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Prediction of Surface Roughness of an Abrasive Water Jet Cut Using an Artificial Neural Network
The study’s primary purpose was to explore the abrasive water jet (AWJ) cut machinability of stainless steel X5CrNi18-10 (1.4301). The study analyzed the effects of such process parameters as the traverse speed (TS), the depth of cut (DC), and the abrasive mass flow rate (AR) on the surface roughnes...
Autores principales: | Ficko, Mirko, Begic-Hajdarevic, Derzija, Cohodar Husic, Maida, Berus, Lucijano, Cekic, Ahmet, Klancnik, Simon |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201306/ https://www.ncbi.nlm.nih.gov/pubmed/34198903 http://dx.doi.org/10.3390/ma14113108 |
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