Pub Date : 2023-02-01DOI: 10.1142/s0219876222500505
Z. Yao, J. W. Li, C. Jiang, G. Yang
This paper proposes an interval vibration analysis method for nonlinear systems subjected to uncertain excitations, through which its dynamic displacement response bounds can be calculated effectively. In the proposed method, the uncertain excitations are described using the interval process model developed by the authors in recent years. Firstly, the displacement response of a certain degree of freedom for a nonlinear system at an arbitrary time point is expressed as a function of several standard uncorrelated interval variables by using the interval K–L expansion. Secondly, two constrained optimization models are established for the lower and upper bounds of the displacement response of the nonlinear system at the time point. Thirdly, the efficient global optimization (EGO) method is used to solve the above optimization models, and the dynamic displacement response bounds of the nonlinear system can be further obtained. Finally, the effectiveness of the proposed method is verified by investigating two numerical examples.
{"title":"An Uncertain Vibration Analysis Method for Nonlinear Systems Under Interval Process Excitations","authors":"Z. Yao, J. W. Li, C. Jiang, G. Yang","doi":"10.1142/s0219876222500505","DOIUrl":"https://doi.org/10.1142/s0219876222500505","url":null,"abstract":"This paper proposes an interval vibration analysis method for nonlinear systems subjected to uncertain excitations, through which its dynamic displacement response bounds can be calculated effectively. In the proposed method, the uncertain excitations are described using the interval process model developed by the authors in recent years. Firstly, the displacement response of a certain degree of freedom for a nonlinear system at an arbitrary time point is expressed as a function of several standard uncorrelated interval variables by using the interval K–L expansion. Secondly, two constrained optimization models are established for the lower and upper bounds of the displacement response of the nonlinear system at the time point. Thirdly, the efficient global optimization (EGO) method is used to solve the above optimization models, and the dynamic displacement response bounds of the nonlinear system can be further obtained. Finally, the effectiveness of the proposed method is verified by investigating two numerical examples.","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45221422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-14DOI: 10.1142/s0219876222500530
E. Zieniuk, K. Szerszen, A. Bołtuć
The paper presents a new strategy for improving the accuracy of solutions near the boundary in the integral identity associated with the parametric integral equation system (PIES) for two-dimensional (2D) potential problems. A significant reduction in accuracy in the zone close to the boundary, also known as the boundary layer effect, is directly associated with the nearly singular properties of kernels present in the integral identity. The paper shows that these singularities can be efficiently eliminated by regularizing the integral identity with the help of the so-called regularizing function with appropriate coefficients. The analyzed examples demonstrate a significant improvement in accuracy, where all integrals of the regularized integral identity are accurately calculated using low-order standard Gauss–Legendre quadrature. The proposed regularization algorithm is independent of the actual boundary shape, its representation and assumed boundary conditions.
{"title":"A Novel Strategy for Eliminating the Boundary Layer Effect in the Regularized Integral Identity in PIES for 2D Potential Problem","authors":"E. Zieniuk, K. Szerszen, A. Bołtuć","doi":"10.1142/s0219876222500530","DOIUrl":"https://doi.org/10.1142/s0219876222500530","url":null,"abstract":"The paper presents a new strategy for improving the accuracy of solutions near the boundary in the integral identity associated with the parametric integral equation system (PIES) for two-dimensional (2D) potential problems. A significant reduction in accuracy in the zone close to the boundary, also known as the boundary layer effect, is directly associated with the nearly singular properties of kernels present in the integral identity. The paper shows that these singularities can be efficiently eliminated by regularizing the integral identity with the help of the so-called regularizing function with appropriate coefficients. The analyzed examples demonstrate a significant improvement in accuracy, where all integrals of the regularized integral identity are accurately calculated using low-order standard Gauss–Legendre quadrature. The proposed regularization algorithm is independent of the actual boundary shape, its representation and assumed boundary conditions.","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46302712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-12DOI: 10.1142/s0219876222500657
Zing L. T. Tran, Tam T. Truong, T. Nguyen-Thoi
{"title":"Optimization design of laminated functionally carbon nanotube reinforced composite plates using deep neural networks and differential evolution","authors":"Zing L. T. Tran, Tam T. Truong, T. Nguyen-Thoi","doi":"10.1142/s0219876222500657","DOIUrl":"https://doi.org/10.1142/s0219876222500657","url":null,"abstract":"","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63938289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-12DOI: 10.1142/s021987622241002x
Xuemei Liu, Xiangyu Xie, Lihai Zhang, N. Lam
{"title":"A numerical method to study the fiber orientation and distribution of fiber reinforced self-compacting concrete","authors":"Xuemei Liu, Xiangyu Xie, Lihai Zhang, N. Lam","doi":"10.1142/s021987622241002x","DOIUrl":"https://doi.org/10.1142/s021987622241002x","url":null,"abstract":"","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44775745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-12DOI: 10.1142/s0219876223500019
R. Yadav, Pratima Rai, K. Sharma
{"title":"NIPG finite element method for convection dominated diffusion problems with discontinuous data","authors":"R. Yadav, Pratima Rai, K. Sharma","doi":"10.1142/s0219876223500019","DOIUrl":"https://doi.org/10.1142/s0219876223500019","url":null,"abstract":"","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42417269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.1142/s0219876222500542
Tong Li, Zebei Mao, Yongming Cai, Bo Wang, Liang Chen
In the process of aircraft structural design, the aerodynamic load and inertial load need to be distributed from single loading points to distributed finite element (FE) nodes before strength analysis. The most commonly used loading distribution method is a Multi-Point Arrangement (MPA) method, which introduces a one-dimensional Lagrange multiplier based on the principle of minimum deformation energy, and simplifies the special-shaped 3D surface in aircraft structure to a plane. However, the actual aircraft structure contains a large number of special-shaped surfaces, and the MPA method cannot accurately distribute the loads on these complex special-shaped surfaces, affecting the accuracy of strength analysis. This paper developed a new 3D load distribution method based on multi-dimensional Lagrange multipliers (MDLM), which can simultaneously achieve an efficient and accurate distribution of surface aerodynamic loads and inertial loads in all directions. Typical numerical cases showed that when an aircraft structure model is a plane, this MDLM method converges to the traditional MPA method. For 3D special-shaped surfaces, the average error of this MDLM method is 0.77–2.28%, which is significantly smaller than the average error of the traditional MPA method (3.30–7.40%).
{"title":"A Multi-Dimensional Lagrange Multiplier Method to Identify the Load Distribution on 3D Special-Shaped Surface in the Strength Analysis of Aircraft Structure","authors":"Tong Li, Zebei Mao, Yongming Cai, Bo Wang, Liang Chen","doi":"10.1142/s0219876222500542","DOIUrl":"https://doi.org/10.1142/s0219876222500542","url":null,"abstract":"In the process of aircraft structural design, the aerodynamic load and inertial load need to be distributed from single loading points to distributed finite element (FE) nodes before strength analysis. The most commonly used loading distribution method is a Multi-Point Arrangement (MPA) method, which introduces a one-dimensional Lagrange multiplier based on the principle of minimum deformation energy, and simplifies the special-shaped 3D surface in aircraft structure to a plane. However, the actual aircraft structure contains a large number of special-shaped surfaces, and the MPA method cannot accurately distribute the loads on these complex special-shaped surfaces, affecting the accuracy of strength analysis. This paper developed a new 3D load distribution method based on multi-dimensional Lagrange multipliers (MDLM), which can simultaneously achieve an efficient and accurate distribution of surface aerodynamic loads and inertial loads in all directions. Typical numerical cases showed that when an aircraft structure model is a plane, this MDLM method converges to the traditional MPA method. For 3D special-shaped surfaces, the average error of this MDLM method is 0.77–2.28%, which is significantly smaller than the average error of the traditional MPA method (3.30–7.40%).","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42637306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-28DOI: 10.1142/s0219876222500578
Xinyu Wei, Jianbing Sang, Chuan Tian, Lifang Sun, Baoyou Liu
Research on mechanical response of single red blood cells (RBCs) to mechanical stimuli and the complex material properties of erythrocyte membranes is significant. This work proposes a novel procedure that combines nonlinear finite element method and two machine learning algorithms including Two-Way Deepnets and XGboost together with experiments to identify the hyper elastic material parameters of erythrocyte membranes. Finite element models were established to simulate the stretching process of erythrocyte optical tweezers with different constitutive material parameters from three constitutive models. And the results from the finite element analysis were carried out to generate the training sets for the neural networks. In order to validate the predictions in great detail, the finite element response curves based on the three groups of predicted constitutive parameters are compared with the experimental data. The comparison results show that the Two-Way Deepnets model has performed better efficiency and accuracy and that Reduced Polynomial can describe more precisely the hyperelastic properties of the erythrocyte membrane in the range of experimentally obtained characteristics of single RBCs. This research provides new insights into the identification of constitutive parameters of biological cell membranes, which is crucial for the future research on mechanical mechanisms of the biological cells.
{"title":"Different Types of Constitutive Parameters Red Blood Cell Membrane Based on Machine Learning and FEM","authors":"Xinyu Wei, Jianbing Sang, Chuan Tian, Lifang Sun, Baoyou Liu","doi":"10.1142/s0219876222500578","DOIUrl":"https://doi.org/10.1142/s0219876222500578","url":null,"abstract":"Research on mechanical response of single red blood cells (RBCs) to mechanical stimuli and the complex material properties of erythrocyte membranes is significant. This work proposes a novel procedure that combines nonlinear finite element method and two machine learning algorithms including Two-Way Deepnets and XGboost together with experiments to identify the hyper elastic material parameters of erythrocyte membranes. Finite element models were established to simulate the stretching process of erythrocyte optical tweezers with different constitutive material parameters from three constitutive models. And the results from the finite element analysis were carried out to generate the training sets for the neural networks. In order to validate the predictions in great detail, the finite element response curves based on the three groups of predicted constitutive parameters are compared with the experimental data. The comparison results show that the Two-Way Deepnets model has performed better efficiency and accuracy and that Reduced Polynomial can describe more precisely the hyperelastic properties of the erythrocyte membrane in the range of experimentally obtained characteristics of single RBCs. This research provides new insights into the identification of constitutive parameters of biological cell membranes, which is crucial for the future research on mechanical mechanisms of the biological cells.","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43855016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-20DOI: 10.1142/s0219876222500591
Hemant Bhardwaj, N. Adlakha
{"title":"Radial Basis Function Based Differential Quadrature Approach to Study Reaction Diffusion of Ca2+ in T Lymphocyte","authors":"Hemant Bhardwaj, N. Adlakha","doi":"10.1142/s0219876222500591","DOIUrl":"https://doi.org/10.1142/s0219876222500591","url":null,"abstract":"","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48764440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-14DOI: 10.1142/s021987622250058x
Jian Dong
{"title":"Well-balanced unstaggered central schemes based on the continuous approximation of the bottom topography","authors":"Jian Dong","doi":"10.1142/s021987622250058x","DOIUrl":"https://doi.org/10.1142/s021987622250058x","url":null,"abstract":"","PeriodicalId":54968,"journal":{"name":"International Journal of Computational Methods","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41703160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：