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http://hdl.handle.net/2080/1922
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DC Field | Value | Language |
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dc.contributor.author | Behera, Ajit | - |
dc.contributor.author | Mishra, S C | - |
dc.contributor.author | Behera, A | - |
dc.contributor.author | Dhal, J P | - |
dc.date.accessioned | 2013-04-16T11:46:46Z | - |
dc.date.available | 2013-04-16T11:46:46Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Journal of Materials, Volume 2013, Article ID 150671, 6 pages | en |
dc.identifier.uri | http://dx.doi.org/10.1155/2013/150671 | - |
dc.identifier.uri | http://hdl.handle.net/2080/1922 | - |
dc.description | Copyright belongs to proceeding publisher | en |
dc.description.abstract | The present piece of work describes the industrial wastes and low grade ores (fly ash + quartz + ilmenite, as the coating material), deposited onmild steel substrates. Inmany cases it is found that porosity is an important factor on the coating surface. Knowledge about the extent of these porosity imperfections is critical since they influence awide range of spray coated properties and behaviors. To decrease the porosity by optimizing necessary operating parameters, artificial neural network (ANN) technique is used.The aim of this investigation is to find out appropriate input vectors in ANN model. ANN experimental results indicate that the projection network has good generalization capability to optimize the porosity. | en |
dc.format.extent | 773653 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | Hindawi Publishing Corporation | en |
dc.title | Porosity Analysis of Plasma Sprayed Coating by Application of Soft Computing | en |
dc.type | Article | en |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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porosity.pdf | 755.52 kB | Adobe PDF | View/Open |
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