International conference on construction engineering and project management (국제학술발표논문집)

  • 2024.07a
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  • Pages.1188-1194
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  • 2024
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  • 2508-9048(eISSN)
Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Design of considering distortion after high energy manufacturing with Finite element analysis & Deep learning

  • Published : 2024.07.29
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Abstract

High-energy manufacturing processes, including laser welding, are actively being adopted not only in precision machinery industries but also in the shipbuilding and construction sectors. Laser welding, in particular, is gaining prominence in the industry due to its faster welding speed and reduced distortion compared to conventional arc welding methods. Integration of automated welding systems is anticipated to address challenges in shipbuilding and construction industries, which are currently facing a shortage of skilled labor. For successful implementation of automated welding systems, it is essential to predict and design for the post-welding effects, such as residual deformation and stresses. However, in the case of high-energy manufacturing like laser welding, the welding bead morphology differs from that of arc welding, and the heat load conditions applied during simulation are distinct. To facilitate accurate simulation predictions, the development of a suitable heat source for predicting welding bead morphology in high-energy manufacturing processes is crucial. The Block-dumping method is proposed for rapid simulation and on-site application, with the shape of the welding bead being imperative for its effectiveness. In this study, data on the welding bead morphology of Nickel-based steel was obtained. Using Deep Learning techniques, we successfully predicted the bead morphology and confirmed minimal discrepancies when compared to actual results. This outcome allows for the simulation of welding under untested conditions, offering practical applicability in the field. Additionally, we present a heat source model (heat load condition) to ensure a highly accurate interpretation of the results.

Keywords

Acknowledgement

This work was supported by Technology Innovation Program (project name : Equipment technologies for 50cm2 all solid state battery cell, project Number : 20012349) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea). This research was supported by National R&D Program through the National Research Foundation of Korea(NRF) funded by Ministry of Science and ICT(2021M3H4A3A02098099)

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