| 期号 |
Int. J. Simul. Multidisci. Des. Optim.
卷号 8, 2017
|
|
|---|---|---|
| 文献编号 | A10 | |
| 页数 | 8 | |
| DOI | https://doi.org/10.1051/smdo/2017003 | |
| 网上发表时间 | 2017年6月30日 | |
Research Article
Neural network computation for the evaluation of process rendering: application to thermally sprayed coatings
1
INRA, UR1268 Biopolymères Interactions Assemblages, 44300
Nantes, France
2
CMLA, ENS-Cachan, 61 av. du Président Wilson, 94235
Cachan Cedex, France
3
UTBM, 90010
Belfort Cedex, France
* e-mail: david.bassir@utbm.fr
Received:
18
May
2017
Accepted:
6
June
2017
In this work, neural network computation is attempted to relate alumina and titania phase changes of a 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 of arc current, hydrogen ratio and total plasma flow rate. For a large parameter domain, phase changes were 10% for alumina and 8% for titania with a significant control of titania phase.
Key words: Artificial neural network / Statistical analysis / Process engineering
© S. Guessasma and D. Bassir, Published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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