Articlehybrid2020

Building Confidence in Simulation: Applications of EasyVVUQ

David W. Wright · Robin A. Richardson · Wouter N. Edeling · Jalal Lakhlili · Robert C. Sinclair · Vytautas Jancauskas +13 more

38 citations0/0 files storedAdvanced Theory and Simulations

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Probabilistic and Robust Engineering Design Simulation Techniques and Applications Scientific Computing and Data Management

Abstract

Abstract Validation, verification, and uncertainty quantification (VVUQ) of simulation workflows are essential for building trust in simulation results, and their increased use in decision‐making processes. The EasyVVUQ Python library is designed to facilitate implementation of advanced VVUQ techniques in new or existing workflows, with a particular focus on high‐performance computing, middleware agnosticism, and multiscale modeling. Here, the application of EasyVVUQ to five very diverse application areas is demonstrated: materials properties, ocean circulation modeling, fusion reactors, forced human migration, and urban air quality prediction.

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References

2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates 2007Global sensitivity analysis using polynomial chaos expansions 2010Verification and Validation in Scientific Computing 2002Error and uncertainty in modeling and simulation 2015Chaospy: An open source tool for designing methods of uncertainty quantification 2020EasyVVUQ: A Library for Verification, Validation and Uncertainty Quantification in High Performance Computing 2016FabSim: Facilitating computational research through automation on large-scale and distributed e-infrastructures

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2021Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit 2021When we can trust computers (and when we can't)2021Uncertainty quantification patterns for multiscale models 2026Uncertainty Quantification for In Silico Chemistry

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