Data-Efficient Scientific Design Optimization with Neural Network Surrogates
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Computer science↗
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Results for “surrogates”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Subgrid-scale surrogate modeling of idealized atmospheric flows: A deep learned approach using high-resolution simulation data
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Gopalakrishnan Meena, Murali↗
Automated Discovery of DOminaNt physics Informed Surrogates (ADDONIS) Framework.
Abstract not provided.
Sockwell, Kenneth↗
Optimization-based Approaches for Design of Chemical Process Families Using ReLU Surrogates
Presentation delivered at 2023 Foundations of Computer-Aided Process Operations (FOCAPO) and Chemical Process Control (CPC) conference.
Stinchfield, Georgia↗
Optimization-based Approaches for Design of Chemical Process Families Using ReLU Surrogates
This conference paper was presented at the 2023 FOCAPO/CPC conference.
Stinchfield, Georgia↗
Framework for Optimization, Quantification of Uncertainty, and Surrogates (FOQUS) – Capabilities and Applications
Presented at the 2022 Carbon Management Project Review Meeting in Pittsburgh, PA
Deshpande, Anuja↗
Framework for Optimization, Quantification of Uncertainty, and Surrogates (FOQUS) – Demonstration
Presented at the 2022 Carbon Management Project Review Meeting in Pittsburgh, PA
Deshpande, Anuja↗
Kinetic modeling of soot formation in counterflow flames of surrogate fuel components
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Energy↗
Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics
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Mathematics and Computing↗
MEASUREMENT OF HYDROGEN GENERATION FROM SNF CLADDING SURROGATES IN A LAB-SCALE "MINI-CANISTER"
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d'Entremont, Anna L.↗
DEVELOPMENT OF AN AEROSOL-BASED METHOD FOR THE MANUFACTURE OF SURROGATE ENVIRONMENTAL TEST SWIPES
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Scott, Spencer M.↗
Optimization of Process Families for Improved Deployment of Industrial Decarbonization using ML Surrogates
This work demonstrates the IDAES process family framework and the computational benefits of these formulations on a family of transcritical CO2 refrigeration cycles to meet a range of design criteria over both cooling capacity and outside air temperature.
Stinchfield, Georgia↗
Generalization of ML-Based Surrogate Models to Dynamic Injection Schedules using Transfer Learning
For presentation at the FECM/ NETL Carbon Management Project Review Meeting, Pittsburgh, PA, August 28-September 1, 2023.
Riedl, Michael↗
Framework for Optimization, Quantification of Uncertainty and Surrogates – Updated Capabilities
This poster presents updated capabilities within the FOQUS Toolset, covering core features as well as project-based applications. Specifically, the poster highlights advancements in FOQUS integration with cloud-based clients, plugin support for machine learning tools and external simulations, sequential design of experiments, and advanced support for dynamic process models. The applications demonstrate the breadth of FOQUS predictive capabilities for chemical, energy and economic system analysis.
Paul, Brandon↗
Efficient Sampling Methods for Machine Learning Error Models with Application to Surrogates of Steady Hypersonic Flows.
Abstract not provided.
Krath, Elizabeth↗