Defining Computational Emissivity Uncertainty Over Large Temperature Scales Due to Surface Evolution

There is a dearth in the literature on how to capture the uncertainty generated by material surface evolution in thermal modeling. This leads to inadequate or highly variable uncertainty representations for material properties, specifically emissivity when minimal information is available. Inaccurate understandings of prediction uncertainties may lead decision makers to incorrect conclusions, so best engineering practices should be developed for this domain. In order to mitigate the aforementioned issues, this study explores different strategies to better capture the thermal uncertainty response of engineered systems exposed to fire environments via defensible emissivity uncertainty characterizations that can be easily adapted to a variety of use cases. Two unique formulations (one physics-informed and one mathematically based) are presented. The formulations and methodologies presented herein are not exhaustive but more so are a starting point and give the reader a basis for how to customize their uncertainty definitions for differing fire scenarios and materials. Finally, the impact of using this approach versus other commonly used strategies and the usefulness of adding rigor to material surface evolution uncertainty is demonstrated.