Optimum design of a seat bracket using artificial neural networks and dandelion optimization algorithm

Materials Testing, Journal Year: 2023, Volume and Issue: 65(12), P. 1767 - 1775

Published: Oct. 13, 2023

Abstract Nature-inspired metaheuristic algorithms are gaining popularity with their easy applicability and ability to avoid local optimum points, they spreading wide application areas. Meta-heuristic optimization used achieve an design in engineering problems aiming obtain lightweight designs. In this article, structural methods the process of achieving a seat bracket. As result topology optimization, new concept bracket was created shape optimization. mass stress values obtained depending on variables, constraint, objective functions were by using artificial neural networks. The problem based minimization is solved applying dandelion algorithm verified finite element analysis.

Language: Английский

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Enhancing the structural performance of engineering components using the geometric mean optimizer

Materials Testing, Journal Year: 2024, Volume and Issue: 66(7), P. 1063 - 1073

Published: April 30, 2024

Abstract In this article, a newly developed optimization approach based on mathematics technique named the geometric mean algorithm is employed to address challenge of robot gripper, airplane bracket, and suspension arm automobiles, followed by an additional three engineering problems. Accordingly, other challenges are ten-bar truss, three-bar tubular column, spring systems. As result, demonstrates promising statistical outcomes when compared well-established algorithms. Additionally, it requires less iteration achieve global optimum solution. Furthermore, exhibits minimal deviations in results, even techniques produce better or similar outcomes. This suggests that proposed paper can be effectively utilized for wide range critical industrial real-world challenges.

Language: Английский

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Crash performance of a novel bio-inspired energy absorber produced by additive manufacturing using PLA and ABS materials

Materials Testing, Journal Year: 2024, Volume and Issue: 66(5), P. 696 - 704

Published: Feb. 19, 2024

Abstract Thin-walled structures are one of the important safety components used in vehicles. They placed front parts vehicles to minimize impacts that occur event a collision, and they absorb impact force by changing shape collision. Crash boxes have high-impact absorption, low weight, low-cost expectations. In design crash boxes, thin-walled preferred due their high deformation capability. this study, additive manufacturing method was produce structures. were produced methods using PLA ABS materials. The manufactured tested an test. experimental results, energy absorption ability from materials examined, fragility observed. results verified finite element analysis made

Language: Английский

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Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm

Materials Testing, Journal Year: 2024, Volume and Issue: 66(8), P. 1230 - 1240

Published: July 5, 2024

Abstract This paper introduces a novel approach, the Modified Electric Eel Foraging Optimization (EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic algorithms for solving multidisciplinary design problems efficiently. Inspired by foraging behavior of electric eels, algorithm incorporates four key phases: interactions, resting, hunting, and migrating. Mathematical formulations each phase are provided, enabling to explore exploit solution spaces effectively. The algorithm’s performance is evaluated on various real-world optimization problems, including weight engineering components, economic pressure handling vessels, cost welded beams. Comparative analyses demonstrate superiority MEELFO in achieving optimal solutions minimal deviations computational effort compared existing methods.

Language: Английский

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Parameters identification of magnetorheological damper based on particle swarm optimization algorithm

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 143, P. 110016 - 110016

Published: Jan. 13, 2025

Language: Английский

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Experimental Investigation on Mechanical properties of CF15PET and GF30PP materials produced with different raster angles

Materials Testing, Journal Year: 2024, Volume and Issue: 66(6), P. 847 - 855

Published: March 22, 2024

Abstract In recent years, additive manufacturing (AM) technologies have been used in many industries, such as automotive, defense, space, and aviation. Depending on the development of this technology, effect relationship between parameters, raster angles, production speed, melting temperature during materials, has an important issue mechanical properties materials. study, effects ±45° 0–90° angles 15 % short carbon fiber reinforced polyethylenetereflatate (CF15PET) 30 glass polypropylene (GF30PP) materials were investigated. As a result it was determined that different affect both

Language: Английский

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A new modified version of mountain gazelle optimization for parameter extraction of photovoltaic models

Electrical Engineering, Journal Year: 2024, Volume and Issue: 106(5), P. 6565 - 6585

Published: April 20, 2024

Language: Английский

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Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components

Materials Testing, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 30, 2024

Abstract This paper introduces and investigates an enhanced Partial Reinforcement Optimization Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory to efficiently solve complex engineering optimization problems. The proposed combines the (PROA) with quasi-oppositional learning approach improve performance of pure PROA. E-PROA was applied five distinct design components: speed reducer design, step-cone pulley weight optimization, economic cantilever beams, coupling bolted rim vehicle suspension arm An artificial neural network as metamodeling is used obtain equations for shape optimization. Comparative analyses other benchmark algorithms, such ship rescue algorithm, mountain gazelle optimizer, cheetah demonstrated superior in terms convergence rate, solution quality, computational efficiency. results indicate that holds excellent promise technique addressing

Language: Английский

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Experimental and numerical investigation of crash performances of additively manufactured novel multi-cell crash box made with CF15PET, PLA, and ABS

Materials Testing, Journal Year: 2024, Volume and Issue: 66(9), P. 1510 - 1518

Published: Aug. 13, 2024

Abstract In this study, a novel multi-cell crash box was designed and produced using 15 % short carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) filaments one of the additive manufacturing methods, melt deposition method (FDM). All structures’ maximum force energy absorption performances have been investigated. As result test, it determined that box, which best meets high folding properties, expected features in boxes, has parts manufactured ABS CF15PET materials. According to test result, found is 11 higher than approximately 4.5 PLA. It response value 5 12 materials can be used boxes form an idea about design by designing analyzing finite element programs.

Language: Английский

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Marathon runner algorithm: theory and application in mathematical, mechanical and structural optimization problems

Materials Testing, Journal Year: 2024, Volume and Issue: 66(8), P. 1267 - 1291

Published: May 22, 2024

Abstract This study proposes a novel human-inspired metaheuristic search algorithm called marathon runner algorithm. method mimics competitive behaviors observed in real runners through mathematical modeling. Unlike classical elitist algorithms that prioritize position of the best agent, introduces concept vision point. point considers quality entire population, not just leader. By guiding population towards point, risk getting trapped local optima is reduced. A two-part evaluation was conducted to thoroughly assess capabilities First, it tested against set unconstrained benchmark functions and algorithm’s quantitative attributes, such as complexity, accuracy, stability, diversity, sensitivity, convergence rate are analyzed. Subsequently, applied mechanical structural optimization problems with both continuous discrete variables. application demonstrated effectiveness solving practical engineering challenges constraints. The outcomes compared those obtained by six other well-established techniques. results indicate yields promising solutions for mathematical, mechanical, problems.

Language: Английский

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