Date of Award

Fall 11-15-2025

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Civil Engineering

First Advisor

Jay Wang

Abstract

In the face of intensifying hurricanes and rising sea levels, Louisiana’s coastal highways, lifelines for communities and commerce, stand increasingly vulnerable. This thesis introduces a pioneering methodology for designing geosynthetic-reinforced highway embankments capable of withstanding wave-induced loading and rapid drawdown scenarios, the most critical failure condition identified in coastal environments. By integrating statistical wave modeling, advanced numerical simulations using SEEP/W and SLOPE/W, and a comprehensive parametric analysis, the study develops a novel hybrid regression formula that accurately predicts optimal reinforcement lengths based on site-specific geotechnical and hydraulic parameters. Validated against Hurricane Katrina data and real-world soil profiles from Cameron Parish, the model achieves a high predictive accuracy (R² = 0.91), offering engineers a practical, performance-based design tool. This research not only challenges conventional static design assumptions but also redefines geosynthetics as essential structural elements in embankment resilience. The findings pave the way for smarter, safer, and more sustainable infrastructure in hurricane-prone coastal regions.

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