Additive manufacturing (AM) technology is becoming more popular for the fabrication of 3D metal products as it offers rapid prototyping and large design freedom. However, part quality and fatigue performance of components fabricated by current AM technology are not comparable to that produced by traditional methods. Post-build processing techniques, such as heat treatment (HT) and Hot Iso-static Pressing (HIP), have been developed to improve microstructure and remove internal flaws that are detrimental to fatigue resistance. In order to simulate the HT and HIP process and optimize the post-build process, an integrated computational materials engineering (ICME) approach is utilized to link the process parameters with material’s structures, properties, and fatigue performance. The purpose of this study is two-fold. First, we simulate the HT/HIP process including the physics of heat transfer, and porosity evolution. Second, a state-of-the-art hybrid optimization approach, combining response surface method and genetic algorithm is utilized to optimize the post-build process parameters in order to minimize porosities.
Abstract. The practicalities of structural fatigue testing limit the fidelity of the cyclic load history that can be applied to a test structure. Testing is, therefore, a compromise between fatigue damage fidelity and test economy. A new methodology is proposed for multiaxial loading spectrum editing to extract cycles that contribute negligible damage during fatigue crack initiation. The method is based on projection by projection (PbP) technique and wavelet transform analysis (WTA) procedure. In this approach, the cycles with negligible contribution to damage in every decoupled projected loading path (i.e. obtained from PbP approach) are extracted using the WTA procedure. Each extracted segment is then replaced with an equivalent cycle that produces the same amount of damage. The effectiveness of the edited spectrums is evaluated by the degree of fatigue damage retention as the original damage and preservation of statistical parameter values. As a case study, the proposed approach has been applied to the numerically produced random bending-torsion fatigue spectrum in plane-stress condition. The result shows an average of 75% reduction of the original spectrums with retention of 90% of the original spectrums' damage values.
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