BRUCE THOMPSON: ADVENTURES AND ADVANCES IN ULTRASONIC BACKSCATTER

Over the course of his professional career Dr. R. Bruce Thompson published several hundred articles on non-destructive evaluation, the majority dealing with topics in ultrasonics. One longtime research interest of Dr. Thompson, with applications both to microstructure characterization and defect detection, was backscattered grain noise in metals. Over a 20 year period he led a revolving team of staff members and graduate students investigating various aspects of ultrasonic backscatter. As a member of that team I had the privilege of working along side Dr. Thompson for many years, serving as a sort of Dr. Watson to Bruce's Sherlock Holmes. This article discusses Dr. Thompson's general approaches to modeling backscatter, the research topics he chose to explore to systematically elucidate a better understanding of the phenomena, and the many contributions to the field achieved under his leadership. The backscatter work began in earnest around 1990, motivated by a need to improve inspections of aircraft engine components. At that time Dr. Thompson launched two research efforts. The first led to the heuristic Independent Scatterer Model which could be used to estimate the average grain noise level that would be seen in any given ultrasonic inspection. There the contribution from the microstructure was contained in a measureable parameter known as the Figure-of-Merit or FOM. The second research effort, spearheaded by Dr. Jim Rose, led to a formal relationship between FOM and details of the metal microstructure. The combination of the Independent Scattering Model and Rose's formalism provided a powerful tool for investigating backscatter in metals. In this article model developments are briefly reviewed and several illustrative applications are discussed. These include: the determination of grain size and shape from ultrasonic backscatter; grain noise variability in engine-titanium billets and forgings; and the design of ultrasonic inspection systems to improve defect-signal-to-grain-noise ratios.