VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations. (29th March 2021)

• Record Type: Journal Article
• Authors: Groen, D.; Arabnejad, H.; Jancauskas, V.; Edeling, W. N.; Jansson, F.; Richardson, R. A.; Lakhlili, J.; Veen, L.; Bosak, B.; Kopta, P.; Wright, D. W.; Monnier, N.; Karlshoefer, P.; Suleimenova, D.; Sinclair, R.; Vassaux, M.; Nikishova, A.; Bieniek, M.; Luk, Onnie O.; Kulczewski, M.; Raffin, E.; Crommelin, D.; Hoenen, O.; Coster, D. P.; Piontek, T.; Coveney, P. V.
• Is Part Of: Philosophical transactions. Volume 379:Number 2197(2021)
• Publication Date: 2021-03-29
• Subjects: multiscale simulations -- verification -- validation -- uncertainty quantification; Physical sciences -- Periodicals; Engineering -- Periodicals; Mathematics -- Periodicals; 500
• DOI: 10.1098/rsta.2020.0221
• Languages: English
• ISSNs: 1364-503X

Abstract

Abstract : We present the VECMA toolkit (VECMAtk), a flexible software environment for single and multiscale simulations that introduces directly applicable and reusable procedures for verification, validation (V&V), sensitivity analysis (SA) and uncertainty quantication (UQ). It enables users to verify key aspects of their applications, systematically compare and validate the simulation outputs against observational or benchmark data, and run simulations conveniently on any platform from the desktop to current multi-petascale computers. In this sequel to our paper on VECMAtk which we presented last year [1 ] we focus on a range of functional and performance improvements that we have introduced, cover newly introduced components, and applications examples from seven different domains such as conflict modelling and environmental sciences. We also present several implemented patterns for UQ/SA and V&V, and guide the reader through one example concerning COVID-19 modelling in detail. This article is part of the theme issue 'Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico '.