The Verification and Validation (V&V) program conducts two major activities at Sandia. The first is to perform assessments and studies that quantify confidence in Advanced Simulation and Computing (ASC) calculation results. The second activity develops and improves V&V and uncertainty quantification methods, metrics, and standards.
This project area conducts studies and assessments for Sandia’s engineering simulation focus areas (outlined below). These assessments quantify the prediction uncertainty of the engineering codes as they apply to applications in the four focus areas.
Safety and Security
This area focuses on engineering codes as they apply to nuclear weapon. External load prediction capability includes mechanical (impact, pressure,) and thermal (propellant and hydrocarbon) environments. System response prediction capability includes mechanical (large deformation, contact, fracture), thermal (conduction, surface radiation), and lightning (arc).
This area assesses models used to predict the reliability/survivability of weapon systems and components in hostile mechanical environments and radiation-induced electrical environments. For mechanical response, the models must predict long-term response to track the flow of energy from the body exterior through the structure to elicit responses at the component level.
This area assesses modeling and simulation capabilities needed to predict weapon performance through a broad range of operational delivery environments. For re-entry systems, the operational environment includes extreme aerodynamic and aerothermodynamic conditions. For aircraft-delivered systems, the operational environment includes harsh shock and vibration conditions.
This area focuses on the physics-based simulation capabilities related to Sandia-developed nuclear weapon components, such as neutron generators, gas transfer systems, and arming, fuzing and firing systems.
Full System Models
The Full System Models activity focuses on developing, verifying, and validating models for numerous weapon systems and selected components, spanning a range of normal, abnormal, and hostile operating conditions.
The Methods project area develops and integrates new and existing methods and tools for performing code verification, solution verification, and uncertainty quantification into code products and associated simulations. This is fundamental to quantification of margins and uncertainties and the ability to be predictive through modeling and simulation.
Predictive Capability Metrics Project
The goal of the Predictive Capability Metrics Project is to develop and provide metrics on the state and improvement of predictive capability through ASC simulation tools. Researchers in this area work to understand the estimation of total uncertainty and predictive accuracy in computational simulation.
Another important activity is the Predictive Capability Assessment Project (PCAP), which baselines and tracks predictive simulation capability improvement. Approaches to PCAP include assessing simulation errors for uncalibrated models across a spectrum of stockpile systems in order to estimate the likely errors and uncertainties present when assessing untested designs.
Software Quality Engineering and Assurance
This activity helps software and capability development teams meet requirements and improve overall software quality and software project management. The team helps develop software quality engineering plans for code projects, performs internal assessments of software quality engineering practices, and delivers improvements to the software quality engineering program guidelines.
Records Management System
A centralized electronic records management system emphasizes traceability and retrievability of documented work products. It combines a web-based application and file repository with software development, records management, and quality processes to form a powerful resource for managing V&V records and documents.
This project focuses on training courses for new and novice users of V&V and uncertainty quantification tools, as well as experienced designers and analysts who have specialized needs. These specialized needs often serve as drivers for new V&V and uncertainty quantification research.