fuel canisters
- DOI:
10.1007/s00366-025-02176-2 - 发表时间:
2025-06-28 - 期刊:
- 影响因子:4.900
- 作者:
Anna Arcaro;Bora Gencturk;Roger Ghanem;Bozhou Zhuang - 通讯作者:
Bozhou Zhuang
Spectral Stochastic Finite Element Method for Log-Normal Uncertainty
求解对数正态不确定性的谱随机有限元法
- DOI:
- 发表时间:
2004 - 期刊:
- 影响因子:0
- 作者:
Riki Honda;Roger Ghanem - 通讯作者:
Roger Ghanem
Roger Ghanem的其他文献
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{{ truncateString('Roger Ghanem', 18)}}的其他基金
Collaborative Research: RIPS Type 1: Human Geography Motifs to Evaluate Infrastructure Resilience
合作研究:RIPS 类型 1:评估基础设施弹性的人文地理学主题
- 批准号:
1441190 - 财政年份:2014
- 资助金额:
$ 18.21万 - 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:
1002517 - 财政年份:2010
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Stochastic Prediction for the Design and Management of Interacting Complex Systems
交互复杂系统设计和管理的随机预测
- 批准号:
1025043 - 财政年份:2010
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Workshop on Stochastic Multiscale Methods: Mathematical Analysis and Algorithms; August 2009, Los Angeles, CA
随机多尺度方法研讨会:数学分析和算法;
- 批准号:
0917661 - 财政年份:2009
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Collaborative Research: Uncertainty quantification for petascale simulation of carbon sequestration through fast ultra-scalable stochastic finite element methods.
合作研究:通过快速超可扩展随机有限元方法对千万亿级碳封存模拟进行不确定性量化。
- 批准号:
0904754 - 财政年份:2009
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Opportunities and Challenges in Uncertainty Quantification for Complex Interacting Systems
复杂相互作用系统不确定性量化的机遇和挑战
- 批准号:
0849537 - 财政年份:2008
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Collaborative Research: Integrated Computational System for Probability Based Multi-Scale Model of Ductile Fracture in Heterogeneous Metals and Alloys
合作研究:异种金属和合金中基于概率的延性断裂多尺度模型集成计算系统
- 批准号:
0728304 - 财政年份:2007
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
AMC-SS: Computational Algorithms and Reduced Models for Stochastic PDEs
AMC-SS:随机偏微分方程的计算算法和简化模型
- 批准号:
0512231 - 财政年份:2005
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
Workshop on Uncertainty Quantification and Error Estimation
不确定性量化与误差估计研讨会
- 批准号:
0351706 - 财政年份:2003
- 资助金额:
$ 18.21万 - 项目类别:
Standard Grant
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