Numerical and Experimental Study of Non-Destructive Detection of Thermal Tile System Debonding Using Short-Pulse Laser

Trivedi, Ashish; Mitra, Kunal; Subramanian, Chelakara

doi:10.2514/6.2003-3488

Cited by 2 publications

(2 citation statements)

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“…This method made use of square pulse thermography, as opposed to the scanning heating method used in the present research. In more specialized work directed toward aerospace applications, Trivedi et al [16] as well as Ng et al [17] worked on locating specific types of defects. These involved areas of low thermal resistance indicating the breakdown the of bonding of the thermal protection system tiles in spacecraft.…”

Section: Introductionmentioning

confidence: 99%

“…These involved areas of low thermal resistance indicating the breakdown the of bonding of the thermal protection system tiles in spacecraft. The objective of Reference [16] is similar to the delamination studies presented in References [3,6,9] but used laser pulses as the primary heating source. In contrast to the specialized application of these methods, the research presented herein is aimed at finding any type of defect or void, either within a material or on the surface.…”

Section: Introductionmentioning

confidence: 99%

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Detecting Material Defects Using a Scanning Laser Beam

McMasters

Brooke

David

et al. 2019

Journal of Thermophysics and Heat Transfer

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Thermal methods have been used in non-destructive testing as part of the collection of many techniques available for finding flaws in various materials. Although several types of Thermal Non-Destructive Testing (TNDT) are used on composite materials, the work presented as part of the present research is focused on plate steel samples. Defects are introduced on a steel sample prior to the start of the experiment and a scanning-laser TNTD method is used in an effort to find the defect locations. A moving line-source laser beam was utilized in an effort to scan the entire surface of a rectangular plate, pursuant to locating defects. In order to reconfigure a point beam of laser energy into a line-heating source, sheetforming optical components were used. Efforts were made to form the beam such that the intensity of the line-heating source would be as uniform as possible. The heat source was then scanned across the sample by placing the sample in a vertical position on a moving servo table which moved horizontally at a prescribed speed of 1 mm/s. This speed was chosen to allow the laser to be utilized at maximum power so as to generate the largest possible temperature gradient without exceeding a temperature rise of ten degrees centigrade. The large temperature gradient was desired in order to maximize the sensitivity of the defect-detection method, since the method of detection hinges on the principle that mechanical defects in the material generate perturbations in the measured temperature field. The relatively-small overall temperature rise of ten degrees is desired in order to allow the heat transfer to be modelled mathematically assuming constant thermal properties. A thermal camera was used for recording the temperature distribution on the non-heated side of the sample, and for this experiment, the camera used was the FLIR 8000. A series of ten images was recorded as the sample was scanned with the laser. Each image was fitted with a mathematical model. Although the thermal diffusivity of the sample is often ostensibly known, thermal diffusivity was treated as one of the unknown parameters in the fitting process. This is because there can be a variation in thermal diffusivity values within a collection of samples of a given type of materials. Moreover, the use of an accurate thermal diffusivity value in the mathematical model has a significant influence on the adequacy of the fit to the experimental data. Once the mathematical model is fitted to the experimental data by varying the thermal diffusivity and the shape of the heat flux, the calculated temperature is subtracted from the measured temperature and a residual temperature field is created. From looking at aberrations and anomalies in this residual temperature field, defects can be found by visual inspection of the residual temperature field image. As an additional feature of this research, the method of model-fitting is compared with a method involving simple spline fits and with the Mollification Method in terms of effectiveness.

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Section: Introductionmentioning

confidence: 99%