Acceleration of powder-bed-size thermal simulation considering scanning-path-scale through a pseudo-layer-wise equivalent heat flux model

Abstract

Part-scale modeling of the temperature field in metal powder bed additive manufacturing (AM) is critical for predicting mechanical properties of the AM-ed parts. Track-by-track heat transfer analysis is impractical due to the extensive number of layers and the intricate design of scan strategies for the heat source, particularly in the fabrication of specimen clusters or parts with complex geometry, where multiple regions in the powder bed are manufactured simultaneously. Many part-scale modeling approaches only focus on the thermal behavior of a single part without considering the thermal interaction from the surrounding parts to reduce computational cost. However, experimental observations have revealed that the temperature distribution along the building direction can vary among samples with identical local geometries. This discrepancy can be attributed to the heating effects from neighboring samples. In this study, we propose an integrated part-scale modeling framework that combines layer-wise equivalent heat flux attribution with layer-wise element activation. Before the layer-wise attribution, we justify the equivalent heat flux of individual layers through high-fidelity track-scale simulations. Unlike traditional heat transfer analysis for single parts, our analysis incorporates heat conduction effects through the powder bed between different fusion zones. The temperature data obtained from each equivalent layer using our approach shows consistency when compared to the experimental observations. This research presents an efficient, physically grounded method for modeling the thermal behavior of large AM specimen clusters, enhancing our understanding of temperature field evolution in AM and supporting the design of optimized scanning path strategies for large samples.