Band 67, Heft 9

In this study, it was tried to determine whether it is possible to produce the slide parts of light firearm from polyamide or glass fiber reinforced polyamide composite material by examining the stresses formed in the body after firing with the finite element method. The slide part of the 25 ACP model pistol with a caliber of 6.35 mm was used for solid modeling, and then the stress and deformation conditions were examined with finite element analysis. In the analysis to be made for the experiments, the firing was carried out using a pistol bullet with a diameter of 6.35 mm. The 6.35 mm caliber is particularly appealing for daily carry or easy storage due to its compact and lightweight design. As a result of the analysis, it was determined that the slide section modeled with both materials experienced plastic deformation. In terms of stress values, it was observed that the stress value of PA66 GF30 during firing was significantly higher compared to PA66. On the other hand, it was determined that the stress in the slide section of the PA66 GF30 composite material during firing was close to the stress of PA66.

Hydraulic breaker is a frequently used piece of equipment in construction and industrial fields. With the advancement of modern industrial technology, users have come to demand higher standards. Therefore, construction equipment has to offer high structural stability, performance, and efficiency. In this study, the effects of austenitizing and tempering processes on the mechanical strength of AISI 4140–4340 steels for rock breaking applications were investigated. Microstructural alterations were examined using optical microscope (OM) and a scanning electron microscope (SEM). The mechanical characteristics of the steels were assessed through tensile, hardness, and impact tests. At 250 °C, isothermal retention formed bainite and tempered martensite. At 300 and 350 °C, isothermal retention produced bainite and untempered martensite. Austempering produced lower hardness but higher impact toughness than quenching and tempering.

Friction welding (FW) is an extremely economical and efficient method for jointing similar or dissimilar metals. This technique is frequently preferred in the automotive and aviation sectors. It offers an effective solution to overcome the difficulties encountered in jointing materials with different physical properties. In this study, AISI 430/HARDOX 450 steels were joined by friction welding using different speeds. The structural changes in the welded joints were assessed by scanning electron microscope (SEM), energy dispersive spectrometry (EDS), elemental mapping, and X-ray diffraction (XRD) analysis. In addition, tensile test, notch impact test, and microhardness test were applied to the samples. Fracture surface examinations after the notch impact test were performed by SEM. Macroscopically, the samples were uniformly combined in all cycle variables. At higher rotational speeds, the deformation between the two metals increased, producing stronger joints.

NiTi coatings were fabricated on AISI 430 by using the plasma transfer arc coating. The phase content and microstructure of the NiTi alloyed samples were analyzed by scanning electron microscope (SEM), optical microscope (OM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), elemental mapping, and electron backscatter diffraction (EBSD) techniques. The mechanical properties were detected by hardness and dry sliding adhesive wear tests. The wear characteristics of the coatings were observed using SEM. Higher heat input and current density promoted the diffusion of alloying elements from the base material into the cladding layer. The Ni and Ti elements were uniformly spread across the coating layers. The hardness of the layer containing the NiTi phase was higher than that of the substrate layer. As the current intensity increased, the removal of the coating during the wear raised due to the increase of brittle intermetallic rates.

In engineering and other fields, metaheuristic algorithms are increasingly used to solve challenging optimization problems. High-dimensional and multimodal issues are complex for traditional optimization techniques, which has led to the development of hybrid metaheuristics that are improved by artificial neural networks (ANNs). To improve search efficiency and solution accuracy, this work presents an ANN-assisted Catch Fish Optimization Algorithm (MCFOA), which draws inspiration from conventional fishing methods. Numerous engineering applications, such as the optimal design of the side profile of an electric vehicle battery box, shell and tube heat exchanger, industrial gear optimization, and welded beam cost minimization, show off the efficacy of MCFOA. For the novel battery case problems, the modified optimizer realized a 20 % improvement in the design compared to the initial design, as well as a 4.5 % improvement compared to the Starfish optimizer. Moreover, for the engineering design problems, the modified optimizer realized 4–10 % better results in terms of the best values of the fitness function. This shows the applicability and implementation of the proposed optimizer for the optimization of real-world engineering problems.

Abstracts In order to reduce the cost and increase the efficiency of ceramic membrane supports, a novel porous black alumina membrane support was prepared using alumina and manganese dioxide as raw materials. The effects of manganese dioxide content and sintering temperature on the flexural strength, porosity, and water flux of the membrane supports were investigated. Meanwhile, the membrane support was characterized by SEM, XRD, and TG-DSC. The results show that the favorable performance of the obtained membrane support is achieved at a manganese dioxide content of 50 wt.% and a sintering temperature of 1,150 °C, due to the formation of manganese–aluminum spinel. The water flux of the membrane support is as high as 8,852.25 L m −2  h −1 ·bar −1 , the flexural strength reaches 38.72 MPa, and it also has desirable acid and alkali corrosion resistance. The present experimental results provide an important experimental basis for obtaining high-performance ceramic membranes.

Nowadays usage of vehicles tremendously increased throughout the world. The crashworthiness of vehicle structures plays a crucial role in ensuring passenger safety during collisions; in order to improve the energy absorption behaviors, this research aims to introduce the new arrangements of truncated single, double and tri tubes. Both experimental and numerical axial compression loading is done on 6 different orientations in normal and reversed taper tubes and made to analyze various crashworthiness indicators such as peak crushing force (F peak ), mean crushing force (F mean ), total energy absorption (TEA), specific energy absorption (SEA) and crush force efficiency (CFE). The deviations between experimental and numerical results are very close to each other. Further, a multi-objective optimization of factors affecting crashworthiness indicators was given utilizing the Taguchi technique and Grey relational analysis (GRA). The findings indicate that, in comparison to an inline order configuration, the TEA increases when the tubes are arranged in triangle order with SEA and CFE also increase in reasonable manner. It is observed that the reversed taper orientation withstands for the maximum crash loads in all the orientations.

As high entropy alloys (HEAs) continue to be increasingly studied for next-generation structural materials, gaining a comprehensive understanding of their mechanical properties, including their creep behaviors, remains essential. In this work, rare earth element yttrium (Y) added CoCrFeNi HEAs are produced by mechanical alloying, followed by consolidation via spark plasma sintering (SPS) with ultrafine grain sizes. The microstructures after SPS consolidation are examined using X-ray diffraction (XRD) and transmission electron microscopy (TEM). The creep properties, including creep displacement, creep strain rate, creep stress, and stress exponent, are evaluated using a nanoindentation test with a Berkovich tip indenter. The results reveal that the average grain size of CoCrFeNi HEA is determined to be 385 ± 65 nm after SPS consolidation, which reduces to 190 ± 30 nm and 155 ± 55 nm with 1 and 4 at.% Y additions, respectively. Accordingly, HEA with the addition of 4 at.% Y exhibits increased hardness, attributed to the presence of additional Y-based oxides and the reduced grain size in its microstructure. Furthermore, the creep mechanisms for the investigated CoCrFeNi HEAs are primarily dominated by dislocation–precipitation interaction based on the calculated stress exponent values.

Bird strikes in aviation affect flight safety and can lead to financial losses or even fatalities. In this study, a machine learning based optimization approach is used to carry out design optimization of a canopy transparency plate for a fighter aircraft against bird strike. The canopy plate is designed to have a multi-layered structure such that polycarbonate (PC) and stretched polymethyl methacrylate (SPMMA) materials are laminated with a thermoplastic polyurethane (TPU) adhesive. To model PC and SPMMA materials, the Johnson–Cook material model is used. A finite element model is generated for the canopy plate subject to bird strike test conditions, and the lightest structure that provides good collusion performance is investigated. For this purpose, a training data set is created with the Latin hypercube sampling method and a support vector machine (SVM) model that could predict the collision outcome is created. Using the constructed SVM model, optimization is made using genetic algorithm and the optimum transparency design is determined. Finally, the optimum design is subjected to bird strike tests for validation. It is found that the optimum transparency design successfully satisfies the test requirements.

Optimization techniques are crucial in industrial engineering, particularly in addressing complex design and operational challenges. Traditional optimization methods often struggle with high computational costs, poor convergence rates, and multimodal fitness functions. To overcome these limitations, nature-inspired metaheuristic algorithms have gained popularity. This study introduces a modified artificial neural network–assisted superb fairy-wren optimization algorithm (MSFWOA) to enhance the search and exploitation capabilities of the standard superb fairy-wren optimizer. The algorithm integrates artificial neural networks (ANNs) to improve solution accuracy and convergence efficiency. The effectiveness of MSFWOA is demonstrated through its application to industrial optimization problems, including heat exchanger cost minimization, reinforced concrete beam structural optimization, piston lever volumetric optimization, pressure vessel design, and aircraft wing rib component structural optimization. Comparative analysis with existing metaheuristic algorithms highlights the superior performance of MSFWOA in achieving optimal solutions with reduced computational cost and higher precision.

This study presents an artificial neural network (ANN)-assisted modified supercell thunderstorm optimizer (MSTO) for solving complex industrial component optimization problems. Inspired by the natural phenomena of spiral motion, tornado formation, and jet streams within supercell thunderstorms, the STO algorithm is enhanced with ANN integration to improve exploration, exploitation, and convergence rates. The algorithm is validated across five constrained engineering problems: cantilever beam optimization, industrial grinding cost optimization, tubular column design, diaphragm spring weight minimization, and fin and tube heat exchanger (FTHE) cost optimization. These results confirm MSTO’s superior performance over recent metaheuristics, highlighting its potential for high-precision, stable, and efficient solutions across structural, thermal, and mechanical design domains.

Metaheuristic algorithms are optimization techniques inspired by natural processes, widely used to solve complex real-world problems. Traditional methods like swarm-based established optimizers often face challenges like premature convergence and high computational costs. The aim of this research is to develop a new optimization method for optimizing electric vehicle components and real-world problems. This research introduces a new chaotic fishing cat optimization algorithm (CFCO), a new optimization algorithm based on recent fishing cat optimization algorithm and chaotic maps. The chaotic maps are integrated into FCO to improve the balance between exploration and exploitation. This research is the first application of the CFCO to the optimum design of electric vehicle components in the literature. The algorithm is applied to various industrial design optimization problems, including structural optimization of cantilever beams, weight optimization of a coupling with a bolted rim, optimization of side profile of an electric vehicle battery enclosure, and heat exchanger economic optimization. The results demonstrate that the developed CFCO outperforms existing recent metaheuristic techniques, achieving superior efficiency and accuracy in industrial applications.

In this paper, experimental and finite element (FE) analyses of the lattice structures resembling an overexpanded honeycomb core material were performed for different parameters for unit cells of the structures. The lattice structures produced using an additive manufacturing (AM) method. Polylactic acid (PLA) was used to manufacture the test specimens by Fused Deposition Modeling (FDM) method. Seven different test specimens were designed changing three parameters of unit cell with the same size of test specimens. All the test specimens were subjected to compressive load and parameter changes’ effect on mechanical properties, which are yield strength and Young’s modulus. For the validation of the tests, finite element analysis was performed. According to the results, experiments and the FE models gave similar outputs. First, decreasing the cell size, increasing the thickness of the cell edges, and increasing the unit cell angle enhance the strength and Young’s modulus of the lattice structures. Moreover, the structures with 0° and 90° angles of the unit cells show auxetic features, whereas the structures with 45° angles of the unit cells show nonauxetic features.

This study aims the use of blast furnace slag, produced as waste during the production of raw iron in blast furnaces, as a reinforcing element in the production of metal matrix composites. The Al6061 alloy, widely used in the automotive industry, was chosen as the matrix. SiC and Al 2 O 3 , two commercial ceramics frequently used in MMC production, were used as the second and third reinforcing elements in hybrid composite production, and their compatibility with blast furnace slag was investigated. Composites were produced using the stir-casting method with reinforcements sized between 22 and 59 µm. Microstructure examinations revealed the presence of blast furnace slag within the internal structure, a homogeneous distribution of reinforcing elements, and the absence of agglomeration. Brinell hardness measurements determined that a 5 wt.% addition of blast furnace slag increased the hardness of the Al6061 alloy by 29.31 %. The greatest increase in hardness, 108.62 %, was observed in the hybrid composite containing 3 wt.% Al 2 O 3 , 3 wt.% SiC, and 5 wt.% BFS reinforcements. Fatigue life tests indicated that fatigue life improved with increasing reinforcement. The most significant enhancement in fatigue life, 625.28 %, was observed in the composite reinforced with 3 wt.% BFS, 5 wt.% Al 2 O 3 , and 5 wt.% SiC compared to the unreinforced alloy.

Natural fiber–reinforced composites offer sustainability benefits but face challenges such as high water absorption and limited wear resistance. To address this, pectin was incorporated into aloe vera fiber–reinforced polyester composites, and its effects on mechanical strength, wear resistance, water absorption, and thermal stability were evaluated. Composites were prepared with varying pectin concentrations: AF0 (pectin-free), PA1 (1 % pectin), PA3 (3 % pectin), PA5 (5 % pectin), and PA7 (7 % pectin). Results showed that PA3 exhibited the highest mechanical properties, with a hardness of 81, impact strength of 3.87 J, flexural strength of 60.31 MPa, and tensile strength of 21.87 MPa, while water absorption decreased to 8.12 %. Wear resistance was also highest in PA3, with the lowest wear loss under applied loads of 10  N , 15  N , and 20  N . However, beyond PA3, mechanical properties and wear resistance declined due to matrix embrittlement. Thermal analysis indicated similar degradation trends across compositions, with about 20 % weight loss between 50 °C and 250 °C and 60 % loss between 250 °C and 400 °C, confirming that pectin had minimal impact on thermal stability. These findings suggest that incorporating 3 % pectin (PA3) optimizes composite performance, making it a promising approach for enhancing the durability of natural fiber–reinforced composites.