Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations

Bond, Stephen D.; Franke, Brian C.; Lehoucq, Richard B.; Smith, John Darby; McKinley, Scott A.

doi:10.2172/1889334

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DOE OSTI · 1889334

Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations

Bond, Stephen D.·Franke, Brian C.·Lehoucq, Richard B.·Smith, John Darby·McKinley, Scott A.

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Abstract

Computational design-based optimization is a well-used tool in science and engineering. Our report documents the successful use of a particle sensitivity analysis for design-based optimization within Monte Carlo sampling-based particle simulation—a currently unavailable capability. Such a capability enables the particle simulation communities to go beyond forward simulation and promises to reduce the burden on overworked analysts by getting more done with less computation.

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Bond, Stephen D., Franke, Brian C., Lehoucq, Richard B., Smith, John Darby, McKinley, Scott A.. 2022-09-01. Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations. https://doi.org/10.2172/1889334

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