PTT System Design and Data Analysis for Improved Performance: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Argonne National Laboratory (ANL), Argonne, IL (United States); University of California, Berkeley, CA (United States)
- Argonne National Laboratory (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States)
Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Because of the geometry of metallic structures of interest for nuclear applications, which consist of planar primitives with no symmetry of revolution, limited options are available for non-destructive evaluation (NDE) either during or post manufacturing. Known material flaws in AM include low density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. As a solution to NDE of AM, we are developing pulsed thermal tomography (PTT) models and depth inversion algorithms for 3D imaging. PTT has many advantages because the method is non-contact and allows for in-service, NDE of AM nuclear reactor parts. By analyzing transients of surface temperature response due to internal thermal resistances, one can obtain 3D reconstructions of material effusively using a unique inversion algorithm developed at Argonne. This study investigates the limits of PTT capability in detection of defects in metallic plates using COMSOL numerical modeling of heat transfer. Defects are modeled as cylindrical flat bottom holes (FBH), which is a common model of calibrated material flaws in thermal tomography experiments. Materials considered in this study include stainless steel 316 (SS316), stainless steel 304 (SS304), and Inconel 718. Theoretical analyses were conducted to validate inversion of simulated PTT data with COMSOL for a plate. Subsequently, 3D reconstructions were performed on COMSOL simulations for FBH, revealing a decrease in spatial resolution over depth due to thermal diffusion. The results of this study show that the performance of the inversion algorithm for detecting smaller defects depends strongly on the depth of the defect as well as the incident heat flux. The size of detectable defect was estimated by fitting a Gaussian function to surface temperature profile. The criteria for detectability was taken as 20mK noise equivalent temperature difference (NETD), which is currently the sensitivity limit of high-performance infrared cameras. It was determined through computer simulations that the smallest detectable FBH in SS316 has a 50µm diameter and is located 0.5mm below the plate surface.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Nuclear Energy (NE), Nuclear Energy Enabling Technologies (NEET)
- DOE Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1558667
- Report Number(s):
- ANL-19/25; 154764
- Country of Publication:
- United States
- Language:
- English
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