Abstract This study investigates the development and mechanical characterization of hybrid and non-hybrid composite materials reinforced with carbon fiber, basalt fiber, glass fiber, and 304 stainless steel fabric within an epoxy matrix. The aim is to create composites with enhanced tensile strength, flexural strength, and impact resistance for potential applications in blast-resistant structures. Composite laminates were fabricated using a hand lay-up method, followed by curing under pressure to ensure optimal interfacial bonding. Mechanical testing, including tensile, three-point bending, Charpy impact, and low-velocity drop weight tests, was conducted in accordance with ASTM standards. Scanning electron microscopy (SEM) analysis provided insights into fracture mechanisms and delamination behavior. The results show that hybrid composites exhibit inferior static mechanical properties compared to non-hybrid pure carbon, glass and basalt composites, but certain hybrid configurations show significant improvements energy absorption due to the steel mesh. These findings suggest that the strategic combination of different fibers and metallic fabrics can be tailored to meet specific engineering requirements, offering a pathway for designing advanced materials in the aerospace, automotive, and defense industries.

Abstract This study presents a modified version of the Animated Oat Algorithm (AOA), enhanced through the integration of chaotic maps, termed the Chaotic Animated Oat Algorithm (CAOA). Inspired by the seed dispersal mechanisms of the oat plant, AOA offers a population-based metaheuristic framework suitable for complex global optimization tasks. The proposed CAOA was evaluated across four real-world engineering optimization problems: pressure vessel design, bolted rim coupling, gear train cost minimization, and robot gripper arm weight reduction. Results demonstrate that CAOA consistently outperforms traditional and state-of-the-art metaheuristics in terms of solution quality, convergence stability, and robustness, affirming its potential for widespread engineering applications.

Abstract In this study, dissimilar butt welding of 0.8 mm thick DP600 and 1 mm thick DP1180 advanced high-strength steels was performed using fiber laser beam welding with beam oscillation. The effects of oscillation type (linear and circular), oscillation amplitude (0.5, 1, 1.5 mm), and welding speed (50–80 mm s −1 ) on weld bead geometry, microhardness, and tensile load were investigated. A total of 12 experimental sets were conducted by keeping the laser power and frequency constant at 1.2 kW and 100 Hz, respectively. Metallographic evaluations, Vickers microhardness tests, and tensile tests were carried out in accordance with standard procedures. The results revealed that welding speed had a significant influence on weld penetration and width, with optimal parameters determined as 60 mm s −1 speed and 1 mm amplitude in both oscillation types. Circular oscillation generally led to higher microhardness values, whereas linear oscillation produced wider weld seams. While amplitude increase decreased penetration depth, it improved weld width. The tensile load of all joints was largely influenced by the DP600 base metal, where fractures were consistently observed. However, the joint at 1.5 mm amplitude in circular mode fractured in the weld zone, indicating insufficient penetration. The findings suggest that proper selection of oscillation parameters can enhance weld quality and mechanical performance when joining dissimilar high-strength steels for lightweight automotive applications.

Abstract CW511L lead-free brass is a newly developed alloy that has found widespread application across various industrial sectors. It is particularly preferred as a raw material for watering and pumping components, which typically require machining before use. This study investigates the influence of cutting tool geometry on drilling performance, focusing on critical parameters such as radial rake angles, axial rake angles, tip radius, and helix angle. An L27 Taguchi experimental design was employed using the following levels: radial rake angle (4°, 8°, 12°), axial rake angle (−2°, 0°, 2°), tip radius (10, 20, 30 µm), and helix angle (0°, 5°, 10°). Drilling experiments were performed in accordance with this design to evaluate cutting forces, chip breakability, burr height, and surface quality. The effects of tool geometry were analyzed using three-dimensional surface plots and a correlation matrix to reveal significant relationships between input variables and drilling responses.

Abstract Self-clinching nuts are increasingly used in automotive industry for fastening bolts to metal sheets, which are too thin to be threaded directly. To ensure safe and reliable use, this type of nuts must meet defined mechanical performance criteria, such as push-out and torque-out resistance. Finite element analysis plays a crucial role in observing the deformation of the sheet metal during the clinching process and in assessing whether the nuts meet the expected performance standards. This study focused on the development of finite element models for clinching, push-out, and torque-out tests for self-clinching nuts. The accuracy of the developed models was evaluated by comparing their results with corresponding experimental data. The findings of the study revealed that mesh quality significantly affect the accuracy of the simulation results. Additionally, it was observed that the compliance of the testing machine plays an important role in the discrepancy between experimental and simulation outcomes during the clinching process.

Abstract The application of lattice structures has become increasingly important in designing complex components due to additive manufacturing (AM) advancements. Various types and design parameters of lattice structures allow weight reduction while maintaining the required strength and improving mechanical properties, with the strength varying based on these parameters. One common approach to calculating this strength is by using software solvers like SimSolid, which employs the meshless analysis solution (MAS). Considering the variety of parameters, the complexity of lattice structures, and the computational difficulties in analysis methods, identifying the optimal lattice structure for a design is highly challenging. To overcome this challenge, artificial neural networks (ANNs) are integrated into the optimization algorithm used in this study. The training data for the ANN are obtained from the analysis results of the designs generated using the design parameters selected by the Latin hypercube sampling (LHS) method. The ANNs integrated non-dominated sorting genetic algorithm II (NSGA-II) optimization algorithm is used to minimize the mass while ensuring the strength of the material by keeping the maximum stress within the permissible limits. The method is applied to the weight reduction of the brake pedal, approximately 26.96 % is achieved while maintaining the required strength under existing conditions.

Abstract In this study, rice husk-reinforced HDPE composites were produced to provide sustainable and economical solutions. For this purpose, HDPE composites with RH ratios of 5 %, 10 %, and 15 % by volume were produced using the injection moulding method. Density, hardness, tensile, bending strength, friction coefficient, and wear values of the produced bio-composite materials were measured. According to the results from the mechanical tests, the lowest density, hardness, tensile, and bending strength values were recorded in the 5 vol % RH + HDPE composite material, while the highest values were observed in the 15 vol % RH + HDPE composite material. Minimum tensile and bending strength values were 27.8 and 31.22 MPa, and maximum tensile and bending strength values were 28,5 and 31,35 MPa. As a result of friction and wear tests, the minimum coefficient of friction and weight loss were found in the 15 vol % RH + HDPE composite material, and the highest values were noted in the 5 vol % RH + HDPE composite material. The minimum coefficient of friction was measured as 00,957 µ and the corresponding weight loss was 00,008 g. The maximum coefficient of friction was 06,485 µ, with a weight loss of 00,022 g.

Abstract This study aims to simulate the FSW conditions of fine-grained ultra-high carbon (UHC) steel alloy used as stirrer tool in friction stir welding by external heat treatments. UHC steel is produced using traditional manufacturing methods for experiment. In order to understand the wear behavior of the stirrer tool, to obtain a fine-grained microstructure and to support the formation of softer phases such as spherical cementite, heat treatments of approximately ten thermal cycles were applied to the internal structure. Scanning electron microscopy was used to observe microstructural changes after each cycle and understand the transformation mechanisms. The result showed a gradual decrease in cementite particle size with increasing thermal cycles. Over time, cementite transformed into spherical shapes, reaching an average particle size of approximately 5 µm. Wear testing revealed that the wear rate is affected by the number of thermal cycles, and the hardness continuously decreases as the number of cycles increases.