Pressure Welding Research Articles

Estimation of Quality of Seam Welds in AlMgSi(Cu) Extrusion by Using an Original Device for Weldability Testing.

Extrusion welding of AlMgSi(Cu) alloys is carried out by using porthole dies, as a result of which hollow shapes are formed with longitudinal seam welds. In the case of the inappropriate selection of the chemical composition of the aluminium alloy or improper metal welding conditions, the weld may have reduced strength in relation to that of the base material, thus weakening the strength of structures based on aluminium extrudates. The prediction of metal welding conditions, depending on the chemical composition of the alloy, the temperature and the unit welding pressures, effectively supports the design of porthole dies, thus significantly reducing the number of necessary extrusion tests and die geometry corrections needed during its implementation in industrial practice, and consequently significantly reducing production costs. In this work, an original laboratory test device simulating the behaviour of metal in a welding chamber of a porthole die was applied to examine the ability of AlMgSi(Cu) alloys to produce high-quality joints. Two different chemical compositions of AlMgSi(Cu) aluminium alloys differing in Mg, Si and Cu contents were used: alloy no. 1A (0.68% wt. Mg, 1.04% wt. Si, 0.61% wt. Cu) and alloy no. 3A (0.8% wt. Mg, 1.21% wt. Si, 1.22% wt. Cu). The weldability tests were carried out under various welding temperatures of 450, 500 and 550 °C and under various welding pressures of 150 MPa, 250 MPa and 350 MPa. The microstructural changes in the produced welds were evaluated with the use of OM and SEM/EDS with chemical analysis in micro-areas, whereas the mechanical effects were evaluated by using a static tensile test. Samples after static tensile testing were subjected to fractographic tests to determine the nature of the fractures. The highest values of relative weld strength were obtained under the highest welding temperature of 550 °C and the highest unit welding pressure of 350 MPa: 87% for alloy number 1/1A (high-strength weld), and 62% for alloy number 6/3A (medium-strength weld). Finally, the extrusion tests were performed in industrial conditions with an examination of the EBSD structure and strength of the longitudinal welds. High values of relative weld strength for extrudates from alloy no. 1/1A and alloy no. 3A, 96% and 89%, respectively, were found, which confirmed the previous weldability testing results.

A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

Abstract Inverse uncertainty quantification commonly uses the well established Bayesian framework. Recently, alternative interval methodologies have been introduced. However, in their current state of the art implementation, both techniques suffer from a large and usually unpredictable computational effort. Thus, both techniques are not applicable in a real-time context. To achieve a low-cost, real-time solution to this inverse problem, we introduce a deep-learning framework consisting of unsupervised auto-encoders and a shallow neural network. This framework is trained by means of a numerically generated dataset that captures typical relations between the model parameters and selected measured system responses. The performance and efficacy of the technique is illustrated using two distinct case studies. The first case involves the DLR AIRMOD, a benchmark case that has served as reference case for the inverse uncertainty quantification problem. The results demonstrate that the achieved accuracy is on par with the existing interval method found in literature, while requiring only a fraction of its computational resources. The second case study examines a resistance pressure welding process, which is known to require extremely fast monitoring and control due to the high process throughput. Based on the proposed method, and with only a limited selection of simulated responses of the process, it is possible to identify the interval uncertainty of the crucial parameters of the process. The computational cost in this case makes it possible for an inverse uncertainty quantification in a real-time setting.

Investigation of the Process Parameters in Rotary Friction Welded Dissimilar AA7075/AA5083 Aluminum Alloy Joints on Fatigue Initiation using FEA and ANN

The rotary friction welding (RFW) method is one of the most widespread methods in the world for producing bimetallic components that require high mechanical strength. Simulations play a vital role in improving energy efficiency and reducing environmental impact, aligning with the sustainability goals of modern industry. A neural network (NN)-based incremental learning system was developed to predict crack growth and fatigue for AA5083 and AA7075 aluminum alloys. The results indicate the ability of this method to accommodate the input temperatures and the S-N curve and provide reliable predictions of expected fatigue. This method can reduce labor costs and time spent on crack propagation tests, enhancing the effectiveness of production processes and reducing process costs. This work also reveals the ability of neural . It maynetworks (NN) in monotonic function extrapolation like the S-N curve, which may pave the way for a wide variety of monotonic function-predicting problems. In future studies, a neural network (NN)-based increment learning scheme could be trained with random parts of individual S–N curves and applied to predict the rest. Additionally, the verification utilizing AISI 2205 and AISI 1020 steel has observed that neural networks may obtain S-N curve values for another metal with less than an 8% error rate. Friction pressure increases temperature, deformation, and stress in welding processes. Friction pressure 17 MPa increases temperature to 355 degrees Celsius, while Friction pressure 23 MPa increases deformation to 0.020 mm. A friction pressure of 29 MPa increases equivalent stress to 110 MPa. The indication of the S-N curve shows that increasing welding pressure increases Alternating Stress. Friction pressure also increases life, with minimum life cycles reaching 171040 cycles at 17 MPa, 195560 cycles at 23 MPa, and 283690 cycles at 29 MPa. Comparing research and simulation results, convergence is less than 8%, reducing error.

Development of the technology of pressure welding with a magnetically impelled arc of small-diameter pipes using supercapacitors

Development of the technology of pressure welding with a magnetically impelled arc of small-diameter pipes using supercapacitors

An improved Coati Optimization Algorithm with multiple strategies for engineering design optimization problems

Aiming at the problems of insufficient ability of artificial COA in the late optimization search period, loss of population diversity, easy to fall into local extreme value, resulting in slow convergence and lack of exploration ability; In this paper, an improved COA algorithm based on chaotic sequence, nonlinear inertia weight, adaptive T-distribution variation strategy and alert updating strategy is proposed to enhance the performance of COA (shorted as TNTWCOA). The algorithm introduces chaotic sequence mechanism to initialize the position. The position distribution of the initial solution is more uniform, the high quality initial solution is generated, the population richness is increased, and the problem of poor quality and uneven initial solution of the Coati Optimization Algorithm is solved. In exploration phase, the nonlinear inertial weight factor is introduced to coordinate the local optimization ability and global search ability of the algorithm. In the exploitation phase, adaptive T-distribution variation is introduced to increase the diversity of individual population under low fitness value and improve the ability of the algorithm to jump out of the local optimal value. At the same time, the alert update mechanism is proposed to improve the alert ability of COA algorithm, so that it can search within the optional range. When Coati is aware of the danger, Coati on the edge of the population will quickly move to the safe area to obtain a better position, while Coati in the middle of the population will randomly move to get closer to other Coatis. IEEE CEC2017 with 29 classic test functions were used to evaluate the convergence speed, convergence accuracy and other indicators of TNTWCOA algorithm. Meanwhile, TNTWCOA was used to verify 4 engineering design optimization problems, such as pressure vessel optimization design and welding beam design. The results of IEEE CEC2017 and engineering design Optimization problems are compared with Improved Coati Optimization Algorithm (ICOA), Coati Optimization Algorithm (COA), Golden Jackal Optimization Algorithm (GJO), Osprey Optimization Algorithm (OOA), Sand Cat Swarm Optimization Algorithm (SCSO), Subtraction-Average-Based Optimizer (SABO). The experimental results show that the improved TNTWCOA algorithm significantly improves the convergence speed and optimization accuracy, and has good robustness. Three‑bar truss design problem, The Gear Train Design Problem, Speed reducer design problem shows a strong solution advantage. The superior optimization ability and engineering practicability of TNTWCOA algorithm are verified.

A novel low-resistance solder-free copper bonding joint using a warm pressure welding method for REBCO coated conductors

Abstract Constrained by the fabrication of second-generation high-temperature superconducting (2G HTS) tapes, connecting multiple pieces of tapes through joints is often necessary in large-scale applications. In the application of HTS magnets, joint technology is key for achieving closed-loop operation and reducing thermal loads. However, most soldered joints still cannot achieve the expected results. Thus, there is an urgent need to find a method for easily fabricating low-resistance joints. In this study, a low-resistance solder-free copper bonding joint for 2G HTS copper-plated tapes is proposed. The formation mechanism of the joint is presented, and the effects of the bonding temperature and pressure on the electrical and mechanical properties of the copper bonding joint are investigated. The results show that the copper bonding joint can be manufactured by pretreating the tape for 5 minutes and bonding it in the air for 3 minutes at 333 MPa at temperatures higher than (or equal to) 150 °C or at pressures greater than (or equal to) 250 MPa and 180 °C. The characteristic resistance of this joint is approximately 16.8 nΩ·cm2, which is approximately one-third lower than that of soldered joints, and it has mechanical properties similar to those of soldered joints under axial tension. We believe that the application of this type of copper bonding joint can significantly aid in the design and manufacturing of large HTS magnets.

Influence of Pyrolysis Products on the Formation of a Joint During Pressure Welding Through a Layer of Hydrocarbon Substance

Influence of Pyrolysis Products on the Formation of a Joint During Pressure Welding Through a Layer of Hydrocarbon Substance

A new method of magnetic pulse welding of dissimilar metal plates using a uniform pressure electromagnetic actuator based on pre-deformation

The magnetic pulse welding method using a uniform pressure electromagnetic actuator can effectively weld dissimilar metal plates. However, the existing uniform pressure welding method leads to serious thinning of the plate at the chamfer, lack of welding at the center, and bulging of the welded sample, which seriously affects the quality of the welded joint. To solve these problems and improve the quality of welded joints, a new uniform pressure welding method of dissimilar metal plates based on pre-deformation was developed in this work. In this study, using the welding of an AA1060 aluminum plate and an SS304 steel plate with a thickness of 1 mm as an example, it was confirmed through numerical simulation and experimental research that the pre-deformation of the flyer plate controlled the impact angle of the central area of the plate, and it effectively suppressed central non-welding and serious bulge issues. Further, the welding method also reduced the height of the cushion blocks on both sides, thus mitigating aluminum plate thinning at the chamfer, ultimately improving the tensile strength of the joint. Additionally, a microscopic observation showed that the welding interface formed a wavy composite interface, and the connection strength was good. This welding method can also be extended to welding other dissimilar metal plates.

Ultrasonic Welding of Acrylonitrile-Butadiene-Styrene Thermoplastics without Energy Directors.

Ultrasonic welding (USW) of thermoplastics plays a significant role in the automobile industry. In this study, the effect of the welding time on the joint strength of ultrasonically welded acrylonitrile-butadiene-styrene (ABS) and the weld formation mechanism were investigated. The results showed that the peak load firstly increased to a maximum value of 3.4 kN and then dropped with further extension of the welding time, whereas the weld area increased continuously until reaching a plateau. The optimal welding variables for the USW of ABS were a welding time of 1.3 s with a welding pressure of 0.13 MPa. Interfacial failure and workpiece breakage were the main failure modes of the joints. The application of real-time horn displacement into a finite element model could improve the simulation accuracy of weld formation. The simulated results were close to the experimental results, and the welding process of the USW of ABS made with a 1.7 s welding time can be divided into five phases based on the amplitude and horn displacement change: weld initiation (Phase I), horn retraction (Phase II), melt-and-flow equilibrium (Phase III), horn indentation and squeeze out (Phase IV) and weld solidification (Phase V). Obvious pores emerged during Phase IV, owing to the thermal decomposition of the ABS. This study yielded a fundamental understanding of the USW of ABS and provides a theoretical basis and technological support for further application and promotion of other ultrasonically welded thermoplastic composites.

QUALITY ASPECTS IN THE WELDING OF SOME ELEMENTS OF MICRO-MOTORS IN AUTOMOTIVE AND HOUSEHOLD APPLIANCES INDUSTRY

In the automotive and household appliances industry, there is a permanent concern to find fast and efficient welding methods and technologies, pressure welding being one of the usual joining methods, due to the minimum qualification requirements, cheap equipment, ease of control, high speed of operation, repeatability and suitability for automation or robotization for inclusion in high production assembly lines. In the paper, quality aspects are described in spot welding of some elements of micro-motors in the automotive industry and household appliances by using tools that allow highlighting the fact that the process is controllable from a statistical point of view, concerning two micro-motors from the production flow.

Continuous Drive Friction Welded Al/Cu Joints Produced Using Short Welding Time, Elevated Rotational Speed, and High Welding Pressures.

The present study aimed to enhance the efficiency and efficacy of the Al/Cu joint production process implemented by the company VEMID Ltd., Jagodina, Serbia, by attaining sound joints within a very short welding time. For this purpose, the present study aimed at investigating the accuracy and the quality of the continuous drive friction welding (CDFW) process, as well as the optimum combination of CDFW parameters with highest joint efficiency in terms of investigated properties. The accuracy was estimated through an analysis of temperature-time curves recorded during CDFW using an infrared camera. The quality was evaluated through an investigation of the properties of Al/Cu joints produced using different friction (66.7, 88.9, and 133.3 MPa) and forging (88.9, 222.2, and 355.6 MPa) pressures and a constant total welding time (4 s) and rotational speed (2100 rpm). Thermal imaging with an infrared camera demonstrated that the actual total welding time was 15% longer compared to the nominal value. This was attributed to the slow pressure response of the pneumatic brake system. The relative changes in the maximum surface temperature (TMS) during the CDFW process corresponded to changes in welding pressures, indicating the potential of the thermal imaging method for monitoring and assessing this process. A preliminary investigation demonstrated that Al/Cu joints produced using welding pressures less than 88.9 MPa often displayed the presence of non-joined micro-regions at the Al/Cu interface and a significant thickness of interfacial Al2Cu (up to 1 µm). However, when friction pressure was set at 66.7 MPa, an increase in the forging pressure to 222.2 MPa eliminated the presence of non-joined micro-regions and reduced the thickness of Al2Cu to 0.5 µm on the average level. These Al/Cu joints achieved the highest joint efficiencies in terms of strength (100%) and ductility (61%). They exhibited an electrical conductivity higher than 92% of the theoretical value. A further increase in any welding pressure produced similar or deteriorated properties, accompanied by an increase in the consumption of raw materials and energy. Such turn of events was counterproductive to the original goal of increasing the efficiency and efficacy of the CDFW process.

Friction Stir Welding Benefits Technique over Other Welding Techniques of Dissimilar Metals

Abstract: Due to the low heat input situation, solid state welding (SSW) has demonstrated higher potential for integrating a variety of equivalent and dissimilar material combinations. The temperature stays below the melting point of the source materials throughout the solid-state welding process. Compared to fusion welding, solid state welding offers the highest quality. Aeronautics, nuclear, space, and aviation are just a few of the industrial production sectors that utilize the solid-state welding technology. Diffusion welding, explosion welding, friction welding, forge welding, cold welding, role welding, hot pressure welding, and ultrasonic welding are just a few of the SSW techniques covered in the current article. This study looks at a variety of SSW kinds and solid-state welding applications. This study examines many types of SSW and the applications of solid-state welding. Current Study includes the pros and cons of other welding techniques over friction stir welding.

Friction Stir Welding Benefits Technique over Other Welding Techniques of Dissimilar Metals

Abstract: Due to the low heat input situation, solid state welding (SSW) has demonstrated higher potential for integrating a variety of equivalent and dissimilar material combinations. The temperature stays below the melting point of the source materials throughout the solid-state welding process. Compared to fusion welding, solid state welding offers the highest quality. Aeronautics, nuclear, space, and aviation are just a few of the industrial production sectors that utilize the solid-state welding technology. Diffusion welding, explosion welding, friction welding, forge welding, cold welding, role welding, hot pressure welding, and ultrasonic welding are just a few of the SSW techniques covered in the current article. This study looks at a variety of SSW kinds and solid-state welding applications. This study examines many types of SSW and the applications of solid-state welding. Current Study includes the pros and cons of other welding techniques over friction stir welding

Graphic Modeling and Equipment used in the Reconstruction of the Original Damascus Steel

Damascus steel was used in the manufacture of swords and hunting knives before medieval times. The original method of the manufacturing of this type of steel has been lost to time. The research set out to create Damascus steel knives reconstituted according to the recipe from documents written many years ago. The study of Damascus steel provided an opportunity to observe in detail the laborious process of manufacturing this material, which involves free forging and pressure welding of different layers of steel to obtain a particularly strong and durable finished product. To carry out this research, two types of steel were selected to create Damascus steel: AISI 1095 and 15N20 steel. During this study, a functional furnace was built, able to contribute by heating the samples to the hot forging process of these two different materials. By applying a complex process of heating and forging and then repeating this process, the layers of steel were welded together, resulting in an extremely resistant material with a unique aesthetic appearance. Sample processing and the laboratory tests were performed on the obtained Damascus steel to evaluate its mechanical properties, including processing the results using Autodesk Inventor Professional 2023 and simulation in Ansys 2023.

Rotary friction welding applied to Cu11.8Al0.45Be shape memory alloy

The feasibility of welding a CuAlBe SMA by continuous drive friction welding was evaluated. The metallurgical state (annealed/quenched) before welding and frictional pressure (5 and 10 MPa) were varied and their effects on joint quality were analyzed. Static tensile tests, microhardness, thermal analysis by DSC, and optical microscopy were carried out to characterize the welded joint. The results indicated joints of excellent thermomechanical quality. The welding zones are well-defined, narrow, and have a very refined microstructure compared to the base metal. The phase transition temperatures along the welded assemblies were not changed when welding was performed on the quenched samples, except in the welding zone of the sample welded with 10 MPa. Maximum tensile strength was obtained by using maximum friction pressure during welding of the annealed alloy (quenching after welding). To fill the gap in bibliographical research in this field of study, this work innovatively presents the possibility of welding Cu-based SMAs by rotary friction, including the welding of quenched parts without the need for subsequent heat treatments and without compromising the shape memory effect.

Ultrasonic welding of Cork Wood/PLA composites: effect of welding factors on lap shear strength performance

Ultrasonic welding of Cork Wood/PLA composites: effect of welding factors on lap shear strength performance

Artificial Neural Networks and Experimental Analysis of the Resistance Spot Welding Parameters Effect on the Welded Joint Quality of AISI 304.

The automobile industry relies primarily on spot welding operations, particularly resistance spot welding (RSW). The performance and durability of the resistance spot-welded joints are significantly impacted by the welding quality outputs, such as the shear force, nugget diameter, failure mode, and the hardness of the welded joints. In light of this, the present study sought to determine how the aforementioned welding quality outputs of 0.5 and 1 mm thick austenitic stainless steel AISI 304 were affected by RSW parameters, such as welding current, welding time, pressure, holding time, squeezing time, and pulse welding. In order to guarantee precise evaluation and experimental analysis, it is essential that they are supported by a numerical model using an intelligent model. The primary objective of this research is to develop and enhance an intelligent model employing artificial neural network (ANN) models. This model aims to provide deeper knowledge of how the RSW parameters affect the quality of optimum joint behavior. The proposed neural network (NN) models were executed using different ANN structures with various training and transfer functions based on the feedforward backpropagation approach to find the optimal model. The performance of the ANN models was evaluated in accordance with validation metrics, like the mean squared error (MSE) and correlation coefficient (R2). Assessing the experimental findings revealed the maximum shear force and nugget diameter emerged to be 8.6 kN and 5.4 mm for the case of 1-1 mm, 3.298 kN and 4.1 mm for the case of 0.5-0.5 mm, and 4.031 kN and 4.9 mm for the case of 0.5-1 mm. Based on the results of the Pareto charts generated by the Minitab program, the most important parameter for the 1-1 mm case was the welding current; for the 0.5-0.5 mm case, it was pulse welding; and for the 0.5-1 mm case, it was holding time. When looking at the hardness results, it is clear that the nugget zone is much higher than the heat-affected zone (HZ) and base metal (BM) in all three cases. The ANN models showed that the one-output shear force model gave the best prediction, relating to the highest R and the lowest MSE compared to the one-output nugget diameter model and two-output structure. However, the Levenberg-Marquardt backpropagation (Trainlm) training function with the log sigmoid transfer function recorded the best prediction results of both ANN structures.

Fuzzy logic-driven genetic algorithm strategies for ultrasonic welding of heterogeneous metal sheets

There are a lot of problems with the conventional fusion welding process, so ultrasonic welding has been used for about 20 years and has helped a lot of manufacturing industries, including aviation, medicine, and microelectronics. Ultrasonic welding takes less than one second, making it suitable for mass production. Poor weld quality and joint strength are common issues that industries encounter as a result of this process. Actually, the success and quality of the welding are determined by its control parameters. This research examines the impacts of weld time, vibrational amplitude, and weld pressure on the welding of 0.6 mm thick sheets of two different metals, specifically copper and aluminum (AA2024). Responses, including tensile shear stress, weld area, and T-peel stress, are acquired through experiments that follow a full factorial design including four replicas. The highest recorded tensile shear stress was 4.34 MPa, the maximum weld area measured was 63.6 mm2, and the peak T-peel stress reached 1.22 MPa. A second-order non-linear regression model was constructed using all of these data points, which related the responses to the predictors. Due to the importance of quality in the production sector, the process parameters were determined by the combination of genetic algorithm (GA) and fuzzy logic (FL) approaches. The impact of the weld zone temperature on various quality characteristics has been investigated through experiments. It has been noted from the confirmatory test that FL produces superior output outcomes compared to the genetic algorithm, with FL achieving a fuzzy multi-performance index of 0.94 compared to 0.61 for GA. By conducting microstructural analysis, weld quality levels, including “under-weld,” “good weld,” and “over-weld,” were established.

Optimization of Composition, Cold Rolling Scheme, and Structure of Brass Strip Billets for Continuous High-Frequency Pressure Welding

Optimization of Composition, Cold Rolling Scheme, and Structure of Brass Strip Billets for Continuous High-Frequency Pressure Welding

Manufacturing of thermoplastic composite sandwich panels using induction welding under vacuum

A new method to manufacture thermoplastic composite sandwich panels is presented, making use of the induction welding process in which a magnetic susceptor generates the heat at the core/facesheet interface. This technique proposes a fast way to assemble thermoplastic sandwich structures without risking the deconsolidation of the composites skin. The welding pressure is obtained by applying vacuum over the sandwich panel. This vacuum induction welding method (Vac-IW) allows joining thermoplastic composite facesheets to a thermoplastic polymer core in a clean and non-contact manner. The feasibility of the method is demonstrated by preparing sandwich samples made of glass fibre reinforced polyetheretherketone (PEEK) skins and a 3D-printed polyetherimide (PEI) honeycomb core. A susceptor made of PEI and µm-sized nickel (Ni) particles is used to generate heat by magnetic hysteresis losses. The strength of the sandwich samples assembled by the Vac-IW method is evaluated by flatwise tensile (FWT) tests.