AEOLUS: Advances in Experimental Design, Optimization and Learning for Uncertain Complex Systems is a U.S. Department of Energy Mathematical Multifaceted Integrated Capabilities Center (MMICC) involving researchers from Brookhaven National Laboratory, Massachusetts Institute of Technology, Oak Ridge National Laboratory, Texas A&M University, and University of Texas at Austin.
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The AEOLUS Center dedicated to developing a unified optimization-under-uncertainty framework for (1) learning predictive models from data and (2) optimizing experiments, processes, and designs, all in the context of complex, uncertain energy systems. The AEOLUS center will address the critical need for a principled, rigorous, scalable, and structure-exploiting capability for exploring parameter and decision spaces of complex forward simulation models.
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Driving Scientific Application Area: Advanced Manufacturing & Materials
Additive Manufacturing Testbed
(Turner)
Materials Self-assembly Testbed
(Alexander & Oden)
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Learning
predictive models via Bayesian inference & optimization
(Webster & Willcox)
Optimizing
experiments, processes, & designs under uncertainty
(Alexander & Ghattas)
Research Sub-Thrusts
Large-scale
Bayesian inference
(Marzouk)
Low-dimensional
& Reduced Modeling
(Willcox)
Large-scale
Bayesian OED
(Ghattas)
Optimal Control Under
Uncertainty
(Biros)
Scientific Machine Learning
(Webster)
Predictive
Multiscale Models
& Inadequacy
(Moser)
Optimal Operator
Design
(Dougherty)
Multifidelity Methods
for OUU
(Gunzburger)
Events & Updates
October 2024
AEOLUS co-PI Biros gives two invited talks at the European Numerical Mathematics and Advanced Applications Conference
September 2024
AEOLUS co-PI Tinsley Oden gave an invited Keynote lecture to Annual Meeting and Summer School 2024 ; IRTG 2379 in Austin on "Phase-Field Models of Phase Change of Complex Systems : Block Copolymers and Growth of VascularTumors", July 2024.
AEOLUS co-PI Tinsley Oden gave the Keynote lecture at cellMath, a workshop on tumor growth modeling held at the Technical University of Munich (TUM) on September 10, 2024, on "A Review of Multiscale Models of Tumor Growth".
AEOLUS co-PI Biros gives invited talk titled "Machine learning-accelerated simulations of complex fluids", at the 热门软件推荐 - Chrome插件(谷歌浏览器插件):2021-6-13 · 流星加速器 05-09 Everything - 文件搜索工具 05-19 我图网免费下载器 - ppt模板免费下载工具 05-07 EV录屏 - 高清无水印录制软件 05-07 Chrome插件推荐 Google谷歌浏览器最新版Chrome v80 ...
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