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YILDIZ, ALİ RIZA

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YILDIZ

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ALİ RIZA

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Now showing 1 - 10 of 48
  • No Thumbnail Available
    Publication
    Nature-inspired algorithms for real-life complex engineering problems
    (Bentham Science Publ Ltd, 2021-01-01) Dhiman, Gaurav; Yıdız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü; F-7426-2011
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    Optimum design of a seat bracket using artificial neural networks and dandelion optimization algorithm
    (Walter de Gruyter Gmbh, 2023-10-13) Erdaş, Mehmet Umut; Kopar, Mehmet; Yıldız, Betül Sultan; Yıldız, Ali Rıza; Erdaş, Mehmet Umut; Kopar, Mehmet; YILDIZ, BETÜL SULTAN; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0003-1790-6987; AAH-6495-2019; F-7426-2011; CNV-1200-2022; DBQ-9849-2022
    Nature-inspired metaheuristic algorithms are gaining popularity with their easy applicability and ability to avoid local optimum points, and they are spreading to wide application areas. Meta-heuristic optimization algorithms are used to achieve an optimum design in engineering problems aiming to obtain lightweight designs. In this article, structural optimization methods are used in the process of achieving the optimum design of a seat bracket. As a result of topology optimization, a new concept design of the bracket was created and used in shape optimization. In the shape optimization, the mass and stress values obtained depending on the variables, constraint, and objective functions were created by using artificial neural networks. The optimization problem based on mass minimization is solved by applying the dandelion optimization algorithm and verified by finite element analysis.
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    Gradient-based optimizer for economic optimization of engineering problems
    (Walter De Gruyter Gmbh, 2022-05-25) Mehta, Pranav; Sait, Sadiq M.; Yıldız, Betül Sultan; YILDIZ, BETÜL SULTAN; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0002-4796-0581; 0000-0003-1790-6987; F-7426-2011; AAL-9234-2020; B-3604-2008
    Optimization of the heat recovery devices such as heat exchangers (HEs) and cooling towers is a complex task. In this article, the widely used fin and tube HE (FTHE) is optimized in terms of the total costs by the novel gradient-based optimization (GBO) algorithm. The FTHE s have a cylindrical tube with transverse or longitudinal fin enhanced on it. For this study, various constraints and design variables are considered, with the total cost as the objective function. The study reveals that the GBO provides promising results for the present case study with the highest success rate. Also, the comparative results suggest that GBO is the robust optimizer in terms of the best-optimized values of the fitness function vis-a-vis design variables. This study builds the future implications of the GBO in a wide range of engineering optimization fields.
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    Simultaneous aerodynamic and structural optimisation of a low-speed horizontal-axis wind turbine blade using metaheuristic algorithms
    (Walter de Gruyter Gmbh, 2023-04-12) Sabangban, Numchoak; Panagant, Natee; Bureerat, Sujin; Wansasueb, Kittinan; Kuma, Sumit; Yıldız, Ali Riza; Pholdee, Nantiwat; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Makine Mühendisliği Bölümü; F-7426-2011
    This work presents a concurrent design and multi-objective optimisation framework of horizontal axis wind turbine blades, made of composite material, for low wind speed. The optimisation model aims to minimise the structural mass of the blade whilst simultaneously maximising the turbine power output, subjected to three constraints viz. blade tip deflection, and Tsai-Hill and von Mises criteria. The design variables are blade shape and details of the internal blade structure. The control points and polynomial interpolation technique were adopted to determine the blade shape while the airfoil types at blade sections remained fixed. The internal blade structure design variables include the thickness of ribs and spars and the carbon fibre thickness and orientations. The blade element momentum approach is utilised to calculate turbine power and structural loads, whereas a finite element method is employed for structural analysis. Twelve multi-objective metaheuristics algorithms are used to solve the proposed multi-objective optimisation problem while their performance is investigated. The results obtained show that the multi-objective cuckoo search algorithm is the most efficient method. This study is said to be the baseline for a future study on multi-objective optimisation which combines two design stages of the composite low-speed wind turbine blades.
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    A comparative study of state-of-the-art metaheuristics for solving many-objective optimization problems of fixed wing unmanned aerial vehicle conceptual design
    (Springer, 2023-04-11) Anosri, Siwakorn; Panagant, Natee; Champasak, Pakin; Bureerat, Sujin; Thipyopas, Chinnapat; Kumar, Sumit; Pholdee, Nantiwat; Yıldız, Betül Sultan; Yıldız, Ali Riza; YILDIZ, ALİ RIZA; YILDIZ, BETÜL SULTAN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0001-7592-8733 ; AAH-6495-2019; F-7426-2011
    The complexity of aircraft design problems increases with many objectives and diverse constraints, thus necessitating effective optimization techniques. In recent years many new metaheuristics have been developed, but their implementation in the design of the aircraft is limited. In this study, the effectiveness of twelve new algorithms for solving unmanned aerial vehicle design issues is compared. The optimizers included Differential evolution for multi-objective optimization, Many-objective nondominated sorting genetic algorithm, Knee point-driven evolutionary algorithm for many-objective optimization, Reference vector guided evolutionary algorithm, Multi-objective bat algorithm with nondominated sorting, multi-objective flower pollination algorithm, Multi-objective cuckoo search algorithm, Multi-objective multi-verse optimizer, Multi-objective slime mould algorithm, Multi-objective jellyfish search algorithm, Multi-objective evolutionary algorithm based on decomposition and Self-adaptive many-objective meta-heuristic based on decomposition. The design problems include four many-objective conceptual designs of UAV viz. Conventional, Conventional with winglet, Twin boom and Canard, which are solved by all the optimizers employed. Widely used Hypervolume and Inverted Generational Distance metrics are considered to evaluate and compare the performance of examined algorithms. Friedman's rank test based statistical examination manifests the dominance of the DEMO optimization technique over other compared techniques and exhibits its effectiveness in solving aircraft conceptual design problems. The findings of this work assist in not only solving aircraft design problems but also facilitating the development of unique algorithms for such challenging issues.
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    Publication
    Aircraft control parameter estimation using self-adaptive teaching-learning-based optimization with an acceptance probability
    (Hindawi, 2021-12-01) Kanokmedhakul, Yodsadej; Panagant, Natee; Bureerat, Sujin; Pholdee, Nantiwat; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0003-1790-6987; F-7426-2011
    This work presents a metaheuristic (MH) termed, self-adaptive teaching-learning-based optimization, with an acceptance probability for aircraft parameter estimation. An inverse optimization problem is presented for aircraft longitudinal parameter estimation. The problem is posed to find longitudinal aerodynamic parameters by minimising errors between real flight data and those calculated from the dynamic equations. The HANSA-3 aircraft is used for numerical validation. Several established MHs along with the proposed algorithm are used to solve the proposed optimization problem, while their search performance is investigated compared to a conventional output error method (OEM). The results show that the proposed algorithm is the best performer in terms of search convergence and consistency. This work is said to be the baseline for purely applying MHs for aircraft parameter estimation.
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    Experimental investigation of mechanical properties of PLA, ABS, and PETG 3-d printing materials using fused deposition modeling technique
    (Walter De Gruyter Gmbh, 2023-09-08) Kopar, Mehmet; Yıldız, Ali Rıza; Kopar, Mehmet; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü,; 0000-0003-1790-6987; F-7426-2011; DBQ-9849-2022
    In recent years, there has been a logarithmic interest in three-dimensional printing technologies. This technique has made it possible to make more intricately shaped parts of superior quality, allowing for use in a variety of industries, including aircraft, automobiles, and ships. This study characterized the materials and assessed the mechanical features of PLA, PETG, and ABS materials generated at various raster angles. The strength ratios of the various materials have been found to fluctuate when the raster angles change. The PLA parts created at a picture raster angle of 45 degrees had the maximum tensile strength. ABS material created with a picture raster angle of 45 degrees has been shown to have the best energy absorption, and PLA material made with a raster angle of 45 degrees has the best performance compressive strength. When bending strength was evaluated, it was found that samples of ABS made with a raster angle of 0-90 degrees had the greatest value. The SEM micrographs were obtained, and the tensile test was used to examine the fracture behavior of the materials. As a result, it has been found that materials created using various raster angles can have various strength values from one another.
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    Publication
    Optimal design of aerospace structures using recent meta-heuristic algorithms
    (Walter de Gruyter Gmbh, 2021-11-01) Korkmaz, Faik Fatih; Yıldız, Ali Riza; Subran, Mert; Korkmaz, Faik Fatih; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Türk Havacılık ve Uzay Sanayi Ar-Ge Merkezi; 0000-0003-1790-6987; KUC-9229-2024; F-7426-2011
    Most conventional optimization approaches are deterministic and based on the derivative information of a problem's function. On the other hand, nature-inspired and evolution-based algorithms have a stochastic method for finding the optimal solution. They have become a more popular design and optimization tool, with a continually growing development of novel algorithms and new applications. Flexibility, easy implementation, and the capability to avoid local optima are significant advantages of these algorithms. In this study, shapes, and shape perturbation limits of a bracket part, which is used in aviation, have been set using the hypermorph tool. The objective function of the optimization problem is minimizing the volume, and the constraint is maximum von Mises stress on the structure. The grey wolf optimizer (GWO) and the moth-flame Optimizer (MFO) have been selected as nature-inspired evolution-based optimizers.
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    Publication
    Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications
    (Walter De Gruyter Gmbh, 2021-01-01) Gürses, Dildar; Bureerat, Sujin; Sait, Sadiq M.; Yıldız, Ali Rıza; GÜRSES, DİLDAR; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; JCN-8328-2023 ; F-7426-2011
    This paper focuses on a comparision of recent algorithms such as the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm. The slime mold algorithm (SMA) is a recent optimization algorithm. In order to strengthen its exploitation and exploration abilities, in this paper, a new hybrid slime mold algorithm-simulated annealing algorithm (HSMA-SA) has been applied to structural engineering design problems. As a result of the rules and practices that have become mandatory for fuel emissions by international organizations and governments, there is increasing interest in the design of vehicles with minimized fuel emissions. Many scientific studies have been conducted on the use of metaheuristic methods for the optimum design of vehicle components, especially for reducing vehicle weight. With the inspiration obtained from the above-mentioned methods, the HSMA-SA has been studied to solve the shape optimization of a design case to prove how the HSMA-SA can be used to solve shape optimization problems. The HSMA-SA provides better results as an arithmetic optimization algorithm than the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm.
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    Publication
    A comparative study of recent non-traditional methods for mechanical design optimization (vol 27, pg 1031, 2020)
    (Springer, 2021-01-01) Yıldız, Ali Rıza; Abderazek, Hammoudi; Mirjalili, Seyedali; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Otomotiv Mühendisliği Bölümü; F-7426-2011