Date of Award


Document Type

Thesis - Open Access


Graduate Studies

Committee Chair

Dr. Eric v. K. Hill

Committee Member

Dr. Walter P. Schimmel

Committee Member

Dr. T. David Kim


This work presents a statistical method for predicting the burst pressures in filament wound composite pressure vessels by analyzing acoustic emission data obtained during hydroproof testing. First the acoustic emission data is plotted in the form of amplitude distributions. Then, by using statistical models with characteristics similar to Rayleigh and Gaussian distributions, failure mechanism percentages are found, at which point multiple regression analysis is used to predict burst pressures. Next, the predicted burst pressures are compared to the actual burst pressures and the significance of the data is analyzed using standard statistical theories. The research shows that the predicted burst pressures are within ± 1% of the actual burst pressures. However, future experiments are required to clarify whether or not the Rayleigh and Gaussian models provide the best fit to the amplitude distributions. Finally, the problem of locating and isolating the acoustic emission sensors to remove extraneous noise must be studied.