Journal of Advanced Joining Processes最新文献

Enhancing the performance of double-flush riveted joints through hybridization with adhesive bonding 通过与胶粘接的杂交，提高双平头铆接接头的性能

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-18 DOI: 10.1016/j.jajp.2025.100324

João M.B. Alpendre , Pedro M.S. Rosado , Rui F.V. Sampaio , João P.M. Pragana , Ivo M.F. Bragança , Carlos M.A. Silva , Paulo A.F. Martins

{"title":"Enhancing the performance of double-flush riveted joints through hybridization with adhesive bonding","authors":"João M.B. Alpendre , Pedro M.S. Rosado , Rui F.V. Sampaio , João P.M. Pragana , Ivo M.F. Bragança , Carlos M.A. Silva , Paulo A.F. Martins","doi":"10.1016/j.jajp.2025.100324","DOIUrl":"10.1016/j.jajp.2025.100324","url":null,"abstract":"<div><div>This paper explores the potential to enhance the mechanical performance of joints created through a new joining-by-forming technique called hybrid double-flush riveting. To achieve this, adhesive bonding is used to form hybrid lap joints with superior mechanical properties. The study focuses on high-strength steel sheets and starts by identifying the appropriate surface conditions necessary for producing strong adhesive-bonded joints. A similar strategy is applied to construct double-flush riveted joints, focusing on the geometric variables involved in the process. Hybrid joints are then created by integrating adhesive bonding with double-flush riveting, with the second carried out before or after curing is completed. The experimental development is supported by finite element analysis conducted with an in-house computer program.</div><div>The mechanical performance of the hybrid joints is compared to that of purely adhesive-bonded and conventionally double-flush riveted joints through shear and peel destructive testing. Results demonstrate that hybrid joints ultimately provide greater joint strength for both solicitations. This allows showcasing the hybridization of double-flush riveting with adhesive bonding as an effective solution for applications where joint strength and continuity are essential.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"12 ","pages":"Article 100324"},"PeriodicalIF":3.8,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330512","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

Thermo mechanical Finite Element Analysis of the plasma Wire Arc Additive Manufacturing process in DEFORM® 13 DEFORM®13中等离子丝弧增材制造过程的热机械有限元分析

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-16 DOI: 10.1016/j.jajp.2025.100321

Marcel Czipin, Alexander Wenda, Karin Hartl, Emre Akalin, Martin Stockinger

{"title":"Thermo mechanical Finite Element Analysis of the plasma Wire Arc Additive Manufacturing process in DEFORM® 13","authors":"Marcel Czipin, Alexander Wenda, Karin Hartl, Emre Akalin, Martin Stockinger","doi":"10.1016/j.jajp.2025.100321","DOIUrl":"10.1016/j.jajp.2025.100321","url":null,"abstract":"<div><div>This study investigates the potential of Finite Element Analysis in DEFORM® to predict the thermal history, deformation, residual stress state and grain growth in the Wire Arc Additive Manufacturing processes of Ti–6Al–4V. The temperature dependent material model for Ti–6Al–4V was extended and adapted to improve the representation of contact boundary conditions within DEFORM®, focusing on Additive Manufacturing. A single layer quad-mesh approach was employed alongside dummy heat sources to simulate the process by accurate layer wise activation within the arc welding module. The model utilized a normalized double-ellipsoid heat source and introduced a power adaptation strategy to account for differences in volumetric deposition. The extracted thermal history showed very good agreement to corresponding thermocouple measurements. The accuracy of the resulting deformation state was validated using a 3D scan, while the predicted grain size distribution was compared against an as-built micrograph. The simulation showed good overall accuracy, though limitations were noted in the grain size model, which was inadequate in predicting the more complex texture of the mixed <span><math><mrow><mi>α</mi><mo>/</mo><mi>β</mi></mrow></math></span>-microstructure typical for Ti–6Al–4V. Seven heat treatment strategies were evaluated to address mechanical anisotropy. Solution annealing followed by water quenching and subsequent low temperature aging was found to be most effective.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"12 ","pages":"Article 100321"},"PeriodicalIF":3.8,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307292","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

Prediction of weld quality in laser welding of hardmetal and steel using high-speed imaging and machine learning methods 基于高速成像和机器学习方法的硬质合金和钢激光焊接焊缝质量预测

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100318

Mohammadhossein Norouzian , Mahan Khakpour , Marko Orosnjak , Atal Anil Kumar , Slawomir Kedziora

{"title":"Prediction of weld quality in laser welding of hardmetal and steel using high-speed imaging and machine learning methods","authors":"Mohammadhossein Norouzian , Mahan Khakpour , Marko Orosnjak , Atal Anil Kumar , Slawomir Kedziora","doi":"10.1016/j.jajp.2025.100318","DOIUrl":"10.1016/j.jajp.2025.100318","url":null,"abstract":"<div><div>Laser welding of steel and hardmetal presents significant challenges due to their differing material properties. Improper laser welding parameters can result in unstable joints, ultimately leading to reduced mechanical strength of the weld. Therefore, defining an optimal process window is critical to ensuring weld quality. In addition, a continuous process monitoring method like High-Speed Imaging (HSI) is essential in real industrial applications to maintain stability and detect potential defects. Understanding plume dynamics helps identify the most important features of weld quality, but it also provides deeper insight into operational parameters that discriminate different weld types. Analysis of individual image plume frames from HSI reveals distinct statistical features that are identified as unique to each welding condition. Performing systematic feature selection using plume morphology, spatter generation and weld quality, we achieved>95 % leveraging Machine Learning (ML) classifiers. Particularly, Gradient Boosting Classifier (GBC), Linear Discriminant Analysis (LDA), Multinomial Logistic Regression (MNL-LR), Support Vector Machine (SVM), and Random Forest (RF), where the RF obtained >99 % classification accuracy of weld quality. The RF was then used in performing Recursive Feature Elimination (RFE), and with the robustness analysis, we managed to reduce the number of features from forty-nine to nine features while maintaining satisfactory performance (Accuracy = 0.981, F1-score = 0.961, AUROC = 0.997). The position of the weld plume, plume eccentricity and plume width are the most essential features that lead to the improvement of node purity and classification accuracy.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100318"},"PeriodicalIF":3.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144194641","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

Corrigendum to “Exploring Wire-Arc Additive Manufactured Rivets for Joining Hybrid Electrical Busbars” “探索用于连接混合电母线的线弧添加剂制造铆钉”的勘误表

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100291

Pedro M.S. Rosado , Rui F.V. Sampaio , João P.M. Pragana , Nuno M.S. Pereira , Ivo M.F. Bragança , Carlos M.A. Silva , Paulo A.F. Martins

引用次数: 0

Enhancement of mechanical properties of thermite heat assisted friction stir welded aluminium bronze alloy (C95300) by eliminating tunnel defect 消除隧道缺陷提高铝热辅助搅拌摩擦焊铝青铜合金（C95300）的力学性能

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100317

Tamil Prabakaran S , Sudha J , Siva S , Balamurali Duraivel , Vivekananda A S

{"title":"Enhancement of mechanical properties of thermite heat assisted friction stir welded aluminium bronze alloy (C95300) by eliminating tunnel defect","authors":"Tamil Prabakaran S , Sudha J , Siva S , Balamurali Duraivel , Vivekananda A S","doi":"10.1016/j.jajp.2025.100317","DOIUrl":"10.1016/j.jajp.2025.100317","url":null,"abstract":"<div><div>Thermite Heat-Assisted Friction Stir Welding (THAFSW) is recognized as an efficient welding method for joining aluminium bronze (AB) alloys. The mechanical and metallurgical characteristics of the welded joints were analyzed and compared with those fabricated using the conventional friction stir welding (CFSW) technique. Tensile strength and hardness assessments of the welded specimens were conducted at ambient temperature. The findings revealed that the THAFSW joints exhibited superior mechanical properties, with tensile strength and elongation improving by 11 % and 25 %, respectively, compared to joints produced through the conventional approach. The strengthening mechanism of the welded joints was examined based on images captured through macroscopy, optical microscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The THAFSW process effectively eliminated tunnel defects and facilitated the development of a uniform α-phase microstructure, which contributed to enhanced mechanical performance.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100317"},"PeriodicalIF":3.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189935","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

A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization 人工智能在搅拌摩擦焊监测、建模和工艺优化中的应用综述

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100316

Mostafa Akbari , Ezatollah Hassanzadeh , Yaghuob Dadgar Asl , Amirhossein Moghanian

{"title":"A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization","authors":"Mostafa Akbari , Ezatollah Hassanzadeh , Yaghuob Dadgar Asl , Amirhossein Moghanian","doi":"10.1016/j.jajp.2025.100316","DOIUrl":"10.1016/j.jajp.2025.100316","url":null,"abstract":"<div><div>Recent advancements in artificial intelligence (AI) technologies have expanded their applications across various industrial environments, particularly in the field of Friction Stir Welding (FSW), a relatively modern manufacturing technique. AI techniques are primarily employed for modeling, monitoring, optimization, and management of complex systems influenced by multiple parameters within industrial processes. This study systematically reviews and evaluates commonly utilized AI techniques in FSW, highlighting their effectiveness, accuracy, and comparative advantages. The discussion is organized into three distinct sections, each focusing on the critical roles of AI and machine learning (ML) in FSW. The first section addresses process prediction, showcasing how AI techniques predict welding outcomes using historical data and process parameters, which enhances decision-making prior to actual implementation. The second section examines process control, emphasizing how AI systems enable real-time monitoring and adaptive control of the welding process. This functionality allows for immediate parameter adjustments, thus significantly improving weld consistency and quality by minimizing defects. Lastly, the third section pertains to the optimization of FSW parameters, illustrating how AI-driven algorithms analyze complex interactions among multiple variables to determine the most effective process settings. By adopting this structured approach, the review articulates the comprehensive benefits of integrating AI into the friction stir welding process, ultimately contributing to enhanced joint quality and improved operational efficiency.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100316"},"PeriodicalIF":3.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189936","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

Regulating intermetallic compound growth and bridging in SnAg solder under electromigration stress through Ni addition and sn crystallographic orientation-grain size 通过添加Ni和sn晶粒取向调节电迁移应力下SnAg焊料中金属间化合物的生长和桥接

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100320

Dinh-Phuc Tran, Ya-Ting Xiao, Mai-Phuong La, Shi-Chi Yang, Chih Chen

{"title":"Regulating intermetallic compound growth and bridging in SnAg solder under electromigration stress through Ni addition and sn crystallographic orientation-grain size","authors":"Dinh-Phuc Tran, Ya-Ting Xiao, Mai-Phuong La, Shi-Chi Yang, Chih Chen","doi":"10.1016/j.jajp.2025.100320","DOIUrl":"10.1016/j.jajp.2025.100320","url":null,"abstract":"<div><div>As semiconductor devices scale down, electromigration (EM) failures in interconnects become more severe, requiring effective under-bump metallization (UBM) strategies. Herein, we investigated EM failures correlated with the development of intermetallic compounds (IMCs) in two UBM structures (Cu/SnAg/Cu and Cu/SnAg/Ni/Cu). Results showed that the Ni layer resulted in thinner IMCs. It acted as a diffusion barrier, which effectively suppressed IMC growth. We also found that the IMC formation in both solder structures was significantly influenced by the Sn grain orientation. A lower <em>c</em>-axis angle of beta-Sn to EM flow associated with faster IMC formation. Sn grain size also impacted IMC growth, with larger grains resulting in slower IMC formation as a result of the reduced grain boundary density. In addition, the IMC bridging phenomenon was observed in the joints. It was found that IMC bridging occurred less frequently in Ni UBM solder joints compared to Cu/SnAg/Cu counterparts. Such a difference could be attributed to the lower solubility of Ni in Sn compared to Cu. The Ni served as a barrier, which limited the Ni dissolution into the Sn solder. It suppressed the IMC formation/growth, thereby reducing the IMC bridging probability in the Cu/SnAg/Ni/Cu joints.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100320"},"PeriodicalIF":3.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212411","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

Prediction of shrink lines in powder bed fusion of metals using a laser beam by means of a finite element simulation approach 用有限元模拟方法预测金属粉末床熔合过程中的收缩线

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-06-01 DOI: 10.1016/j.jajp.2025.100315

Dominik Rauner, Niklas Eilers, Hannes Panzer, Lukas Frei, Michael F. Zaeh

{"title":"Prediction of shrink lines in powder bed fusion of metals using a laser beam by means of a finite element simulation approach","authors":"Dominik Rauner, Niklas Eilers, Hannes Panzer, Lukas Frei, Michael F. Zaeh","doi":"10.1016/j.jajp.2025.100315","DOIUrl":"10.1016/j.jajp.2025.100315","url":null,"abstract":"<div><div>Powder bed fusion of metals using a laser beam (PBF-LB/M) enables the near-net-shape fabrication of thin-walled parts with a high geometric complexity, thus often featuring structural transitions. Due to high temperature gradients during manufacturing, these structural transitions are subject to localized deformations, which manifest themselves in a shrink line, which is reducing the part lifetime and the dimensional accuracy. In current PBF-LB/M process simulations, however, the shrink line formation cannot be predicted on a physical basis yet. In this study, a finite element approach for efficiently predicting the shrink line formation is presented. The three-stage approach begins with a numerical geometry analysis, which is used to define an appropriate finite element mesh for the subsequent analyses. This is followed by the prediction of the geometry-dependent overheating during the PBF-LB/M process. Using these overheating results and an experimentally calibrated overheating-shrink-line relation, the shrink lines are modeled in a mechanical analysis considering the physics-based effects. The simulation approach was verified on an academic specimen design and was experimentally validated on two parts with different degrees of geometric complexity. The derived overheating-shrink-line relation provided a valid strategy for predicting the resulting shrink line depth. Applying the approach, the deviation between the measurements and the shrink line simulation was determined to be lower than 41 µm. Furthermore, the prediction quality of the dimensional accuracy was increased by 6.9 % for a topology-optimized part. For the approach, necessary extensions were derived to allow for simulating an asymmetric shrink line formation in the future.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100315"},"PeriodicalIF":3.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144220957","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

Data-driven parameter optimization for bead geometry in wire arc additive manufacturing of 17-4 PH stainless steel 17-4 PH不锈钢丝弧增材制造中焊头几何参数的数据驱动优化

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-05-30 DOI: 10.1016/j.jajp.2025.100319

Muhammad Irfan , Yun-Fei Fu , Shalini Singh , Sajid Ullah Butt , Abul Fazal Arif , Osezua Ibhadode , Ahmed Qureshi

{"title":"Data-driven parameter optimization for bead geometry in wire arc additive manufacturing of 17-4 PH stainless steel","authors":"Muhammad Irfan , Yun-Fei Fu , Shalini Singh , Sajid Ullah Butt , Abul Fazal Arif , Osezua Ibhadode , Ahmed Qureshi","doi":"10.1016/j.jajp.2025.100319","DOIUrl":"10.1016/j.jajp.2025.100319","url":null,"abstract":"<div><div>Due to its high strength, corrosion resistance, and toughness, 17-4 Precipitation Hardening (PH) stainless steel is widely used in aerospace, petrochemical, and marine industries. Additive manufacturing (AM) technologies enable the fabrication of complex and/or customized components while offering superior material efficiency and shorter lead times. Because of its high deposition rate, Wire Arc Additive Manufacturing (WAAM) can produce large metal structures. However, consistent bead profiles remain challenging because the process is highly sensitive to variations in thermal input and deposition conditions. Achieving uniform bead geometry during additive manufacturing is essential to avoid defects such as humming, spattering, and distortion, which can compromise the structural integrity of 3D components.</div><div>To achieve a uniform bead profile in WAAM, in this study, a full-factorial design of experiments is implemented to optimize the process parameters such as Wire Feed Rate (WFR), Torch Travel Speed (TTS), and Gas Flow Rate (GFR) for 17-4PH stainless steel. A backpropagation neural network (BPNN) is trained to model a non-linear relationship between these process parameters and bead geometry. Moreover, a genetic algorithm (GA) optimizes for bead uniformity and deposition efficiency. With a Pearson Correlation Coefficient (PCC) of 0.85, the optimized parameters exhibited significantly improved uniformity and higher deposition efficiency.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"12 ","pages":"Article 100319"},"PeriodicalIF":3.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242889","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

Robotized hardfacing on high-strength steels: determination of impact properties with different heat inputs 高强度钢的自动化堆焊：不同热输入下冲击性能的测定

IF 3.8

Journal of Advanced Joining Processes Pub Date : 2025-05-19 DOI: 10.1016/j.jajp.2025.100314

Ákos Meilinger, Gábor Terdik

{"title":"Robotized hardfacing on high-strength steels: determination of impact properties with different heat inputs","authors":"Ákos Meilinger, Gábor Terdik","doi":"10.1016/j.jajp.2025.100314","DOIUrl":"10.1016/j.jajp.2025.100314","url":null,"abstract":"<div><div>The use of high-strength steels as a substrate for hardfacing is becoming increasingly common in the industry (e.g., for demolition shears). In the case of joint welding, the weldability of these steels is limited because welding heat has significant affect to the base material. Both softening and hardening can occur in the different sub-zones of heat-affected zone, leading to changes in impact properties. For demolition shears, impact stresses are the most critical loads. Heat input can alter the microstructure of the heat-affected zone, potentially reducing the load-bearing capacity due to the penetration depth of the hardface layer or the buffer layer. Robotization of hardfacing creates equal layers with high precision, which helps the precise comparison. In this study, S690QL and S960QL substrates were investigated under different heat inputs, and the impact properties of these specimens were tested. Instrumented impact test results were analyzed and supplemented with surface fractography. The impact resistance of the S690QL substrate decreases with higher heat input and penetration depth. In contrast, S960QL exhibits different behavior: the use of lowest heat input causes a 226 % increase in impact energy compared with the base material. The underlying reasons for this were identified through force-time curve analysis, where the positive effect of the heat-affected zone is determined. Additionally, the maximum impact forces display different behavior for the two materials: S960QL shows higher impact force except in case of highest heat input, where the S690QL shows better force. These findings are valuable for selecting the appropriate substrate and hardfacing technology for this application and its specific loading conditions.</div></div>","PeriodicalId":34313,"journal":{"name":"Journal of Advanced Joining Processes","volume":"11 ","pages":"Article 100314"},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124951","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