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Robust experimental data assimilation for the Spalart-Allmaras turbulence model
Not provided.
Involute Working Group – Validation of CFD Turbulence Models for Steady-State Safety Analysis of Corner Geometry
Worldwide, three research reactors have fuel plates curved as a circle-involute (a spiral generated around a circle): Oak Ridge National Laboratory High Flux Isotope Reactor located in Tennessee, U.S.A. [1], Institut Laue-Langevin High Flux Reactor located in Grenoble, France [2], and Technical University of Munich Research Neutron Source Heinz Maier-Leibnitz located in Garching, Germany [3]. All three reactors are currently using highly enriched uranium ( 235 U/U ≥ 20 wt%) as fuel, and all three are actively engaged in activities to convert to low-enriched uranium ( 235 U/U < 20 wt%) fuel.
Assembling training datasets for generalizable machine-learned turbulence models.
Abstract not provided.
Assembling training datasets for generalizable machine-learned turbulence models.
Abstract not provided.
Turbulence modeling for compressible flows using discrepancy tensor-basis neural networks and extrapolation detection .
Abstract not provided.
Uncertainty Propagation of the Negative Spalart-Allmaras Turbulence Model Coefficients using Projection-based Reduced-Order Models.
Abstract not provided.
Robust Data-Driven Turbulence Modeling for RANS Closures Using a SciML Approach for Validation
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Independent Evaluation and Verification of Data-Driven RANS Closures in Turbulence Modeling
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Data-driven modifications to the Spalart-Allmaras turbulence model for High Reynolds number flow
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Explainable Machine Learning for Data-Driven Turbulence Modeling in Compressible Fluid Flows Using SHAP Analysis
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Enhancing Turbulence Modeling for RANS Closures through Explainable Machine Learning Using SHAP Analysis
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Computational Design of a Supersonic Expansion-Compression Experiment for Turbulence Model Development
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Implementation of k-L RANS turbulence model in a high-order finite element code
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Uncertainty Propagation of the Negative Spalart-Allmaras Turbulence Model Coefficients using Projection-based Reduced-Order Models.
Abstract not provided.