J. Liu, B. Jalalahmadi, Z. Liu, M. McReynolds
Keywords: additive manufacturing, part qualification, ICME, distortion and residual stress modeling, microstructure modeling
Summary:Additive Manufacturing (AM) shows great promise for reducing development time and cost for a variety of aerospace and commercial products. However, a major barrier that remains is rapid qualification of additively manufactured components. Current methods to qualify AM parts heavily rely on experimental testing, which is very expensive and time consuming. It usually takes years and hundreds/thousands of tests to fully qualify an additive part. Additionally, a minor change in designs, materials, or machine settings, would require a complete re-qualification. Computational modeling is a promising approach to obtain rapid qualification for the emerging AM technique. Sentient Corporation (Sentient) has incorporated its DigitalClone® technique to develop an ICME (integrated computational materials engineering) modeling framework for qualifying metal additive manufacturing. This ICME framework includes physics-based models to qualify AM parts at multiple levels. Specifically, Sentient’s DigitalClone technique can 1) predict the as-build residual stress, and distortion at part level; 2) predict grain structure and defects at microscale level; and 3) predict fatigue performance under different loading conditions. The modeling suite can consider the sensitivity of process parameters including power, scan speed, scan pattern, hatch spacing, pre-heating etc. This multiscale model has been validated against several AM materials (Ni alloys, Ti alloys, Al alloys, stainless steel etc.) printed at different AM platforms (SLM, EBM, LENS etc.). It is capable of virtually assessing the printing quality during and after printing. This includes potential build failure, distortion, microstructure defects, and dynamic properties. This modeling suite aims to provide customers with knowledge of compressive part quality assessment before actual printing, so it allows to optimize part design and build setting to maximize part quality.