Date of Award
8-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Civil Engineering
Committee Chair/Advisor
M.Z naser
Committee Member
Dr. Laura Redmond
Committee Member
Dr. Brandon Ross
Committee Member
Dr. Prasad Rao Rangaraju
Abstract
When concrete is exposed to fire, it can suddenly break apart in a dangerous process called spalling. This can severely weaken buildings and even trigger a collapse. While researchers have studied this problem for years, we still don’t fully understand what causes it. My research uses a combination of data, and advanced AI techniques to identify and quantify the key factors that increase the risk of spalling. I collected data from over 1,000 fire tests and used AI models to predict when spalling might happen. I also applied explainable AI tools to understand why it happens.
The results showed that six key factors play a major role. These include how hot the fire gets, how strong the concrete is, how fast it heats up, the amount of moisture in the concrete, and whether it contains special fibers or additives. But prediction isn’t enough, we also need to understand cause and effect. To do this, I used causal AI techniques, which go beyond identifying patterns to uncovering which factors truly make spalling more or less likely. For example, I found that adding polypropylene fibers can reduce the risk of spalling by up to 31%, while too much moisture can increase the risk by more than 20%. These insights could help engineers design safer, more fire- resistant buildings and may eventually lead to clearer building code guidelines to prevent concrete failure in fires.
Recommended Citation
Al Bashiti, Mohammad, "Toward a Unified Theory of Fire-Induced Spalling of Concrete: Transcending Domain Knowledge Limitations Through Explainable Artificial Intelligence, Causal Discovery and Inference" (2025). All Dissertations. 4022.
https://open.clemson.edu/all_dissertations/4022
Author ORCID Identifier
0000-0002-3889-2564