Simulation-based optimization of microcomputed tomography inspection parameters for topology-optimized aerospace brackets

Innovative lightweight design, in particular using additive manufacturing (AM), is a decisive factor in reducing weight and fuel consumption in aerospace applications. The production of high-quality AM components shows high growth rates in a wide range of relevant applications, e.g. launch vehicles. However, strict regulations concerning mechanical performance necessitate a compromise between high reliability and weight savings. One goal is the large-scale production of the same product while maintaining consistently high quality, e.g. in relation to dimensional accuracy and surface properties. A major challenge in the production of failure-proof AM aerospace structures therefore concerns quality assurance, e.g. in the course of non-destructive testing. In this contribution, we non-destructively evaluate topology optimized engine brackets using X-ray microcomputed tomography (µCT). To optimize µCT inspection parameters for aluminum parts, we apply a µCT simulation pipeline. Resulting volume data is evaluated using nominal – actual comparisons in order to quantify dimensional accuracy. Actual AM parts are produced using selective laser melting and µCTscanned using the determined optimal parameter sets using an industrial µCT system. Results show that the maximum geometric deviation in simulated µCT data can be several times larger than the applied voxel size, reaching local maxima up to 0.3 mm. Those findings highlight the need for optimal scanning parameters for the µCT inspection of topology-optimized aerospace brackets to circumvent a bias when investigating the warpage of real AM parts due to suboptimal µCT image quality and severe beam-hardening artifacts.