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Neural network computation for the evaluation of process rendering: application to thermally sprayed coatings

Abstract : In this work, neural network computation is attempted to relate alumina and titania phase changes ofa coating microstructure with respect to energetic parameters of atmospheric plasma straying (APS) process.Experimental results were analysed using standard fitting routines and neural computation to quantify the effect ofarc current, hydrogen ratio and total plasma flow rate. For a large parameter domain, phase changes were 10% foralumina and 8% for titania with a significant control of titania phase
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https://halshs.archives-ouvertes.fr/halshs-02527153
Contributor : David Bassir <>
Submitted on : Wednesday, April 1, 2020 - 12:25:47 AM
Last modification on : Thursday, April 15, 2021 - 3:31:43 AM

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Sofiane Guessasma, David Bassir. Neural network computation for the evaluation of process rendering: application to thermally sprayed coatings. International Journal for Simulation and Multidisciplinary Design Optimization, EDP sciences/NPU (China), 2017, 8 (A10), pp.1-8. ⟨10.1051/smdo/2017003⟩. ⟨halshs-02527153⟩

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