9422696 Belyschko Health monitoring and assessment of steel bridges and other steel facilities offers tremendous potential benefits if used to asses the safety and reliability and to extend the remaining useful life by timely repairs. This project involves the development of high performance computing tools for identifying flaws in critical bridge components form the output of nondestructive evaluation (NDE) sensing devices and assessing the impact of these flaws on the useful life of the component. High performance computing tools will be developed to provide a characterization of flaws from the output of NDE sensors and asses the reliability of the component. The proposed research addresses this objective in an integrated approach which will involve the following tasks: 1. adapting ultrasonic QNDE methods to in situ health monitoring of bridges; 2. the solution of the inverse problem of identifying and characterizing the crack, which will be accomplished with the aid of neural networks; 3. development of high fidelity forward solutions of the wave equation for detailed models with one or more cracks, which are needed for the identification process; because of the large size of these problems, parallel computations will be used; 4. estimating the reliability of a component in terms of the crack which is identified. Testing of the overall model will take place on test prototypes and on actual bridges. Working groups form various states and several interested companies will be set up to facilitate dissemination of the research results to practice.
