This award supports research on the fire behavior of timber structures to develop novel engineering methods to design mass timber buildings for fire resilience. Recent innovations in engineered wood products unlock benefits for the built environment, however, knowledge gaps in fire performance can limit adoption or lead to inadequate fire safety in buildings. To date, design has relied on empirical methods based on charring rates that do not capture the complex fire-structure interaction and the potential for collapse during the fire decay phase, highlighted by recent experiments. This project aims to derive novel modeling capabilities to enable the fire-resilient design of mass timber buildings. The research efforts will be integrated with dissemination activities involving professional committees, aimed at informing building codes. Through enabling resource-efficient designs with novel timber structures that address fire safety challenges, this award will contribute to NSF’s mission to advance the national prosperity, safety, and welfare. The goal of the research is to develop a computational framework for understanding and modeling the response of timber structures in fire and use this framework to derive design methods for fire-resilient timber buildings. The research methodology will combine computational modeling, machine learning, and topology optimization. By analyzing recent timber fire test data with Bayesian inference techniques and surrogate modeling, the proje