The Journal of Strain Analysis for Engineering Design最新文献

Phase field thermal shock analysis of rotating porous cracked pretwisted FGM microblade using exact shear correction factor 使用精确剪切校正因子对旋转多孔裂纹预扭曲 FGM 微刀进行相场热冲击分析

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-09-18 DOI: 10.1177/03093247241273785

Shashank Pandey

{"title":"Phase field thermal shock analysis of rotating porous cracked pretwisted FGM microblade using exact shear correction factor","authors":"Shashank Pandey","doi":"10.1177/03093247241273785","DOIUrl":"https://doi.org/10.1177/03093247241273785","url":null,"abstract":"The present work is an attempt to develop a simple and accurate finite element formulation for the thermal shock analysis of the rotating porous cracked pretwisted functionally graded material (FGM) microblade using modified coupled stress theory in conjunction with phase-field and first-order shear deformation theory (FSDT). The physical neural surface is taken as the reference plane and the exact value of the shear correction factor is calculated from the shear stiffness. The elastic properties are assumed to be temperature-dependent and the upper ceramic layer is subjected to a high thermal shock whereas the bottom metallic layer is maintained at room temperature or is thermally insulated. The governing differential equation for the present analysis is derived using Hamilton’s principle and Newmark average acceleration method is used to obtain the transient response of the rotating porous cracked pretwisted FGM microblade subjected to thermal shock. The results obtained from the present finite element formulation are first validated with several benchmark examples available in the literature. New results are presented investigating the effect of crack depth, crack location, crack angle, rotational velocity and material scale ratio on the transient response of the cracked rotating porous pretwisted FGM microblade subjected to thermal shock. It is shown here that the parameters like crack depth, crack location and crack angle have a significant influence on the transient response of the rotating porous cracked pretwisted FGM microblade.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive modeling of spring-back in pre-punched sheet roll forming using machine learning 利用机器学习对预冲孔板材辊压成型中的回弹进行预测建模

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-07-26 DOI: 10.1177/03093247241263685

Ali Zeinolabedin-Beygi, Hassan Moslemi Naeini, Hossein Talebi-Ghadikolaee, Amir Hossein Rabiee, Saeid Hajiahmadi

{"title":"Predictive modeling of spring-back in pre-punched sheet roll forming using machine learning","authors":"Ali Zeinolabedin-Beygi, Hassan Moslemi Naeini, Hossein Talebi-Ghadikolaee, Amir Hossein Rabiee, Saeid Hajiahmadi","doi":"10.1177/03093247241263685","DOIUrl":"https://doi.org/10.1177/03093247241263685","url":null,"abstract":"This study outlines an experimental and computational endeavor aimed at developing a machine learning model to estimate spring-back values utilizing the decision tree methodology. A design of experiment approach was employed to collect a dataset, and based on the experimental results, a precise model was constructed to predict spring-back values. The model considered parameters such as thickness, diameter of circle hole, distance between the center hole and flange edge, and hole spacing. Various hyper parameters, including max depth and minimum samples for split, were explored, with configurations such as (30,5), (20,8), and (10,2) being evaluated to identify the optimal model for spring-back prediction. Analysis of the results demonstrated that the decision tree models accurately estimated spring-back values in cold roll forming of pre-punched sheets based on the input parameters. The coefficient of determination in the test section for decision tree models with parameters (30,5), (20,8), and (10,2) was found to be 0.90, 0.98, and 0.96, respectively. Additionally, the percentage of absolute error in the test section for the same decision tree models was calculated as 8.84%, 6.18%, and 7.6%, respectively.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141770233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Eliminating eccentricity error in measuring residual stresses via hole-drilling method using strain gauge rosette with five measuring grids: For thin plates using through-holes 使用带有五个测量网格的应变片罗盘，通过钻孔法消除测量残余应力时的偏心误差：针对使用通孔的薄板

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-07-26 DOI: 10.1177/03093247241262178

Ying Gu, Jiaojiao Chen, Song Gu, Chao Kong, Songbo Ren, Yixiang Du

{"title":"Eliminating eccentricity error in measuring residual stresses via hole-drilling method using strain gauge rosette with five measuring grids: For thin plates using through-holes","authors":"Ying Gu, Jiaojiao Chen, Song Gu, Chao Kong, Songbo Ren, Yixiang Du","doi":"10.1177/03093247241262178","DOIUrl":"https://doi.org/10.1177/03093247241262178","url":null,"abstract":"In the measurement of residual stresses (RSs) via the hole-drilling method, the error induced by the eccentricity of the drilled hole is inevitable and non-negligible in some cases. In this study, both the eccentricity coordinates and RS state (two principal stresses and one principal angle) are considered unknowns that must be solved. A set of five equations is required to determine these five unknowns. Therefore, two additional measuring grids are added to the strain gauge comprising three grids, which is typically used in measuring RSs. Consequently, a novel strain gauge rosette with five measuring grids (SGR-5MG) is created. Subsequently, an algorithm associated with the SGR-5MG is developed to solve the five unknowns based on the Newton–Raphson method. The algorithm is elasticity-based and derived according to the layout of the SGR-5MG. Finally, the proposed method is verified numerically and experimentally. The results show that (1) the eccentricity error is up to 35.1% when the eccentricity reaches 0.05 D, where D represents the diameter of the gauge circle; (2) Using the proposed method, the error can be significantly reduced to 7.2%; (3) The elasticity-based proposed method cannot make the predicted results exactly converge to the actual stresses in predicting high stresses because of the plasticity deformation around the hole. The eccentricity error can be reduced significantly by using the proposed method based on the SGR-5MG.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141784938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Creep damage assessment of HR3C austenitic steel by using misorientation parameters derived from EBSD technique 利用 EBSD 技术得出的错误取向参数评估 HR3C 奥氏体钢的蠕变损伤

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-07-23 DOI: 10.1177/03093247241260900

Gaole Hong, Na Risu, Fubao Zhang, Maoxun Sun, Yue Zhang, Xiao Wang

引用次数: 0

3D dynamic contact analysis of tyre internal deformation using 2D image sensor 利用二维图像传感器对轮胎内部变形进行三维动态接触分析

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-05-18 DOI: 10.1177/03093247241252497

JongWook Lim, JongHwan Kim, Sung Jin Kim, KyeJoo Song, Seong Yun Kim

引用次数: 0

Investigation of the effect of anisotropy on Generalized Forming Limit Diagram 各向异性对广义成型极限图影响的研究

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-05-08 DOI: 10.1177/03093247241244564

Mohammad Mehdi Ghane Shalmani, Ali Basti, Abolfazl Taherkhani

{"title":"Investigation of the effect of anisotropy on Generalized Forming Limit Diagram","authors":"Mohammad Mehdi Ghane Shalmani, Ali Basti, Abolfazl Taherkhani","doi":"10.1177/03093247241244564","DOIUrl":"https://doi.org/10.1177/03093247241244564","url":null,"abstract":"In contemporary industrial practices, various methods are employed to subject raw metal sheets to deformation in order to fabricate requisite components. These sheets exhibit a defined capacity for deformation during the forming process. Over recent decades, a plethora of experimental and numerical methodologies have emerged to ascertain these forming limits. Initially, a forming limit diagram (FLD) was devised, predicated on the phenomenon of necking, under the assumption that forming takes place under plane-stress conditions. However, in certain complex processes like hydroforming and incremental forming, necking can manifest at sites where normal and through-thickness shear stresses act upon the sheet in addition to the in-plane stresses, rendering the plane-stress assumption inadequate for predicting forming limits in such scenarios. Thus, it becomes imperative to derive a diagram that can accurately forecast forming limits in these processes. This study aims to establish a Generalized Forming Limit Diagram (GFLD) through numerical means. GFLDs were constructed utilizing two distinct yield functions, namely Von-Mises and Hill48, for isotropic and anisotropic states, respectively. The findings reveal that normal compressive stress and through-thickness shear strain augment the formability of sheet metals. Furthermore, the outcomes illustrate that accounting for anisotropy introduces variances between diagrams in some regions of the FLD curve while the discrepancies are minor within the central regions.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Random load identification of cylindrical shell structure based on multi-layer neural network and support vector regression 基于多层神经网络和支持向量回归的圆柱形壳体结构随机载荷识别

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-04-26 DOI: 10.1177/03093247241245185

Xinliang Yang, Yanfeng Guo, Yawen Chen, Jinwei Zhao, Longlei Dong, Yanjun Lü

{"title":"Random load identification of cylindrical shell structure based on multi-layer neural network and support vector regression","authors":"Xinliang Yang, Yanfeng Guo, Yawen Chen, Jinwei Zhao, Longlei Dong, Yanjun Lü","doi":"10.1177/03093247241245185","DOIUrl":"https://doi.org/10.1177/03093247241245185","url":null,"abstract":"A new-type identification method in the frequency domain by combining a multi-layer neural network and support vector regression is proposed to identify random load of a complex cylindrical shell structure. The kernel function of support vector regression has a great influence on the prediction accuracy of machine learning model, and it is effective to employ the linear function. As the penalty factor is large, the identification accuracy of the Gaussian kernel function is close to the linear kernel function. In the process of random load identification, the prediction accuracy of the neural network using the L-BFGS method is higher than the traditional Adam method. The number of hidden layers of the neural network has little effect on the L-BFGS algorithm, but a great effect on the Adam method. Different levels of noise are introduced to verify the robustness of the machine learning model. Both the support vector regression with linear kernel function and neural network model based on the L-BFGS method have strong robustness. For the noise percentage of 1%, the support vector regression has better prediction accuracy than the neural network, yet the case is contrary for the noise percentage greater than 5%. The verification shows that the neural network model trained by simulation data has better identification accuracy for real load at some frequencies. The load identification method is proposed based on the frequency points which may establish the machine learning model. The mean absolute percentage error shows that the method based on a multi-layer neural network and support vector regression has high identification accuracy.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Static, buckling, and free vibration responses of functionally graded carbon nanotube-reinforced composite beams with elastic foundation in non-polynomial framework 非多项式框架下带弹性地基的功能分级碳纳米管增强复合梁的静态、屈曲和自由振动响应

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-04-10 DOI: 10.1177/03093247241234707

Abhijeet Babar, Rosalin Sahoo

{"title":"Static, buckling, and free vibration responses of functionally graded carbon nanotube-reinforced composite beams with elastic foundation in non-polynomial framework","authors":"Abhijeet Babar, Rosalin Sahoo","doi":"10.1177/03093247241234707","DOIUrl":"https://doi.org/10.1177/03093247241234707","url":null,"abstract":"In this work, the static, buckling, and free vibration analysis of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) beam resting on a Pasternak elastic foundation are studied. The secant function-based shear deformation theory (SFSDT) is used for this analysis. This theory fulfills the traction-free boundary conditions at the top and bottom surfaces of the beam, hence there is no need for a shear correction factor. Hamilton’s principle is used to determine the governing differential equations and boundary conditions whereas Navier’s solution technique is used for determining the closed-form solution. The analytical approach is used to examine the deflection, stresses, critical buckling load, and natural frequencies of the FG-CNTRC beam resting on the Pasternak elastic foundation including a shear layer and Winkler springs. To determine the material characteristics of FG-CNTRC beams, the Rule of the mixture is used. Uniform distribution (UD-beam), FG-X beam, FG-O beam, and FG-V beam are the different forms of CNT reinforcement distribution that are used in this study. Considering different span thickness ratios, the volume fraction and distribution of CNT, the Winkler spring, and the shear layer constant factors, all the structural responses are predicted. It is also observed that the present theory predicts the structural responses of the FG-CNTRC beam accurately when compared to other existing theories. A few new results are also included as the benchmark solutions for the new research.","PeriodicalId":517390,"journal":{"name":"The Journal of Strain Analysis for Engineering Design","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140573731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Progressive failure prediction of laminated composite thin skew plates under transverse loading using nonlinear strains 利用非线性应变预测横向加载下层状复合薄斜板的渐进破坏

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-03-30 DOI: 10.1177/03093247241240821

D. Chatterjee, Arghya Ghosh, Dipankar Chakravorty

引用次数: 0

An artificial intelligence-based approach for identifying the in-plane orthotropic mechanical properties of electronic circuit boards 基于人工智能的电子线路板平面正交机械特性识别方法

The Journal of Strain Analysis for Engineering Design Pub Date : 2024-03-28 DOI: 10.1177/03093247241240832

Mohammad A. Gharaibeh

引用次数: 0