ASME V&V 40:2018 pdf free download

ASME V&V 40:2018 pdf free download.Assessing Credibility of Computational Modeling Through Verification and Validation: Applicationto Medical Devices.
It is incumbent upon the organization performing the V&V activities and applicability assessment to determine goals for each credibility Factor such that the overall model credibility Is commensurate with the model risk. The rationale for the credibility goals should support the desired confidence in the computational model for the COIl. It Is recommended that the participants who help establish credibility goals have the appropriate knowledge and experience to assess computational model credibility. A Phenomena Identification and RankingTable (PIRT) is a tool that can help to Identify and provide rationale for setting the goal For each credibility Factor (see Nonmandatory Appendix A For more details). NOTE: It may be valuable for stakeholders to consider how exceeding or missing a specific credibility factor goal would change the overall credibility of the computational model,
Some organizations may want to assign numerical values For each credibility factor gradation. While the numerical values or an overall numerical credibility may support internal decision making, this Standard does not prescribe quantification of the credibility Factor gradations. If the credibility of individual Factors and/or the entire model are quantified (e.g., through averaging or weighting schemes), then such quantification should not replace the critical thinking needed for a well-Informed credibility assessment
Paragraphs 5.1 through 5.3 describe the credibility factors listed in Table 5-1 in more detail.
5.1 Verification
A computational model Is the numerical implementation of an underlying mathematical model. The objective of verification is to ensure that the mathematical model is implemented correctly and then accurately solved. Verification is composed of two activities: code verification and calculation verification (ref. [1]).
5.1.1 Code Verification. The goals of code verification are to identify and remove errors in the source code and numerical algorithms of the computational software. Documented results from verification studies conducted by the software developer may be referenced to support code verification. However, the verification studies from the software developer may not encompass all aspects of the software used for the COIJ, and thus additional code verification specific to the COU may be required. Code verification activities include software quality assurance and numerical code verification.
5.1.1.1 Software QuaLity Assurance (SQA). The objective of SQA is to ensure that the software is functioning correctly and produces repeatable results on a specified computer resource in a specified software environment. Types ofcomputational model software include, but are not limited to, off-the-shelf (OTS), modified ofF-the-shelf(MOTS), and user-developed. SQA Is achieved through software validation on OTS and MOTS software and software quality development assurance on MOTS and user-developed software (refs: [3] and [6] through [9]).