Xin Zhang, Jie Liu, Pu Xue, Shuowen Yan, Yahao Xu, M. S. Zahran
{"title":"An Integral Method for Solving Dynamic Equations with Fluid–Solid Coupling","authors":"Xin Zhang, Jie Liu, Pu Xue, Shuowen Yan, Yahao Xu, M. S. Zahran","doi":"10.1007/s10338-023-00434-8","DOIUrl":null,"url":null,"abstract":"<div><p>In this work, a new methodology is presented to mainly solve the fluid–solid interaction (FSI) equation. This methodology combines the advantages of the Newmark precise integral method (NPIM) and the dual neural network (DNN) method. The NPIM is employed to modify the exponential matrix and loading vector based on the DNN integral method. This involves incorporating the basic assumption of the Newmark-<i>β</i> method into the dynamic equation and eliminating the acceleration term from the dynamic equilibrium equation. As a result, the equation is reduced to a first-order linear equation system. Subsequently, the PIM is applied to integrate the system step by step within the NPIM. The DNN method is adopted to solve the inhomogeneous term through fitting the integrand and the original function with a pair of neural networks, and the integral term is solved using the Newton–Leibniz formula. Numerical examples demonstrate that the proposed methodology significantly improves computing efficiency and provides sufficient precision compared to the DNN method. This is particularly evident when analyzing large-scale structures under blast loading conditions.</p></div>","PeriodicalId":50892,"journal":{"name":"Acta Mechanica Solida Sinica","volume":"37 1","pages":"99 - 108"},"PeriodicalIF":2.0000,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Mechanica Solida Sinica","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10338-023-00434-8","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, a new methodology is presented to mainly solve the fluid–solid interaction (FSI) equation. This methodology combines the advantages of the Newmark precise integral method (NPIM) and the dual neural network (DNN) method. The NPIM is employed to modify the exponential matrix and loading vector based on the DNN integral method. This involves incorporating the basic assumption of the Newmark-β method into the dynamic equation and eliminating the acceleration term from the dynamic equilibrium equation. As a result, the equation is reduced to a first-order linear equation system. Subsequently, the PIM is applied to integrate the system step by step within the NPIM. The DNN method is adopted to solve the inhomogeneous term through fitting the integrand and the original function with a pair of neural networks, and the integral term is solved using the Newton–Leibniz formula. Numerical examples demonstrate that the proposed methodology significantly improves computing efficiency and provides sufficient precision compared to the DNN method. This is particularly evident when analyzing large-scale structures under blast loading conditions.
期刊介绍:
Acta Mechanica Solida Sinica aims to become the best journal of solid mechanics in China and a worldwide well-known one in the field of mechanics, by providing original, perspective and even breakthrough theories and methods for the research on solid mechanics.
The Journal is devoted to the publication of research papers in English in all fields of solid-state mechanics and its related disciplines in science, technology and engineering, with a balanced coverage on analytical, experimental, numerical and applied investigations. Articles, Short Communications, Discussions on previously published papers, and invitation-based Reviews are published bimonthly. The maximum length of an article is 30 pages, including equations, figures and tables