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10.1098/rsta.2020.0221 http://scihub22266oqcxt.onion/10.1098/rsta.2020.0221 33775151!8059654!33775151     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Philos+Trans+A+Math+Phys+Eng+Sci 2021 ; 379 (2197): 20200221 Nephropedia Template TP {{tp|p=33775151|t=2021. VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations |pdf=|usr=}}{{33775151}} gab.com Text VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations JO: Philos Trans A Math Phys Eng Sci http://www.kidney.de/pget.php?&tw=1&pmid=33775151 #FOAvip 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'. Twit Text FOAVip VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations ????Philos Trans A Math Phys Eng Sci http://www.kidney.de/pget.php?&tw=1&pmid=33775151 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33775151 #FOAvip English Wikipedia <ref>{{Cite pmid|33775151}}</ref> VECMAtk: a scalable verification, validation and uncertainty quantification toolkit for scientific simulations #MMPMID33775151 Groen D; Arabnejad H; Jancauskas V; Edeling WN; Jansson F; Richardson RA; Lakhlili J; Veen L; Bosak B; Kopta P; Wright DW; Monnier N; Karlshoefer P; Suleimenova D; Sinclair R; Vassaux M; Nikishova A; Bieniek M; Luk OO; Kulczewski M; Raffin E; Crommelin D; Hoenen O; Coster DP; Piontek T; Coveney PV Philos Trans A Math Phys Eng Sci 2021[May]; 379 (2197): 20200221 PMID33775151show ga 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'. äVECMAtk: a scalable verification, validation and uncertainty quantific(epmc).pdf DeepDyve Pubget Overpricing