Initial Verification and Validation Assessment for VERA

Technical Report · Sat Apr 01 04:00:00 EDT 2017

DOI:https://doi.org/10.2172/1409270· OSTI ID:1409270

Dinh, Nam ^[1]; Athe, Paridhi ^[1]; Jones, Christopher ^[2]; Hetzler, Adam ^[2]; Sieger, Matt ^[3]

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1. North Carolina State Univ., Raleigh, NC (United States)
2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

The Virtual Environment for Reactor Applications (VERA) code suite is assessed in terms of capability and credibility against the Consortium for Advanced Simulation of Light Water Reactors (CASL) Verification and Validation Plan (presented herein) in the context of three selected challenge problems: CRUD-Induced Power Shift (CIPS), Departure from Nucleate Boiling (DNB), and Pellet-Clad Interaction (PCI). Capability refers to evidence of required functionality for capturing phenomena of interest while capability refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements against which the VERA software is assessed. This approach, in turn, enables the focused assessment of only those capabilities relevant to the challenge problem. The evaluation of VERA against the challenge problem requirements represents a capability assessment. The mechanism for assessment is the Sandia-developed Predictive Capability Maturity Model (PCMM) that, for this assessment, evaluates VERA on 8 major criteria: (1) Representation and Geometric Fidelity, (2) Physics and Material Model Fidelity, (3) Software Quality Assurance and Engineering, (4) Code Verification, (5) Solution Verification, (6) Separate Effects Model Validation, (7) Integral Effects Model Validation, and (8) Uncertainty Quantification. For each attribute, a maturity score from zero to three is assigned in the context of each challenge problem. The evaluation of these eight elements constitutes the credibility assessment for VERA.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1409270
• Report Number(s): ORNL/TM-2017/229
• Country of Publication: United States
• Language: English

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