Date of Award
Master of Science (MS)
Chowdhury , Mashrur
Pang , Weichiang
Putman , Bradley
Bridges are vital components of the United States surface transportation infrastructure and, moreover, support the growth of our nation's economy. However, over the past few decades the design capacity and service condition of many bridges in the U.S. has been challenged. Numerous incidents of bridge collapse call for an urgent need to develop a systematic method of assessing the failure risks and identifying the initiating events that can lead to a bridge collapse. This thesis presents a process of bridge failure risk analysis through fault-tree modeling and identification of specific countermeasures, to minimize failure risk, related to structural health monitoring (SHM).
The fault-tree analysis (FTA) process involves development of a visual fault-tree model, identification of minimal cut sets, assignment of basic event probabilities, and ranking of minimal cut sets according to probability of occurrence. The ranked minimal cut sets are used to identify SHM sensors that can reduce the causal factors associated with bridge failure.
The use of FTA as a risk assessment method for bridge collapse was found to be an improvement on current risk analysis methods, however, it is not a replacement. It is best used in combination with visual inspections and SHM sensors. The added benefits of FTA are its ability to identify initiating events to bridge failure through assessment of bridge components and their relationships to one another. It also has the advantage of being capable of assessing internal bridge components. These aspects make the qualitative analysis component of FTA a great tool for determining the initiating bridge failure events. The deficiencies of FTA arise in quantitative analysis. There is often a lack of numerical data available on a basic event's contribution to bridge failure; however, expert opinion, sensitivity analysis, and probabilistic ranges can sometimes provide information accurate enough for use in countermeasure assessment and application. With validation data difficult to find, the accuracy of the quantitative results cannot be quantified with certainty; therefore, more reliable probabilistic data would make FTA a more successful bridge risk assessment tool.
Davis-mcdaniel, Caitlyn, "Fault-Tree Model for Bridge Collapse Risk Analysis" (2011). All Theses. 1265.