Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Special Issues
Simulation, Optimization and Application of Welding Process
share announcement

Simulation, Optimization and Application of Welding Process

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 2983

Special Issue Editors

Dr. Qian Zhi

E-Mail Website
Guest Editor
School of Materials Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
Interests: welding
Dr. Rogante Massimo

E-Mail Website
Guest Editor
Rogante Engineering Office, 62012 Civitanova Marche, Italy
Interests: characterization of welded joints by conventional and advanced (neutron and synchrotron) techniques; optimization of welding mode parameters; wire arc additive manufacturing of high entropy alloys

Special Issue Information

Dear Colleagues,

The study and development of welding techniques in the aerospace, automobile, and electronic packaging industries have been ongoing for many years. The welding process plays an essential role in the joining quality of separated components; however, the temperature evolution, welding mechanisms, and control of the welding process still require further investigations. With the advancement of computer science, simulations of welding processes have developed rapidly. Numerical simulations enable the visual simulation of the temperature distribution at the faying interface, which is favorable for predicting the weld area and joint strength. Research on the optimization of the welding process based on simulation and practice has attracted significant interest; it provides us with novel design concepts, welding flexibility, and rapid estimations of weld quality. The welding process can be applied to various materials, including metals, polymers, ceramics, etc. Studies involving the simulation, optimization, and application of welding processes have a profound significance for manufacturing industries.

This Special Issue will provide readers with the latest progress in the simulation, optimization, and application of welding processes in materials, ranging from fundamentals to phenomena, from the macro- to the micro-scale.

Contributing papers are solicited in the following areas:

  • Numerical modeling of welding processes;
  • Simulation and experimental studies of welding processes;
  • Investigations into the temperature field and welding mechanisms;
  • Optimization of welding processes;
  • Application of welding processes in specific situations.

Dr. Qian Zhi
Dr. Rogante Massimo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • welding
  • simulation
  • welding evolution
  • optimization
  • microstructure
  • weld quality

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 7607 KiB  
Article
Experimental and FEM Studies of Continuous Drive Friction Welding of Ferritic Spheroidal Graphite Cast Iron
by Radosław Winiczenko and Andrzej Skibicki
Processes 2024, 12(4), 719; https://doi.org/10.3390/pr12040719 - 02 Apr 2024
Viewed by 500
Abstract
Experimental and FEM studies of the friction welding process of spheroidal graphite cast iron (SGCI) are presented. A coupled thermal and mechanical 2.5 D FEM model was used to simulate the continuous drive friction welding (CDFW) process. The FE model predicted the peak [...] Read more.
Experimental and FEM studies of the friction welding process of spheroidal graphite cast iron (SGCI) are presented. A coupled thermal and mechanical 2.5 D FEM model was used to simulate the continuous drive friction welding (CDFW) process. The FE model predicted the peak temperature of the joint, effective stress, axial shortening, and the weld flash size. Additionally, the friction force on the axial shortening of specimens was studied. The peak temperatures were measured both on the axis and at the surface of the specimen. The predicted maximum temperatures in the axis, ½ radius, and 2 mm from the surface of the sample amounted to 1162 °C, 1177 °C, and 1061 °C, respectively. The maximum temperature of the spheroidal graphite cast iron joint was below the melting temperature of the base material (~1350 °C). The predicted temperature curves, outbursts, and shortening of welded elements indicated a good match with real models. Full article
(This article belongs to the Special Issue Simulation, Optimization and Application of Welding Process)
►▼ Show Figures

Figure 1

22 pages, 6933 KiB  
Article
Optimization of Installation Position for Complex Space Curve Weldments in Robotic Friction Stir Welding Based on Dynamic Dual Particle Swarm Optimization
by Guanchen Zong, Cunfeng Kang, Shujun Chen and Xiaoqing Jiang
Processes 2024, 12(3), 536; https://doi.org/10.3390/pr12030536 - 07 Mar 2024
Viewed by 475
Abstract
Robotic friction stir welding (RFSW), with its wide application range, ample working space, and task flexibility, has emerged as a vital development in friction stir welding (FSW) technology. However, the low stiffness of serial industrial robots can lead to end-effector deviations and vibrations [...] Read more.
Robotic friction stir welding (RFSW), with its wide application range, ample working space, and task flexibility, has emerged as a vital development in friction stir welding (FSW) technology. However, the low stiffness of serial industrial robots can lead to end-effector deviations and vibrations during FSW tasks, adversely affecting the weld quality. This paper proposes a dynamic dual particle swarm optimization (DDPSO) algorithm through a new comprehensive stability index that considers both the stiffness and vibration stability of the robot to optimize the installation position of complex space curve weldments, thereby enhancing the robot’s stability during the FSW process. The algorithm employs two independent particle swarms for exploration and exploitation tasks and dynamically adjusts task allocation and particle numbers based on current results to fully utilize computational resources and enhance search efficiency. Compared to the standard particle swarm optimization (PSO) algorithm, the DDPSO approach demonstrated superior search capabilities and stability of optimization results. The maximum fitness value improved by 4.2%, the average value increased by 12.74%, and the concentration level of optimization results rose by 72.91% on average. The new optimization method pioneers fresh perspectives for optimizing the stability of RFSW, providing significant grounds for the process optimization and offline programming of complex spatial curve weldments. Full article
(This article belongs to the Special Issue Simulation, Optimization and Application of Welding Process)
►▼ Show Figures

Figure 1

23 pages, 3902 KiB  
Article
A Numerical Simulation of the Seismic Performance and Residual Stress of Welded Joints in Building Steel Structures Based on the Finite Element Method
by Jun Peng and Xiangyu Li
Processes 2024, 12(2), 263; https://doi.org/10.3390/pr12020263 - 25 Jan 2024
Viewed by 745
Abstract
With the development of society and urbanization, higher requirements have been put forward for the safety and seismic resistance of building structures. The fatigue strength and seismic performance of welded joints have received close attention, especially as a crucial part of building steel [...] Read more.
With the development of society and urbanization, higher requirements have been put forward for the safety and seismic resistance of building structures. The fatigue strength and seismic performance of welded joints have received close attention, especially as a crucial part of building steel structure. This study used the finite element simulation method to analyze the stress-strain of welded joints in building steel structures, and explore the influence of residual stress on their seismic performance. A stress-strain calculation model for welded joints in building steel structures was studied and constructed, and the accuracy of the model was verified through numerical calculation methods. The results showed that the residual stress peaks of the horizontal and vertical directions of the V-groove welded joint structure were 475 MPa and 325 MPa, respectively, and the longitudinal residual stress peaks were 525 MPa and 425 MPa, respectively. The seismic performance of four different steel structural plates was Q960>Q690>Q460>Q345. In summary, the numerical simulation of residual stress in the seismic performance of welded joints in building steel structures, when based on the finite element method, makes a contribution of clear value to the field of seismic performance of welded joints in building steel structures. Full article
(This article belongs to the Special Issue Simulation, Optimization and Application of Welding Process)
►▼ Show Figures

Figure 1

14 pages, 6694 KiB  
Article
A Study on Defect Detection of Dissimilar Joints in Cu-STS Tubes Using Infrared Thermal Imaging of Induction Heating Brazing
by Chung-Woo Lee, Suseong Woo and Jisun Kim
Processes 2024, 12(1), 163; https://doi.org/10.3390/pr12010163 - 09 Jan 2024
Viewed by 712
Abstract
We proposed a novel detection method for identifying joint defects in the brazing process between copper tubes and stainless steel using a convolutional neural network (CNN) model. The brazing joints were created using high-frequency induction heating equipment, and infrared thermal imaging cameras were [...] Read more.
We proposed a novel detection method for identifying joint defects in the brazing process between copper tubes and stainless steel using a convolutional neural network (CNN) model. The brazing joints were created using high-frequency induction heating equipment, and infrared thermal imaging cameras were employed to capture the thermal data generated during the jointing process. The experiments involved 15.88 mm diameter copper tubes commonly used in plate heat exchangers, stainless-steel tubes, and filler metal containing 20% Ag. The thermal data were obtained with a resolution of 80 × 80 pixels per frame, resulting in 4796 normal joint data and 5437 defective joint data collected over 100 high-frequency induction-heating brazing experiments. A total of 10,233 thermal imaging data were categorized into 6548 training data, 1638 validation data, and 2047 test data for the development of the predictive model. We designed CNN models with varying hyperparameters, specifically the number of kernel filters and nodes, to evaluate their impact on detection performance. A comparative analysis revealed that a CNN model structure, exhibiting 98.53% accuracy and 99.82% recall on test data, was the most effective. The selected CNN-based defect prediction model demonstrated the potential of using CNN models to discern joint defects in tube configurations that are challenging to identify visually. This study opens avenues for applying CNN-based models for detecting imperfections in complex tube structures. Full article
(This article belongs to the Special Issue Simulation, Optimization and Application of Welding Process)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop