Determination of the effect of plasma spray parameters on in-situ reaction intensity by experimental method and by means of artificial neural networks techniques
| dc.contributor.author | Durmus, H | |
| dc.contributor.author | Tekmen, C | |
| dc.contributor.author | Tsunekawa, Y | |
| dc.date.accessioned | 2025-04-10T10:30:18Z | |
| dc.date.available | 2025-04-10T10:30:18Z | |
| dc.description.abstract | In the present work, mechanically alloyed Al-12Si and SiO2 powder was deposited onto an aluminium substrate by atmospheric plasma spraying (APS) to obtain a composite coating consisting of in-situ formed alumina reinforced hypereutectic Al-18Si matrix alloy. The effects of spray parameters and in-flight particle characteristics on reaction intensity between selective powders were investigated. Obtained results are tested by artificial neural network (ANN) techniques. An ANN model is built, trained and tested. Multilayer perception model has been constructed with back propagation algorithm using the input parameters of arc current, spray distance, in-flight particle velocity and temperature. The ANN model was found able to predict the coating hardness, substrate temperature, alumina intensity and silicon intensity in the range of input parameters considered. This study demonstrates that ANN is very efficient for predicting output parameters of experimental studies. | |
| dc.identifier.e-issn | 1338-4252 | |
| dc.identifier.issn | 0023-432X | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14701/36923 | |
| dc.language.iso | English | |
| dc.title | Determination of the effect of plasma spray parameters on in-situ reaction intensity by experimental method and by means of artificial neural networks techniques | |
| dc.type | Article |