Ultrasonic testing uses high frequency sound waves to determine the state of materials without intrusion. The technique can be applied to flaw detection, small cracks due to fatigue, material characterization, and other applications. Nonlinear ultrasonic testing differs from its linear counterpart on the consideration of large amplitude of sound wave; therefore it has capabilities of detecting microstructural variations in aged steel. The measurable characteristics in nonlinear ultrasonic testing are influenced by various types and distribution of microstructural defects and cracks. This award supports fundamental research to understand the correlation between ultrasonic wave characteristics and microstructural damage. The research will develop a paradigm to detect damage in steel using ultrasonic waves by combining numerical modeling and experimental measurements. The research can be applied to structural health inspection of aging civil infrastructure such as truss bridges, pipelines, nuclear power plants, etc. Early detection of damage and subsequent repairs can extend life of structures. The results of this research will benefit the U.S. economy and society. This research involves disciplines of computational mechanics, sensing and monitoring, and material science. The interdisciplinary approach will impact the education in the Science, Technology, Engineering, and Math disciplines.
Nonlinear ultrasonic testing detects microstructural variations through measuring high order harmonics; however, the nonlinear coefficient extracted from high order harmonics is influenced by the heterogeneous damage distribution and the various damage types. Although they can be assessed using experimental methods, it is practically infeasible to consider all variables in damage distribution and types when conducting nonlinear ultrasonic testing in situ. The research is to predict changes in the ultrasonic waves due to heterogeneous damage distribution in steel alloys using multi-scale numerical modeling and experiments. The micro-scale model containing material heterogeneity and microstructure will be created from micrographs to obtain nonlinear properties of damaged materials, which will then be utilized in macro scale models to assess damage. The multi-scale framework will allow modeling microstructural changes in the material and their effects on the behavior of the component. The changes in ultrasonic signal will be quantified and compared with changes in mechanical properties characterized via mechanical testing and microstructural analysis using other nondestructive evaluation techniques.
