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Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models
Rolled homogeneous armor steel (RHA) with a high tensile strength, toughness, and hardness is often used in military combat vehicles. RHA is a high-strength low alloy steel suitable for all battlefield usage in military vehicles. The present work examines the prediction output responses in the mater...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9230904/ https://www.ncbi.nlm.nih.gov/pubmed/35744427 http://dx.doi.org/10.3390/ma15124368 |
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author | Rammohan, Soundarapandian Kumaran, Sundaresan Thirumalai Uthayakumar, Marimuthu Korniejenko, Kinga Nykiel, Marek Velayutham, Arumugam |
author_facet | Rammohan, Soundarapandian Kumaran, Sundaresan Thirumalai Uthayakumar, Marimuthu Korniejenko, Kinga Nykiel, Marek Velayutham, Arumugam |
author_sort | Rammohan, Soundarapandian |
collection | PubMed |
description | Rolled homogeneous armor steel (RHA) with a high tensile strength, toughness, and hardness is often used in military combat vehicles. RHA is a high-strength low alloy steel suitable for all battlefield usage in military vehicles. The present work examines the prediction output responses in the material removal rate (MRR), surface roughness (Ra), and kerf angle (Ka) for the AWJM of armor steel using regression and semi-empirical models. The AWJM trials were performed using an L27 factorial design with each process variable set to three levels, namely, the standoff distance (SOD), jet traversing speed (JT), and jet water pressure (P). A regression model was constructed using the response surface method (RSM) and data from the trials. Through dimensional analysis and with Buckingham’s π-theorem, a semi-empirical model was built using both the experimental data and material property data. Predictions made by the models were proportionate with the results of the experiments under the same conditions. Microscopic investigations on MRR and Ra were performed using a scanning electron microscope (SEM). The optimal values of the output responses of the machined armor steel plate were obtained with higher MRR = 298.92 mm(3)/min, lower Ka = 0.651°, and lower Ra = 2.23 µm. The present work established that semi-empirical models accurately predict the output responses in the AWJM of armor steel. |
format | Online Article Text |
id | pubmed-9230904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92309042022-06-25 Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models Rammohan, Soundarapandian Kumaran, Sundaresan Thirumalai Uthayakumar, Marimuthu Korniejenko, Kinga Nykiel, Marek Velayutham, Arumugam Materials (Basel) Article Rolled homogeneous armor steel (RHA) with a high tensile strength, toughness, and hardness is often used in military combat vehicles. RHA is a high-strength low alloy steel suitable for all battlefield usage in military vehicles. The present work examines the prediction output responses in the material removal rate (MRR), surface roughness (Ra), and kerf angle (Ka) for the AWJM of armor steel using regression and semi-empirical models. The AWJM trials were performed using an L27 factorial design with each process variable set to three levels, namely, the standoff distance (SOD), jet traversing speed (JT), and jet water pressure (P). A regression model was constructed using the response surface method (RSM) and data from the trials. Through dimensional analysis and with Buckingham’s π-theorem, a semi-empirical model was built using both the experimental data and material property data. Predictions made by the models were proportionate with the results of the experiments under the same conditions. Microscopic investigations on MRR and Ra were performed using a scanning electron microscope (SEM). The optimal values of the output responses of the machined armor steel plate were obtained with higher MRR = 298.92 mm(3)/min, lower Ka = 0.651°, and lower Ra = 2.23 µm. The present work established that semi-empirical models accurately predict the output responses in the AWJM of armor steel. MDPI 2022-06-20 /pmc/articles/PMC9230904/ /pubmed/35744427 http://dx.doi.org/10.3390/ma15124368 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rammohan, Soundarapandian Kumaran, Sundaresan Thirumalai Uthayakumar, Marimuthu Korniejenko, Kinga Nykiel, Marek Velayutham, Arumugam Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title | Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title_full | Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title_fullStr | Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title_full_unstemmed | Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title_short | Prediction of Abrasive Waterjet Machining Parameters of Military-Grade Armor Steel by Semi-Empirical and Regression Models |
title_sort | prediction of abrasive waterjet machining parameters of military-grade armor steel by semi-empirical and regression models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9230904/ https://www.ncbi.nlm.nih.gov/pubmed/35744427 http://dx.doi.org/10.3390/ma15124368 |
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