VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations

被引：16

作者：

Groen, D. ^{[1
,2
]}

Arabnejad, H. ^{[1
]}

Jancauskas, V ^{[3
]}

Edeling, W. N. ^{[4
]}

Jansson, F. ^{[4
,11
]}

Richardson, R. A. ^{[2
,5
]}

Lakhlili, J. ^{[6
]}

Veen, L. ^{[5
]}

Bosak, B. ^{[7
]}

Kopta, P. ^{[7
]}

Wright, D. W. ^{[2
]}

Monnier, N. ^{[8
]}

Karlshoefer, P. ^{[8
]}

Suleimenova, D. ^{[1
]}

Sinclair, R. ^{[2
]}

Vassaux, M. ^{[2
]}

Nikishova, A. ^{[9
]}

Bieniek, M. ^{[2
]}

Luk, Onnie O. ^{[6
]}

Kulczewski, M. ^{[7
]}

Raffin, E. ^{[8
]}

Crommelin, D. ^{[4
,10
]}

Hoenen, O. ^{[6
]}

Coster, D. P. ^{[6
]}

Piontek, T. ^{[7
]}

Coveney, P., V ^{[2
,9
]}

机构：

[1] Brunel Univ London, Dept Comp Sci, London, England

[2] UCL, Ctr Computat Sci, London, England

[3] Leibniz Supercomp Ctr, Garching, Germany

[4] Ctr Wiskunde & Informat, Amsterdam, Netherlands

[5] Netherlands eSci Ctr, Amsterdam, Netherlands

[6] Max Planck Inst Plasma Phys Garching, Munich, Germany

[7] Poznan Supercomp & Networking Ctr, Poznan, Poland

[8] CEPP Ctr Excellence Performance Programming, Rennes, France

[9] Univ Amsterdam, Inst Informat, Computat Sci Lab, Amsterdam, Netherlands

[10] Korteweg de Vries Inst Math, Amsterdam, Netherlands

[11] Delft Univ Technol, Dept Geosci & Remote Sensing, Delft, Netherlands

来源：

PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2021年 / 379卷 / 2197期

基金：

欧盟地平线“2020”;

关键词：

multiscale simulations; verification; validation; uncertainty quantification; MULTISCALE SIMULATIONS; FRAMEWORK;

D O I：

10.1098/rsta.2020.0221

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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'.

引用

页数：22

共 50 条

[1] Introducing VECMAtk - Verification, Validation and Uncertainty Quantification for Multiscale and HPC Simulations
Groen, Derek
Richardson, Robin A.
Wright, David W.
Jancauskas, Vytautas
Sinclair, Robert
Karlshoefer, Paul
Vassaux, Maxime
Arabnejad, Hamid
Piontek, Tomasz
Kopta, Piotr
Bosak, Bartosz
Lakhlili, Jalal
Hoenen, Olivier
Suleimenova, Diana
Edeling, Wouter
Crommelin, Daan
Nikishova, Anna
Coveney, Peter, V
[J]. COMPUTATIONAL SCIENCE - ICCS 2019, PT IV, 2019, 11539 : 479 - 492
[2] Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit*
Suleimenova, Diana
Arabnejad, Hamid
Edeling, Wouter N.
Coster, David
Luk, Onnie O.
Lakhlili, Jalal
Jancauskas, Vytautas
Kulczewski, Michal
Veen, Lourens
Ye, Dongwei
Zun, Pavel
Krzhizhanovskaya, Valeria
Hoekstra, Alfons
Crommelin, Daan
Coveney, Peter, V
Groen, Derek
[J]. JOURNAL OF COMPUTATIONAL SCIENCE, 2021, 53
[3] A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing
Roy, Christopher J.
Oberkampf, William L.
[J]. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2011, 200 (25-28) : 2131 - 2144
[4] Verification and Validation and Uncertainty Quantification of Code Models
Skorek, Tomasz
[J]. NUCLEAR TECHNOLOGY, 2019, 205 (12) : 1540 - 1553
[5] Uncertainty Quantification for Multiscale Fusion Plasma Simulations with VECMA Toolkit
Lakhlili, Jalal
Hoenen, Olivier
Luk, Onnie O.
Coster, David P.
[J]. COMPUTATIONAL SCIENCE - ICCS 2020, PT VII, 2020, 12143 : 719 - 730
[6] Potential of statistical model verification, validation and uncertainty quantification in automotive vehicle dynamics simulations: a review
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Riedmaier, Stefan
Lienkamp, Markus
[J]. VEHICLE SYSTEM DYNAMICS, 2022, 60 (04) : 1292 - 1321
[7] Unified Framework and Survey for Model Verification, Validation and Uncertainty Quantification
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Danquah, Benedikt
Schick, Bernhard
Diermeyer, Frank
[J]. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2021, 28 (04) : 2655 - 2688
[8] VERIFICATION, VALIDATION AND UNCERTAINTY QUANTIFICATION OF A NUCLEAR THERMAL HYDRAULICS CODE
Aydogan, Fatih
[J]. PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2013, VOL 6B, 2014,
[9] Unified Framework and Survey for Model Verification, Validation and Uncertainty Quantification
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Benedikt Danquah
Bernhard Schick
Frank Diermeyer
[J]. Archives of Computational Methods in Engineering, 2021, 28 : 2655 - 2688
[10] FRAMEWORK FOR CONVERGENCE AND VALIDATION OF STOCHASTIC UNCERTAINTY QUANTIFICATION AND RELATIONSHIP TO DETERMINISTIC VERIFICATION AND VALIDATION
Mousaviraad, S. Maysam
He, Wei
Diez, Matteo
Stern, Frederick
[J]. INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 2013, 3 (05) : 371 - 395

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