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Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint

Axial extrusion-connection technology is one of the important connection technologies for hydraulic piping systems, with high sealing performance and mechanical strength. In this paper, the finite-element-modeling method is used to simulate the experimental process of the connection strength of the...

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Autores principales: Wu, Jianguo, Zhai, Jingyu, Yan, Yangyang, Lin, Hongwei, Chen, Siquan, Luo, Jianping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999510/
https://www.ncbi.nlm.nih.gov/pubmed/35407768
http://dx.doi.org/10.3390/ma15072433
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author Wu, Jianguo
Zhai, Jingyu
Yan, Yangyang
Lin, Hongwei
Chen, Siquan
Luo, Jianping
author_facet Wu, Jianguo
Zhai, Jingyu
Yan, Yangyang
Lin, Hongwei
Chen, Siquan
Luo, Jianping
author_sort Wu, Jianguo
collection PubMed
description Axial extrusion-connection technology is one of the important connection technologies for hydraulic piping systems, with high sealing performance and mechanical strength. In this paper, the finite-element-modeling method is used to simulate the experimental process of the connection strength of the axial extrusion joint. The generation mechanism and calculation method of the connection strength are analyzed. To optimize the joint strength, orthogonal testing and grey correlation analysis are used to analyze the influencing factors of joint strength. The key factors affecting joint strength are obtained as the friction coefficient [Formula: see text] , [Formula: see text] between joint components and the groove angle [Formula: see text] of the fittings body. The back-propagation (BP) neural-network algorithm is used to establish the connection-strength model of the joint and the genetic algorithm is used to optimize it. The optimal connection strength is 8.237 kN and the optimal combination of influencing factors is 0.2, 0.4 and 76.8°. Compared with the prediction results of the neural-network genetic algorithm, the relative error of the finite-element results is 3.9%, indicating that the method has high accuracy. The results show that the extrusion-based joining process offers significant advantages in the manufacture of high-strength titanium tubular joints.
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spelling pubmed-89995102022-04-12 Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint Wu, Jianguo Zhai, Jingyu Yan, Yangyang Lin, Hongwei Chen, Siquan Luo, Jianping Materials (Basel) Article Axial extrusion-connection technology is one of the important connection technologies for hydraulic piping systems, with high sealing performance and mechanical strength. In this paper, the finite-element-modeling method is used to simulate the experimental process of the connection strength of the axial extrusion joint. The generation mechanism and calculation method of the connection strength are analyzed. To optimize the joint strength, orthogonal testing and grey correlation analysis are used to analyze the influencing factors of joint strength. The key factors affecting joint strength are obtained as the friction coefficient [Formula: see text] , [Formula: see text] between joint components and the groove angle [Formula: see text] of the fittings body. The back-propagation (BP) neural-network algorithm is used to establish the connection-strength model of the joint and the genetic algorithm is used to optimize it. The optimal connection strength is 8.237 kN and the optimal combination of influencing factors is 0.2, 0.4 and 76.8°. Compared with the prediction results of the neural-network genetic algorithm, the relative error of the finite-element results is 3.9%, indicating that the method has high accuracy. The results show that the extrusion-based joining process offers significant advantages in the manufacture of high-strength titanium tubular joints. MDPI 2022-03-25 /pmc/articles/PMC8999510/ /pubmed/35407768 http://dx.doi.org/10.3390/ma15072433 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
Wu, Jianguo
Zhai, Jingyu
Yan, Yangyang
Lin, Hongwei
Chen, Siquan
Luo, Jianping
Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title_full Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title_fullStr Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title_full_unstemmed Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title_short Simulation and Optimization of Connection-Strength Performance of Axial Extrusion Joint
title_sort simulation and optimization of connection-strength performance of axial extrusion joint
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999510/
https://www.ncbi.nlm.nih.gov/pubmed/35407768
http://dx.doi.org/10.3390/ma15072433
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