Search Results (1,120)

Traditional methods of construction for reinforced concrete columns utilize longitudinal steel bars and transverse ties. Field experience has shown that such a transverse reinforcement method is labor-intensive, time-consuming, and prone to inconsistencies in quality. Welded wire reinforcement (WWR) offers a prefabricated alternative, forming a closed cage that simplifies installation and speeds up the fabrication process. This study investigates the potential of using WWR as a replacement for conventional ties in reinforced concrete columns in pure compression. To achieve this objective, eight one-third-scale columns (1000 mm height, 200 × 200 mm cross-section) were tested under concentric axial loading inside a Universal Testing Machine. Four of the specimens contained WWR, while the other four had conventional ties. The variables that were considered in this study include the concrete compressive strength (34.3 and 43.5 MPa) and the grid size of the WWR (25 and 50 mm). This study investigated the influence of the type of transverse reinforcement on the strength, modulus of elasticity, and ductility of the confined concrete within the core. The findings of the study showed that lateral reinforcement in the form of WWR can increase the concrete core strength by 2.7% relative to corresponding columns employing ties when f′_c = 34.3 MPa was used. Conversely, the utilization of ties proved to be more effective than WWR in improving concrete core strength by an average of 28.8% when f′_c = 43.5 MPa was used. Additionally, WWR reinforced columns demonstrated a marginal 2.0% rise in the modulus of elasticity and a remarkable 21.0% increase in the ductility of the confined concrete core compared with corresponding tied columns. Theoretical predictions of the axial compressive capacity of WWR reinforced columns subjected to concentric loading based on the ACI-318 code provisions underestimated the experimental results by 20%. These findings demonstrate that WWR can serve as an effective substitute for conventional ties, particularly in cases where rapid installation and reduced labor costs are prioritized. Full article

Due to the construction damage of high-density polyethylene film (HDPE) during the early stages of landfill construction and missed or faulty welding, this paper proposes a method based on the synchronous characteristic temperature differences between defective and intact areas of HDPE film. An image feature-edge-picking algorithm was used to detect various defects. First, under the action of a continuous heat source, infrared images of different types of defects on the surface of HDPE films were collected, and we recorded the temperature of different areas on the film surface. We also analyzed the changes in the temperatures of the complete and defect areas over time and extracted the temperature characteristic curves. Second, the contour characteristics of hidden defects in the weld area were analyzed. The image with the most substantial temperature difference resolution was selected and preliminary noise reduction was performed. Further enhancement of the edges was carried out using the guided image-filtering (GIF) algorithm, which was improved by using the edge-aware weighting in weighted guided image filtering (WGIF) and the weighted aggregation mechanism in weighted aggregated guided image filtering (WAGIF). Finally, the Canny operator was used to detect the edges of the processed images to recognize the contour of the welding defect. The best pixel image was extracted, the pixel comparison relationship was used to quantitatively detect the defect size of the HDPE film and the error between the image defect size and the actual size was analyzed. The experimental results show that the model could identify the surface defects on HDPE film during construction and could obtain the approximate outline and size of the hidden defects in the welding area. Full article

A weld pool morphology acquisition and visualization system was designed in the current study, which can present real-time three-dimensional (3D) weld pool morphologies to welders. The underneath of the weld pool is calculated by utilizing an in situ calibrated analytical solution based on real-time collected welding voltage, current, and the surface boundary of the weld pool. In the meantime, the heat source distribution coefficients of the analytical solution were also calibrated through a scaling calibration method. Thus, the system updates a 3D weld pool instantaneously in weld diameter, and the error is 0.8% at the minimum, and the average value is 8.54%. Furthermore, a virtual environment was constructed by using virtual reality (VR) devices, and the visualization of the 3D weld pool model was realized by employing the hot-update technology. The experimental results demonstrate that this system is basically feasible except the update rates still need to be optimized. The current study facilitates the easier observation of weld pool morphology and is highly significant for enhancing the teleoperation skills of welders, especially in achieving precise teleoperation welding. Full article

In order to establish the influence of prolonged exposure to high temperatures on 14MoV6-3 steel, three different weld joints were designed. New-to-new material, new-to-used material, and used-to-used material joints were welded using two welding technologies—GTAW and a combination of GTAW + MMA. The weldments were tested by means of microstructure and tensile testing. The results showed that in all weldments, a fracture occurred in the base metal. Also, in the case of the new-to-used welded sample, the fracture always occurred in the used base metal. Since both materials have the same chemical composition, the difference in microstructure was related to long exposure to high temperatures. New steel has a considerably smaller grain size, while the used material underwent grain growth coupled with carbide coarsening, which decreased its strength. The yield strength (YS) of the new material was higher than the YS of the used material, which exhibited similar values in the used base metal and both weldments. It can be assumed that, since deformation starts in the area with the lowest yield point, the used material is the critical place in a given weldment. Therefore, the accurate extent of strength decrease cannot be evaluated based on the testing of new material, i.e., there is a need to reconsider the traditional qualifications of welding technology. Full article

Ultrasonic tests are widely used, both in laboratory and industrial settings, to assess the quality of joints, mainly welded joints. Studies are being carried out on the possibility of ultrasonic evaluation of adhesive joints. This study was conducted using signal analysis in the time and frequency domains. The ultrasonic probes used in the tests were selected on the basis of the properties of the test elements. For example, when testing welded joints, ultrasonic probes with a water delay line bounded by a thin diaphragm were used. Since adhesives have different acoustic properties, it is necessary to evaluate the capabilities of different ultrasonic probes to test adhesive joints. Tests were conducted for two different adhesives (cyanoacrylate and structural) and eight ultrasonic probes with a frequency range of 1.660 to 13.70 MHz. In the literature, no studies have analyzed the use of ultrasonic probes at such different frequencies. Frequency has the greatest effect on the attenuation of ultrasonic waves and the ultrasonic wavelength, and it was noted that the adhesive could cause a 25 percent change in the maximum frequency of the ultrasonic pulse. It was also found that it is necessary to make reference samples before ultrasonic testing of adhesive joints, since specific frequencies can produce erroneous signals for the selected adhesives. Full article

The principles of the friction welding (FW) process of the two different non-ferrous metals, aluminum and copper, are presented in this paper. Considering that the bimetallic Al-Cu joints find applications in electrical engineering, as well as in other industrial fields, the basic characteristics and compatibility of these metals are discussed, along with the influence of various parameters on the properties of their friction welded joints. The experimental study involved rotation friction welding (RFW), which was used to weld aluminum and copper samples. The samples were monitored for shortening due to the applied deformation, as well as the size of the formed mushroom. Then, the central part of the welded joint was cut from the welded samples to determine the hardness and microstructure of the joint. At the end of the research, the possibility of applying software for the design of a numerical model for analysis of the possibility of joining aluminum and copper, with the same input parameters as those used in the experiment, was considered. The numerical simulation exhibited a high agreement with the experimental results. Full article

Many pipelines are buried and operated underground in nuclear and chemical plants. Since these pipelines are welded on-site and subsequently coated, ensuring the integrity of these coatings is crucial. Over time, rubber coatings can disbond due to factors such as soil pressure, creating gaps that lead to defects and may expose weld joints to electrolytes locally. Thus, effective detection of coating defects in buried pipelines is crucial for maintaining pipelines’ structural integrity and preventing corrosion. This study examines the shielding effect of rubber disbond on DCVG signal magnitude using the Direct Current Voltage Gradient (DCVG) technique. Simulations conducted with COMSOL Multiphysics^®, considering variables such as soil resistivity (1–19 kΩ·cm), defect exposure size (100 cm² and 1 cm²), detection electrode distance, and applied voltage, show that the DCVG signal generally increases as soil resistivity decreases and as defect size and electrode spacing increase. This is due to a stronger current distribution resulting from the higher applied voltages. However, shielded defects consistently produce lower DCVG signals than unshielded ones, a phenomenon that stems from the insulating shielding layer around the defect, which restricts the flow of the inspection current. These findings highlight how the shielding layer significantly influences the distribution of the inspection current. Full article

In this study, Artificial Neural Networks (ANN) were employed to develop a Digital Twin (DT) of the Rotary Friction Welding (RFW) process. The neural network models were trained to predict the peak temperature generated during the welding process of dissimilar Ti Grade 2/AA 5005 joints over a temperature range of 20–640 °C. This prediction was based on a parametric numerical model of the RFW process constructed using the Finite Element Method (FEM) within the ADINA System software. Numerical simulations enabled a detailed analysis of the temperature distribution within the weldment. Accurate temperature predictions are essential for assessing the mechanical properties and microstructural integrity of the welded materials. Artificial Intelligence (AI) models, trained on historical data and real-time inputs, dynamically adjust critical process parameters—such as rotational speed, axial force, and friction time—to maintain optimal weld quality. A key advantage of employing AI-augmented DT systems in the RFW process is the ability to conduct real-time (less than 0.1 s) optimization and adaptive control. By integrating a Genetic Algorithm (GA) with the DT algorithm of the RFW process, the authors developed an effective tool for analyzing parameters such as axial force and rotational speed, in order to determine the optimal welding conditions, which translates into improved joint quality, minimized defects, and maximized process efficiency. Full article

Resistance spot welding (RSW) faces critical monitoring challenges in industrial applications due to nonlinear coupling characteristics and production line disturbances. This study developed a Zigbee-enabled real-time monitoring system to address the precision limitations of conventional methods in tracking RSW parameters. Using DP780/DP590 dual-phase steel specimens with thickness variations, we implemented a dedicated data acquisition system capturing welding current, voltage, and barometric pressure dynamics. The experimental results demonstrated measurement accuracies within ±0.49% for current, ±0.25% for voltage, and 3.72% average relative error for barometric pressure with stable operational deviations (0.017–0.024 MPa). Full article

Welding defects threaten structural integrity, demanding efficient and accurate detection methods. Traditional radiographic testing defects interpretation is subjective, necessitating automated solutions to improve accuracy and efficiency. This study integrates wavelet transform convolutions (WTConv) into YOLOv11n, creating WT-YOLO, to enhance defect detection in X-ray films. Wavelet transforms enable multi-resolution analysis, extracting both high-frequency and low-frequency features critical for detecting various welding defects. WT-YOLO replaces standard convolutional layers with WTConv, improving multi-scale feature extraction and noise suppression. Trained on 7000 radiographic images, WT-YOLO achieved a 0.0212 increase in mAP75 and a 0.0479 improvement in precision compared to YOLOv11n. On a test set of 200 images per defect category across seven defect types, WT-YOLO showed precision improvements of 0.0515 for cracks, 0.0784 for lack of fusion, 0.0067 for incomplete penetration, 0.1180 for concavity, 0.0516 for undercut, and 0.0204 for porosity, while experiencing a slight 0.0028 decline for slag inclusion. Compared to manual inspection, WT-YOLO achieved higher precision for cracks (0.0037), undercut (0.1747), slag inclusion (0.1129), and porosity (0.1074), with an inference speed 300 times faster than manual inspection. WT-YOLO enhances weld defect detection capabilities, providing the possibility for a robust solution for industrial applications. Full article

The paper presents the results of oxidation tests on the alloy based on the intermetallic phase, Fe40Al5Cr0.2TiB, in the air at 700–1000 °C temperature. The kinetics of corrosion processes were determined, the surface condition after oxidation was assessed, and the type and morphology of the oxides formed were determined. In addition, the paper presents the possibility of applying the technology of surfacing Fe40Al5Cr0.2TiB alloy on the surface of steel grade S235JR as a protective coating that is resistant to high temperatures. The process was carried out using the TIG method by direct current (DC). After the surfacing, the structure of the surfacing weld made of the tested material on the base of structural steel grade S235JR was determined. It was found that a protective Al₂O₃ oxide layer is formed on the surface of the oxidized alloy based on the intermetallic phase from the FeAl system, and the oxidation kinetics have a parabolic course. Moreover, it was found that the morphology of the oxides formed on the surface varies depending on the oxidation temperature, which clearly indicates a different mechanism of oxide layer formation. The formation of a stable α-Al₂O₃ oxide variety on the surface of the Fe40Al5Cr0.2TiB alloy protects the material from further corrosion, which favors the application of this alloy on structures and fittings operating at elevated temperatures. The aim of the research was to use the Fe40Al5Cr0.2TiB alloy with very good oxidation resistance as a layer overlay on ordinary quality S235JR steel. In this way, conditions were created that fundamentally changed the surface condition (structure and physicochemical properties) of the system: steel as a substrate—intermetallic phase Fe40Al5Cr0.2TiB as a surfacing layer, in order to increase resistance to high-temperature corrosion and erosion (in the environment of gases and solid impurities in gases) often occurring in corrosive environments, especially in the power industry (boilers, pipes, installation elbows) and the chemical industry (fittings). At the same time, the surfacing method used is one of the cheapest methods of changing the surface properties of the material and regenerating or repairing the native material with a material with better properties, especially for applications in high-temperature corrosion conditions. Full article

The Invar steel molten pool is characterized by low fluidity of the molten pool due to high tension, which hinders the escape of gases and exacerbates the formation of porosity defects. In this study, the influences of different welding process parameters, material properties, and U-groove on the flow behavior of the molten pool of laser–tungsten inert gas (TIG) hybrid welding of Invar steel are investigated by numerical simulation and high-speed photography. This research proposes effective measures to suppress porosity defects, such as optimizing process parameters and extending the existence time of the molten pool. In conclusion, this study systematically investigates the dynamic mechanism of the formation of welding defects in 4J36 Invar steel and provides important theoretical support for the optimization of the welding process of 4J36 Invar steel. The results indicate that controlling the laser power at 4–6 kW, welding speed at 0.5–1.0 m/min, and welding current at 150–170 A can stabilize the molten pool flow and keyhole and promote the molten pool flow and gas escape. Full article

Accurate prediction of weld bead geometry is critical for optimizing laser overlap welding of low-carbon galvanized steel, as it directly affects joint quality and mechanical performance. Traditional finite element method (FEM)-based models provide reliable predictions but are computationally expensive and impractical for real-time applications. This study presents an artificial neural network (ANN)-based predictive model trained on a combination of experimental data and validated FEM simulations to estimate key weld characteristics, including depth of penetration (DOP), weld bead width at the surface (WS), and weld bead width at the interface (WI). The ANN model was evaluated using various improved statistical metrics. Results demonstrated a strong correlation between ANN predictions and experimental measurements, with R² values exceeding 95% for WS and DOP and 92% for WI, and mean errors below 7%. A comparative analysis between ANN, FEM, and experimental data confirmed the model’s reliability across different welding conditions. Additionally, ANN significantly reduced computational time compared to FEM while maintaining high accuracy, making it a practical tool for real-time process optimization. These findings highlight the potential of ANN models as efficient alternatives to conventional simulation techniques in laser overlap welding applications. Future improvements may involve integrating real-time sensor data and deep learning techniques to further enhance predictive performance. Full article

In pipeline all-position welding processes, laser scanning provides critical geometric data of width-changing bevel morphology for welding torch swing control, yet conventional second-order derivative zero methods often yield pseudo-inflection points in practical applications. To address this, a third-order derivative weighted average threshold algorithm was developed, integrating image denoising, enhancement, and segmentation pre-processing with cubic spline fitting for precise bevel contour reconstruction. Bevel pixel points were captured by the laser sensor as inputs through the extracted second-order derivative eigenvalues to derive third-order derivative features, applying weighted threshold discrimination to accurately identify inflection points. Dual-angle sensors were implemented to synchronize laser-detected bevel geometry with real-time torch swing adjustments. Experimental results demonstrate that the system achieves a steady-state error of only 1.645% at the maximum swing width, a dynamic response time below 50 ms, and torch center trajectory tracking errors strictly constrained within ±0.1 mm. Compared to conventional methods, the proposed algorithm improves dynamic performance by 20.6% and exhibits unique adaptability to narrow-gap V-grooves. The results of these studies confirmed the ability of the method to provide real-time, accurate control for variable-width weld tracking, forming a swing-width adaptive control system. Full article

Mobile welding robots have attracted considerable attention due to their flexible movement and robust adaptability, offering substantial market potential. However, the complexity of their operational conditions poses specific demands on robot configurations, with no established design methodology available at the time. To address this challenge, we constructed Lagrange’s equations for wheeled mobile welding robots. Through simplification and deduction analysis, we concluded that larger wheeled mobile welding robots are suited for paths with larger curvature radii, whereas smaller ones are more appropriate for paths with smaller curvature radii. Based on the above analysis and considering the load-bearing capacity of the robot, we proposed a configuration design method for wheeled mobile welding robots, evolving from large to small and micro wheels, including track constraints and wheel number adjustments. Subsequently, prototype robots, including magnetic wheel, tracked, and flexible contour tracing mobile welding robots, have been developed to accommodate various operational conditions. Welding experiments demonstrate that these three configurations, distinguished by their travel path curvature radii, can effectively meet the mobile welding requirements of their respective environments. The effectiveness of the configuration design of wheeled mobile welding robots under different working conditions has been verified. Full article