Degree
Doctor of Philosophy (PhD)
Department
Burt S. Turner Department of Construction Management
Document Type
Dissertation
Abstract
Flooding remains the most recurrent and economically disruptive natural hazard in Louisiana, where resilience efforts are often hindered by fragmented regulations, inconsistent code enforcement, and limited technical capacity. This dissertation develops and validates an automated Building Information Modeling (BIM)–based rule-checking framework designed to evaluate single-family residential buildings for flood-resilience compliance with the International Residential Code (IRC, 2021), ASCE 24-14, and FEMA Technical Bulletins.
The system converts narrative regulatory provisions into machine-interpretable logic using First-Order Logic (FOL), operationalized through a JSON-based metadata schema and executed on Industry Foundation Classes (IFC) models via IfcOpenShell and Python. A total of 162 synthetic housing scenarios representing six foundation types and five flood-zone classifications were analyzed to assess system performance. Compliance outcomes across four regulatory categories—elevation and freeboard, flood openings, breakaway walls, and free-of-obstruction—were synthesized into a Regulatory Compliance Score (RCS). The RCS quantifies the degree of conformity between building designs and flood-resilient construction requirements, offering a standardized indicator for evaluating and comparing structural compliance.
This research introduces the RCS as a novel resilience indicator, enabling the automated evaluation of design compliance and providing a foundation for integrating rule-based validation into flood-resilient design practice. The proposed framework establishes a replicable, transparent, and data-driven model for regulatory automation, supporting decision-making in flood mitigation and housing policy.
The framework advances both theory and practice by uniting regulatory automation with resilience analytics, offering a scalable model for adaptive governance. It provides a replicable approach for digital code enforcement, enabling transparent, data-driven decision-making in hazard mitigation. The research concludes that the integration of logic-based automation and socio-environmental data can fundamentally transform resilience assessment from a reactive to a proactive process, positioning Louisiana as a leader in evidence-based flood governance.
Date
11-3-2025
Recommended Citation
Al-Maabreh, Osama, "AUTOMATED BIM-BASED RULE CHECKING OF FLOOD RESILIENCE REGULATIONS FOR SINGLE FAMILY HOUSES" (2025). LSU Doctoral Dissertations. 6935.
https://repository.lsu.edu/gradschool_dissertations/6935
Committee Chair
YongCheol Lee