Assessment of the Predictive Capability of VERA—CS for CASL Challenge Problems

Abstract

This paper describes the process for assessing the predictive capability of the Consortium for the advanced simulation of light-water reactors (CASL) virtual environment for reactor applications code suite (VERA—CS) for different challenge problems. The assessment process is guided by the two qualitative frameworks, i.e., phenomena identification and ranking table (PIRT) and predictive capability maturity model (PCMM). The capability and credibility of VERA codes (individual and coupled simulation codes) are evaluated. Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements (based on PIRT) against which the VERA software is evaluated. This approach, in turn, enables the focused assessment of only those capabilities that are relevant to the challenge problem. The credibility assessment using PCMM is based on different decision attributes that encompass verification, validation, and uncertainty quantification (VVUQ) of the CASL codes. For each attribute, a maturity score from zero to three is assigned to ascertain the acquired maturity level of the VERA codes with respect to the challenge problem. Credibility in the assessment is established by mapping relevant evidence obtained from VVUQ of codes to the corresponding PCMM attribute. The illustration of the proposed approach is presented using one of the CASL challenge problems called chalk river unidentified deposit (CRUD) induced power shift (CIPS). The assessment framework described in this paper can be considered applicable to other M & S code development efforts.