Uncertainty Quantification and Model Validation of Fire/Thermal Response Predictions

Coupled fire-environment/thermal-response models were validated using data for an object engulfed in a JP8 hydrocarbon fuel fire. Fire model predictions of heat flux were used as boundary conditions in the thermal response calculations of the object. Predictions of transient external shell temperatures as well as the surface temperatures of the embedded mass were averaged spatially and compared to data. The solution sensitivity to mesh size, time step, nonlinear iterations, and radiation rays were assessed and the uncertainties in the predictions were quantified using a Latin Hypercube Sampling (LHS) technique. The comparisons showed that the response variable was more sensitive to fire model parameters than to thermal model parameters. The observed relative difference in measurements and model predictions was also compared to the model uncertainty. The comparisons showed that the model plus uncertainty bounded the experimental data. I. Introduction Sandia National Laboratories has been engaged in testing weapon system safety in fire environments since the 1950s. Due to the high consequences involved, system safety has traditionally been demonstrated through full scale system tests, albeit with a limited number of tests. Historically developed standardized tests include the placement of a system in a fully engulfing fire for 1 hour. Systems are declared qualified and ready for production based on passage of these standardized tests and with reference to the testing and analysis during development. Beginning in the early to mid 1990’s, the DOE began a program of Science Based Stockpile Stewardship. A significant part of this program is the Advanced Simulation and Computing (ASC) program, in which modeling and simulation, through high performance computing has been applied to system development and qualification. As part of the ASC program, Sandia engaged in developing the capability to model fire environments coupled to system response in those environments. An important thrust area within the ASC program includes the advancement of the verification and validation (V&V) methodologies and uncertainty quantification techniques. Sandia National Laboratories has made strides in developing new capabilities in this area and applying them to current applications. A best estimate plus uncertainty approach has been fully adopted and incorporated into safety themes for system qualification. Providing uncertainty estimates along with deterministic results has provided value to Sandia programs and gives more insight into predictive capability. The direct contribution of this study to current and future systems is an understanding of the uncertainties in predicting internal system temperatures when an object is engulfed in a JP8 fire environment. The uncertainty in input parameters can be used with other scenarios and configurations to evaluate situations that challenge safety themes. Confidence gained in validation processes such as discussed in the current work is crucial when evaluating system qualification activities that include modeling and simulation. II. Numerical Modeling