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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...

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Autores principales: Rammohan, Soundarapandian, Kumaran, Sundaresan Thirumalai, Uthayakumar, Marimuthu, Korniejenko, Kinga, Nykiel, Marek, Velayutham, Arumugam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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