Pulsed thermography is an effective technique for quantitative prediction of defect depth within a specimen. Several methods have been reported in the literature. In this paper, using an analysis based on a theoretical one-dimensional solution of pulsed thermography, we analyzed four representative methods. We show that all of the methods are accurate and converge to the theoretical solution under ideal conditions. Three methods can be directly used to predict defect depth. However, because defect features that appear on the surface during a pulsed thermography test are always affected by three-dimensional heat conduction within the test specimen, the performance and accuracy of these methods differs for defects of various sizes and depths. This difference is demonstrated and evaluated from a set of pulsed thermography data obtained from a specimen with several flat-bottom holes as simulated defects.

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The cutting temperature and cutting force are some of the main factors that influence the surface quality of carbon fiber-reinforced polymer (CFRP). However, few investigations have been done on cutting temperature because it is difficult to capture the dynamic response of the temperature measurement system. Degradation of resin will occur within the machined surface or surface layer as the temperature exceeds the glass-transition temperature of the resin matrix. In this research, the relationship between cutting parameters and cutting temperature, cutting force were developed by response surface methodology (RSM). The experiments were designed using the tool-workpiece thermocouple technique. Taking into consideration the effect of the glass-transition temperature, the influence of cutting force and cutting temperature on surface quality of CFRP was analyzed. Analysis results showed that Spindle speed is the key parameter which influenced the cutting temperature while feed rate is the key parameter which influenced the cutting force in milling of CFRP. When the cutting temperature exceeds the glass-transition temperature (T g ), the matrix cannot provide enough support to the fibers, and the machining quality of composite material is poor.

Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with the laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer and through reconstruction of data obtained from experimental measurements. Thermal tomography reconstructions of structure shape and dimensions are shown for the Inconel 718 AM structure which has variations in the horizontal plane but is uniform along the depth dimension. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and the Inconel 718 plate is produced with the LPBF method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBHs have the same sizes as the imprinted defects in the LPBF specimens but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects and allow for estimation of their sizes and locations. Results of this study demonstrate that thermal tomography can be used for visualization and quality control in AM.

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