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GÜRSES, DİLDAR

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DİLDAR

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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
    African vultures optimization algorithm for optimization of shell and tube heat exchangers
    (Walter De Gruyter Gmbh, 2022-08-26) Mehta, Pranav; Sait, Sadiq M.; Gürses, Dildar; GÜRSES, DİLDAR; Yıldız, Ali Riza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi.; 0000-0002-4796-0581; 0000-0003-1790-6987; F-7426-2011
    Nature-inspired optimization algorithms named meta-heuristics are found to be versatile in engineering design fields. Their adaptability is also used in various areas of the Internet of things, structural design, and thermal system design. With the very rapid progress in industrial modernization, waste heat recovery from the power generating and thermal engineering organization is an imperative key point to reduce the emission and support the government norms. However, the heat exchanger is the component applied in various heat recovery processes. Out of the available designs, shell and tube heat exchangers (SHTHEs) are the most commonly adopted for the heat recovery process. Hence, cost minimization is the major aspect while designing the heat exchanger confirming various constraints and optimized design variables. In this study, cost minimization of the SHTHE is performed by applying a novel metaheuristic algorithm which is the African vultures optimization algorithm (AVOA). Adopting the AVOA for the best-optimized value (least cost of heat exchanger) and the design parameters are realized, confirming all the constraints. It was found that the AVOA is able to pursue the best results among the rest of them and can be used for the cost optimization of the plate-fin and tube-fin heat exchanger case studies.
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    Publication
    Cheetah optimization algorithm for optimum design of heat exchangers
    (Walter De Gruyter Gmbh, 2023-06-30) Sait, Sadiq M.; Mehta, Pranav; YILDIZ, ALİ RIZA; Gürses, Dildar; GÜRSES, DİLDAR; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi.; Bursa Uludağ Üniversitesi/Gemlik Asım Kocabıyık Meslek Yüksekokulu.; 0000-0002-4796-0581; 0000-0003-1790-6987; F-7426-2011; JCN-8328-2023
    Thermal system optimization is always a challenging task due to several constraints and critical concepts of thermo-hydraulic aspects. Heat exchangers are one of those devices that are widely adopted in thermal industries for various applications such as cryogenics, heat recovery, and heat transfer applications. According to the flow configurations and enhancement of fins, the heat exchangers are classified as plate-fin heat exchangers, shell and tube heat exchangers, and tube-fin heat exchangers. This article addresses the economic optimization challenge of plate-fin heat exchangers using cheetah optimization (CO) algorithm. The design variables were optimized using the CO algorithm, and statistical results were compared with eight well-established algorithms. The study revealed that the cheetah algorithm is prominent in terms of realizing minimizing the overall cost of the plate-fin heat exchanger with a 100 % of success rate. Furthermore, the study suggests adopting the cheetah optimizer for solving optimization challenges in different fields.