A methodology to determine the thermal diffusivity of additively manufactured jet engine blades based on laser-induced temperature field

This paper presents a new methodology for the thermal diffusivity determination of additively manufactured jet engine blades by using active infrared thermography. The technique is combined with a dedicated procedure based on deep machine learning models. The investigated samples were fabricated from different metal alloy powders by using the Laser Engineered Net Shaping (LENS®) technique. The experimental data for model development were in the form of laser shot-induced temperature fields, obtained from an original, in-house developed test apparatus. The advantage of the proposed methodology is that it can be used for the non-destructive measurements of the additively manufactured jet engine blades, which distinguishes the presented approach from the traditional laser-flash technique or other well-established methods. The obtained experimental values of the thermal diffusivity are in good agreement with data measured using the ASTM standard test method. The presented non-destructive technique has significant implementation/commercialization potential when applied to quality control or diagnostic procedures of 3D-printed parts.