Publications

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Abstract not provided.

This report describes the results of the FY01 Level 1 Peer Reviews for the Verification and Validation (V&V) Program at Sandia National Laboratories. V&V peer review at Sandia is intended to assess the ASCI (Accelerated Strategic Computing Initiative) code team V&V planning process and execution. The Level 1 Peer Review process is conducted in accordance with the process defined in SAND2000-3099. V&V Plans are developed in accordance with the guidelines defined in SAND2000-3 101. The peer review process and process for improving the Guidelines are necessarily synchronized and form parts of a larger quality improvement process supporting the ASCI V&V program at Sandia. During FY00 a prototype of the process was conducted for two code teams and their V&V Plans and the process and guidelines updated based on the prototype. In FY01, Level 1 Peer Reviews were conducted on an additional eleven code teams and their respective V&V Plans. This report summarizes the results from those peer reviews, including recommendations from the panels that conducted the reviews.

This document describes a proactive plan for assessing and controlling sources of risk for the ASCI (Accelerated Strategic Computing Initiative) V&V program at Sandia National Laboratories. It offers a graded approach for identifying, analyzing, prioritizing, responding to, and monitoring risks.

The US Department of Energy (DOE) Waste Isolation Pilot Plant (WIPP), located in southeast New Mexico, is a deep geologic repository for the permanent disposal of transuranic waste generated by DOE defense-related activities. Sandia National Laboratories (SNL), in its role as scientific advisor to the DOE, is responsible for evaluating the long-term performance of the WIPP. This risk-based Performance Assessment (PA) is accomplished in part through the use of numerous scientific modeling codes, which rely for some of their inputs on data gathered during characterization of the site. The PA is subject to formal requirements set forth in federal regulations. In particular, the components of the calculation fall under the configuration management and software quality assurance aegis of the American Society of Mechanical Engineers (ASME) Nuclear Quality Assurance (NQA) requirements. This paper describes SNL's implementation of the NQA requirements regarding configuration management. The complexity of the PA calculation is described, and the rationale for developing a flexible, robust run-control process is discussed. The run-control implementation is described, and its integration with the configuration-management system is then explained, to show how a calculation requiring 37,000 CPU-hours, and involving 225,000 output files totaling 95 GB, was accomplished in 5 months by two individuals, with full traceability and reproducibility.

The US Department of Energy (DOE) Waste Isolation Pilot Plant (WIPP), located in southeast New Mexico, is a deep geologic repository for the permanent disposal of transuranic waste generated by DOE defense-related activities. Sandia National Laboratories (SNL), in its role as scientific advisor to the DOE, is responsible for evaluating the long-term performance of the WIPP. This risk-based Performance Assessment (PA) is accomplished in part through the use of numerous scientific modeling codes, which rely for some of their inputs on data gathered during characterization of the site. The PA is subject to formal requirements set forth in federal regulations. In particular, the components of the calculation fall under the configuration management and software quality assurance aegis of the American Society of Mechanical Engineers (ASME) Nuclear Quality Assurance (NQA) requirements. This paper describes SNL's implementation of the NQA requirements regarding software quality assurance (SQA). The description of the implementation of SQA for a PA calculation addresses not only the interpretation of the NQA requirements, it also discusses roles, deliverables, and the resources necessary for effective implementation. Finally, examples are given which illustrate the effectiveness of SNL's SQA program, followed by a detailed discussion of lessons learned.