Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26016
Title: Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit
Authors: Suleimenova, D
Arabnejad, H
Edeling, WN
Coster, D
Luk, OO
Lakhlili, J
Jancauskas, V
Kulczewski, M
Veen, L
Ye, D
Zun, P
Krzhizhanovskaya, V
Hoekstra, A
Crommelin, D
Coveney, PV
Groen, D
Keywords: validation;verification;sensitivity analysis;uncertainty quantification
Issue Date: 7-Jun-2021
Publisher: Elsevier
Citation: Suleimenova, D. et al. (2021) 'Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit', Journal of Computational Science, 53, 101402, pp. 1 - 19. doi: 10.1016/j.jocs.2021.101402.
Abstract: Copyright © 2021 The Author(s). The VECMA toolkit enables automated Verification, Validation and Uncertainty Quantification (VVUQ) for complex applications that can be deployed on emerging exascale platforms and provides support for software applications for any domain of interest. The toolkit has four main components including EasyVVUQ for VVUQ workflows, FabSim3 for automation and tool integration, MUSCLE3 for coupling multiscale models and QCG tools to execute application workflows on high performance computing (HPC). A more recent addition to the VECMAtk is EasySurrogate for various types of surrogate methods. In this paper, we present five tutorials from different application domains that apply these VECMAtk components to perform uncertainty quantification analysis, use surrogate models, couple multiscale models and execute sensitivity analysis on HPC. This paper aims to provide hands-on experience for practitioners aiming to test and contrast with their own applications.
URI: https://bura.brunel.ac.uk/handle/2438/26016
DOI: https://doi.org/10.1016/j.jocs.2021.101402
ISSN: 1877-7503
Other Identifiers: ORCID iDs: Diana Suleimenova https://orcid.org/0000-0003-4474-0943; Hamid Arabnejad https://orcid.org/0000-0002-0789-1825; Derek Groen https://orcid.org/0000-0001-7463-3765.
101402
Appears in Collections:Dept of Computer Science Research Papers

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