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require substantial volumes of high-quality, label led training data, which are often costly and time-intensive to generate experimentally in engineering applications. This project seeks to overcome these
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are vital to ensuring a high-quality WA-DED process. Finite element analysis (FEA) is widely used to predict the temperature field during the WA-DED process. Traditional FEA models rely heavily on
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