Date of Graduation


Document Type


Degree Name

Master of Science in Civil Engineering (MSCE)

Degree Level



Civil Engineering


Gary S. Prinz

Committee Member

Cameron D. Murray

Second Committee Member

W. Micah Hale


carbon fiber, finite element analysis, crack mitigation, Fatigue, Multi-axial, polymer, river dams, waterway transportation infrastructure, pintle region, crack growth delay, stiffened CFRP plates, CFRP-to-steel bond


Lock gates are essential infrastructure components to the United State (US) supply chain. They create large cost savings and environmental benefits when compared with traditional methods of transport (freight and rail). Because of the large quantity of goods and dependence on these shipping chains, the US economy can be drastically affected by an unexpected gate closure. Unfortunately, many lock gates within the US have reached or exceeded their designed life. Due to the intensity of cyclic loads and the environment, fatigue cracks have become a prominent issue. Developed cracks near the pintle region (a joint which the gate rotates and rests upon) have shown to be difficult to mitigate due to the complex stresses that flow through this area. Mitigation methods commonly used for mode I cracking have been futile in the arrestment of cracks seen around the pintle because of this. These stresses are known to be multi-axial stresses which cause multi-mode cracking at the crack tips of the developed fatigue cracks.

The thesis herein presents an analytical and experimental investigation into multi-axial fatigue crack mitigation by the use of carbon fiber reinforced polymer (CFRP) capable of extending gate life into a time frame where permanent repair can occur. Detailed finite element analysis (FEA) models are used to develop and validate CFRP retrofit geometries capable of mitigating crack propagation on generalized, scaled specimens as well as a detailed model of the pintle geometry itself. Additionally, experimental crack mitigation is conducted in an attempt to validate what is found through the FEA models.