SIM-AM 2025

A Thermal-History-Informed Inherent Strain Framework for Efficient Distortion Prediction in PBF-LB

  • Setien, Iñaki (LORTEK)
  • Chiumenti, Michele (CIMNE-UPC)
  • San Sebastian, Maria (LORTEK)

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Predicting distortions and residual stresses in parts fabricated by Powder Bed Fusion - Laser Beam (PBF-LB) remains a crucial challenge for ensuring dimensional accuracy and mechanical performance. Classical Inherent Strain Methods (ISM) offer a computationally efficient alternative to full thermo-mechanical simulations but often neglect spatial and temporal thermal variations, limiting predictive accuracy in complex geometries or in multi-laser processes. This work introduces an Enhanced Inherent Strain Method (EISM), which incorporates part-scale thermal evolution into the ISM framework through a part-level, layer-by-layer thermal analysis. By adjusting precomputed inherent strain tensors based on average temperature histories, the proposed method improves distortion prediction without significantly increasing computational cost. The methodology is validated on an industrial-relevant Ti-6Al-4V component manufactured via PBF-LB. The results demonstrate the importance of incorporating thermal effects at the part-scale to enhance simplified simulation strategies. The proposed method offers a promising balance between accuracy and efficiency for early-stage design and process optimisation in metal additive manufacturing.