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About
Riheng He is a researcher focused on advancing robotic welding technologies, particularly in the domain of metal inert gas (MIG) welding processes. His primary research areas include weld bead geometry prediction, numerical modeling of heat sources, and process optimization for stainless steel joining. He’s most notable contribution is the development of a novel combined heat source model—integrating Gaussian surface and Gaussian cylinder distributions—to accurately simulate and predict weld bead shape and formation during robotic MIG welding of 316L stainless steel sheets. This work, published in 2025, has already garnered early citations, signaling its relevance to both academic and industrial communities. By leveraging ANSYS software for numerical calculations, He’s research provides critical insights into process parameters, helping to reduce trial-and-error in manufacturing and improve weld quality. His achievements underscore a commitment to bridging computational modeling with practical welding applications, making his work valuable for engineers and researchers seeking to enhance automation and precision in metal fabrication.
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