Data-Driven Optimization of Interlocking Metasurface Design
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Brown, Nathan Kenneth↗
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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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Data Driven Variational Method for Discrepancy Modeling
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Tainpakdipat, Sitanan↗
Developing data-driven strength models incorporating temperature and strain-rate dependence
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Aragon, Nicole↗
Quantifying Hall Conductivity Using Data-Driven Model Identification
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Vasey, Gina Rose↗
Data-Driven and AI approaches for Robotic Manipulation
Presentation for AI workshop at UNM.
Slightam, Jonathon↗
Robust Data-Driven Turbulence Modeling for RANS Closures Using a SciML Approach for Validation
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Balakrishnan, Uma↗
Data-Driven Sea-Ice Deformation Forecasts in the Canadian Arctic Archipelago Using DEMSI
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Nikolov, Svetoslav Valeriev [Sandia National Labor↗
Hammerstein-Wiener Data-Driven Compact Circuit Models
this is poster for the CoDA conference in Santa Fe starting February 25th
Hanson, Joshua McKinley [Sandia National Laborator↗
Data-driven compact photocurrent models
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Bochev, Pavel B. [Sandia National Laboratories (SN↗
Independent Evaluation and Verification of Data-Driven RANS Closures in Turbulence Modeling
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Balakrishnan, Uma [Sandia National Laboratories (S↗
A Data-Driven Approach to Embed Advection-Based Heat Flux Into Conduction-Only Porous Heat Transfer Models
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Kury, Matthew Wilson [Sandia National Laboratories↗
Machine Learning Data-Driven Closure Models
Our collaborators at Texas A&M will be presenting this work.
Schafer, Toryn [Texas A&M University]↗
Data-driven Reduced Modeling in the Time and Frequency Domains: Fundamentals, Best Practices, and Implementation
Minitutorial at SIAM CSE25, see https://www.siam.org/conferences-events/siam-conferences/cse25/program/minitutorials/.
McQuarrie, Shane Alexander [Sandia National Labora↗
Data-driven modifications to the Spalart-Allmaras turbulence model for High Reynolds number flow
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Jordan, Cyrus Joshua [Sandia National Laboratories↗
Enabling Data-Driven Closure Models for Closed-Box Simulation Models
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Neal, Kyle Daniel [Sandia National Laboratories (S↗
MINLP for regularized symbolic regression with applications to data-driven modeling of critical minerals processes
The poster summarizes recent advances in symbolic regression developed as part of the PrOMMiS project over the past year. In particular, it describes the comparison of surrogates for critical minerals (CM) & rare earth element (REE) recovery flowsheets obtained via symbolic regression and ALAMO. It also compares the predictive ability and solvability of optimization models that incorporate these surrogates.
36 MATERIALS SCIENCE↗
MINLP for regularized symbolic regression with applications to data-driven discovery of physical laws
The slides summarize recent advances in symbolic regression developed as part of the PrOMMiS project over the past year. It describes the use of various regularization metrics in the context of symbolic regression, and it includes computational experiments performed to build simple and accurate symbolic regression models.
97 MATHEMATICS AND COMPUTING↗
Explainable Machine Learning for Data-Driven Turbulence Modeling in Compressible Fluid Flows Using SHAP Analysis
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Balakrishnan, Uma [Sandia National Laboratories (S↗