Description
Data-driven modeling is a cornerstone for many applications. Finding appropriate scale/level models conditioned to the data requires some type of reduced-order modeling. This workshop brings together experts working on mathematical, statistical, computational, and engineering aspects of model reduction to share their research experience.
The workshop will be hosted by Texas A&M University in College Station, Texas, and is supported by the Institute for Scientific Computation, Texas A&M Energy Institute, and Foundation CMG.
Organizing Committee
- Yalchin Efendiev, Institute for Scientific Computation
- Eduardo Gildin, Foundation CMG
- Joseph Kwon, Texas A&M Energy Institute
- Anirban Bhattacharya, Department of Statistics
- Suman Chakravorty, Department of Aerospace Engineering
- A Computationally Optimal Randomized Proper Orthogonal Decomposition Technique
- Paul Cizmas, Department of Aerospace Engineering
- A Proper Orthogonal Decomposition Method for Deforming Computational Domains
- Yalchin Efendiev, Department of Mathematics
- Some Concepts for Local Multiscale Model Reduction
- Simon Foucart, Department of Mathematics
- Computing a Quantity of Interest from Observational Data
- Irina Gaynanova, Department of Statistics
- Joint Exploratory Analysis of Multiple Heterogeneous Data Source
- Richard Gibson, Department of Geology & Geophysics
- Applications of Generalized Multiscale Finite Element Modeling to Efficient and Adaptive Seismic Imaging Techniques
- Eduardo Gildin, Department of Petroleum Engineering
- Model Reduction for Efficient Oil Reservoir Simulation and Production Optimization
- Faruque Hassan, Department of Chemical Engineering
- Data-Driven Feasibility Mapping and Optimization
- Mike King, Department of Petroleum Engineering
- Upscaling of Fluid Flow in High Contrast Systems
- Costas Kravaris, Department of Chemical Engineering
- Dynamic Model Reduction for Two-Stage Anaerobic Bioreactors
- Joseph Kwon, Department of Chemical Engineering
- Development of Local Model Reduction Technique: Application to Hydraulic Fracturing
All workshop presentations will take place in Rudder Tower (RDER) 510. Please note that the schedule is tentative and subject to change. All times listed are local time.
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- Welcome
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- Costas Kravaris, Department of Chemical Engineering
- Dynamic Model Reduction for Two-Stage Anaerobic Bioreactors
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- Joseph Kwon, Department of Chemical Engineering
- Development of Local Model Reduction Technique: Application to Hydraulic Fracturing
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- Suman Chakravorty, Department of Aerospace Engineering
- A Computationally Optimal Randomized Proper Orthogonal Decomposition Technique
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- Irina Gaynanova, Department of Statistics
- Joint Exploratory Analysis of Multiple Heterogeneous Data Source
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- Break
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- Eduardo Gildin, Department of Petroleum Engineering
- Model Reduction for Efficient Oil Reservoir Simulation and Production Optimization
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- Anirban Bhattacharya, Department of Statistics
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- Lunch Break
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- Simon Foucart, Department of Mathematics
- Computing a Quantity of Interest from Observational Data
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- Richard Gibson, Department of Geology & Geophysics
- Applications of Generalized Multiscale Finite Element Modeling to Efficient and Adaptive Seismic Imaging Techniques
- –
- Faruque Hassan, Department of Chemical Engineering
- Data-Driven Feasibility Mapping and Optimization
- –
- Break
- –
- Paul Cizmas, Department of Aerospace Engineering
- A Proper Orthogonal Decomposition Method for Deforming Computational Domains
- –
- Mike King, Department of Petroleum Engineering
- Upscaling of Fluid Flow in High Contrast Systems
- –
- Yalchin Efendiev, Department of Mathematics
- Some Concepts for Local Multiscale Model Reduction
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- Closing Remarks
Contact Information
If you have any questions concerning this workshop, email Brad Shumbera at shumbera@tamu.edu.