Scalable, Trustworthy, Agile, Goal-oriented, Efficient, and Data-assimilated Data-Driven Closure Models (STAGED DDCMs)
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Neal, Kyle Daniel↗
SEARCH · Engineering Papers
Results for “Closure”
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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MACHINE LEARNING DATA-DRIVEN CLOSURE MODELS
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Schafer, Toryn↗
Framing camera approach for dynamic hole closure experiments
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Farfan, Bernardo G↗
Trustworthy and Scalable Data-Driven Closure Models
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Portone, Teresa [Sandia National Laboratories (SNL↗
Modelling Gap Closure within Vaporizing Transmission Lines of Pulsed Power Machines Using PIC-DSMC
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Kirk, Grace↗
Robust Data-Driven Turbulence Modeling for RANS Closures Using a SciML Approach for Validation
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Balakrishnan, Uma↗
SciML Credibility for Turbulence Closures
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Balakrishnan, Uma [Sandia National Laboratories (S↗
Independent Evaluation and Verification of Data-Driven RANS Closures in Turbulence Modeling
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Balakrishnan, Uma [Sandia National Laboratories (S↗
Machine Learning Data-Driven Closure Models
Our collaborators at Texas A&M will be presenting this work.
Schafer, Toryn [Texas A&M University]↗
Enabling Data-Driven Closure Models for Closed-Box Simulation Models
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Neal, Kyle Daniel [Sandia National Laboratories (S↗
Data-Driven Closure Modeling in Sparsely Observed Dynamical Systems
Our collaborators at Texas A&M will be presenting this work.
Drennan, Daniel [Texas A&M University]↗
Investigating the physical origins of anomalous, low-voltage self-closure in spark gap switches
Presentation at PPPS 2025, Berlin, Germany
Steiner, Adam Michael [Sandia National Laboratorie↗
Enhancing Turbulence Modeling for RANS Closures through Explainable Machine Learning Using SHAP Analysis
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Balakrishnan, Uma [Sandia National Laboratories (S↗
STAGED DDCM: A Framework for Closure Modeling through Data Assimilation and Machine Learning
Presentation video for ML/DL workshop
Bandy, Rileigh Jade [Sandia National Laboratories ↗
Towards Trustworthy Data-Driven Closure Models - Incorporating Input and Output Uncertainties in Neural Networks
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Smith, Paul Andrew [Sandia National Laboratories (↗
Data-Driven Closure Models (DDCMs)
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Pabon Cancel, Eric Javier [Sandia National Laborat↗
Learning turbulence with machines: data-driven closures and generative models
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general physics↗
Predicting domain structures in KxNa1-xNbO3 epitaxial thin films with phase-field simulations: Polydomains, superdomains, and flux-closure domains
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Wang, Bo [Lawrence Livermore National Laboratory]↗