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Abstract: Accurate prediction of the melt pool morphology evolution is a crucial foundation for realizing control of melt pool and reducing laser powder bed fusion process defects. The existing ...

Abstract: In laser powder bed fusion, a convolutional neural network could build a good regression model to predict a laser power value from a melt-pool image. To empirically validate it, we used the ...

The aim of this work was to study the main effects of acerola powder on fluidized bed agglomeration. A 2(4-1) fractional factoring design was used to evaluate the main operating conditions (fluidizing ...

† State Key Laboratory of Multi-phase Complex Systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, People’s Republic of China ‡ State Key Laboratory of Fine ...

Chemical and Environmental Engineering Department, Escuela Técnica Superior de Ingeniería, University of Seville, Camino de los descubrimientos s/n, 41092 Seville, Spain ...