Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2025Scopus SJRQ1Investigation of notch effect in the optimum weight design of steel truss towers via Particle Swarm Optimization and Firefly Algorithm
Yilmaz, Elif; Artar, Musa; Ergün, Mustafa
In this study, the optimal weight designs of steel truss towers are determined, considering the notch effect. Thus, the impact of discontinuities in the cross-sections of steel elements on the total weight of the structure is revealed. For this purpose, the optimal weight designs of different truss towers analyzed by other researchers in previous years are reexamined using Particle Swarm Optimization and Firefly Algorithm. The main program where finite element analyses and optimization algorithms are encoded has been developed in MATLAB. Displacement, stress, geometric, and section height constraints are used in optimization methods. The effectiveness of these methods has been demonstrated by comparing both the results in the literature and with each other under un-notched conditions. Subsequently, considering the notch effect on the tension bar with the highest stress capacity in each structure, the impact of stress concentration on the minimum weight sizing of the structure is investigated using these proven methods. When the analysis results of both cases are examined, it is observed that the optimum weights of all structures under the notch effect have slightly increased. The stress concentration around the notch severely raises the nominal stress in the cross-section. In this case, the cross-section becomes insufficient due to the overcapacity, requiring larger profiles. The structure’s weight shows an increasing trend depending on the number of notched elements and the severity of stress concentration. Additionally, SAP2000 software is utilized for numerical simulations of the structures under identical conditions, enhancing the research content and providing further support for the comprehensive design optimization analyses. Consequently, minimizing the adverse effects of notches through careful material selection, proper manufacturing and assembly techniques, and regular maintenance is essential. The effects of notches should be considered in structural analysis and design, with measures taken to mitigate these effects when necessary.
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İncele - MakaleAçık Erişim2023Scopus SJRQ1The effect of various industrial dust particles on the performance of photovoltaic panels in Turkey
Güngör, Okan; Kahveci, Hakan; Gökçe, H. Süleyman
The accumulation of dust is one of the main causes of power loss in photovoltaic (PV) farms, and the effect of dust particles’ size and chemistry on system performance is often overlooked. This study has focused on a comprehensive analysis of the effect of different dust particles collected from common industrial production facilities in Turkey on the performance of PV panels in the indoor laboratory environment. The collected dust samples were analyzed to determine the dust sample particles’ chemical properties, size, character, and topography. The data for dust samples at different weights with changes in maximum power point (MPP) of PV panel has been collected using the artificial solar irradiation source system. Thus, the mathematical correlations (R2≥0.965) between the PV panel Thevenin resistance (RTH), fill factor (FF), MPP, and pollution rate were obtained using these collected data and particle swarm optimization (PSO). According to the results of the obtained mathematical correlations, marble dust is 2.3, 3.4, and 4.2 times less polluting than cement, fly ash, and silica fume, respectively. Additionally, it was observed that smaller dust particles block more light than larger ones of the same weight and reduce MPP, FF while increasing the RTH.
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İncele - Yüksek Lisans TeziAçık Erişim2022Çelik kule yapıların gerilme yığılması etkisi altında parçacık sürü optimizasyonu ve ateş böceği algoritması ile optimum tasarımı
Elif Yılmaz
Çelik yapılara olan rağbet gün geçtikçe artmaktadır. Çelik yapıların betonarme yapılara göre maliyeti yüksektir. Bu nedenle daha az maliyetle çelik yapı üretmek gerekmektedir. Son yıllarda yapay zekaya dayalı optimizasyon teknikleri gün geçtikçe artmaktadır. Mühendislik problemlerinin çözümünde de kullanılan yapay zeka maliyeti düşürerek optimum sonuç vermektedir. İmalat sonrası çekme çubuklarında meydana gelebilecek yorulmaya veya malzeme kusurlarına (parçalardaki boşluklar, eleman üzerindeki ani kesit değişikliği, çentik veya delik gibi sebepler) bağlı olarak malzeme sürekliliği bozulabilmektedir. Malzeme sürekliliğinin bozulduğu noktalarda gerilmeler normal değerinden uzaklaşıp maksimum seviyeye ulaşmaktadır. Bu durum gerilme yığılması olarak adlandırılmaktadır. Gerilme yığılmasının ortaya çıktığı elemanlarda gerilme durumu karmaşık olabilmektedir. Bu karmaşıklığı sadece basit eğilme ya da basınç, basit burulma ve basit eğilme yöntemleri ile çözmek mümkün olmayabilir. Bu durumda gerilme yığılması faktörü olan K katsayısı hesaplara dahil olmaktadır. Bu çalışmanın amacı farklı yıllarda geliştirilen sezgisel iki algoritmanın optimizasyon işlemi üzerindeki etkinliğini test etmektir. Bunun için sezgisel optimizasyon algoritmalarından 1995 yılında geliştirilen parçacık sürü optimizasyonu (PSO) ve 2009 yılında geliştirilen ateş böceği algoritması (FFA) kullanılmıştır. Optimizasyon işlemi için literatürde farklı algoritma teknikleri ile optimize edilmiş 25 elemanlı, 72 elemanlı ve 582 elemanlı uzay kafes kule yapıları ile 52 elemanlı düzlem kafes kule yapısı kullanılmıştır. Optimizasyon işleminde bulunan sonuçlar bu örneklerin farklı algoritma teknikleri ile optimize edildiği çalışmalarla karşılaştırılmıştır. Daha sonra en yüksek gerilme kapasitesine sahip elemanda çentik olduğu düşünülerek bu elemana ait gerilme değeri gerilme yığılması katsayısı K ile çarpılıp optimizasyon işlemi yeniden yapılmış ve sonuçlar tablolarla sunulmuştur. Anahtar kelimeler: Optimizasyon, parçacık sürü optimizasyonu, ateş böceği algoritması, gerilme yığılması, çelik kule.
- MakaleAçık Erişim2020Scopus SJRQ1Development of particle swarm and topology optimization-based modeling for mandibular distractor plates
Şensoy, Abdullah Tahir; Kaymaz, Irfan; Ertaş, Ümit
Mandibular Distraction Osteogenesis (MDO) is a common clinical procedure to correct mandibular retrognathia. However, since there is not a gold standard for determining the screw positions for current MDO operations, deviation of distraction direction and malocclusion increases. This case results in need of additional operations that affect the callus stability. In these cases, relapse risk increases and remodelling period gets longer. On the other hand, large volume of the distractor plates results in more invasive treatment and negatively affects the patients’ comfort. To overcome these problems, this study offers a new method including; virtual surgery simulation, determining the optimum screw configuration using particle swarm optimization loop linked between MATLAB-PYTHON-ANSYS programs and the design of distractor plate geometry with topology optimization. In order to test the proposed method, two different Finite Element (FE) models, CM and OM, were established based on conventional and optimum method, respectively. FEA results of the current study reveals that OM has 33.56% less displacement compared to CM, and the most critical screw in terms of screw loosening for OM has 35.29% less strain value than CM. These outcomes show OM shows superior callus stability in comparison with CM. On the other hand, redesign of the distractor plates using topology optimization according to the best screw positions provides 43.32% reduction in the total implant volume which means reduced cost and a less invasive MDO operation. Therefore, the clinical use of this protocol is expected to increase the success of the operation by shortening the recovery period.
AtıfScopus13WoS11OpenAlex13İncele - MakaleYalnız künye2020Scopus SJRQ1Simulation and optimization of gamma-ray linear attenuation coefficients of barite concrete shields
Şensoy, A.T.; Gökçe, H.S.
The remarkable increment in radioactivity risks of today's industrial world is required to the efficient design of shielding structures. In the present study, the optimal design parameters of barite concrete shields for providing the highest gamma radiation shielding capability were researched by using a hybrid technique of the Box-Behnken Design based response surface method and Particle Swarm Optimization. Barite aggregate fraction, water-to-cement ratio and cement content of the shields were limited as 0:100 (by weight), 0.30:0.70 (by weight) and 200:600 (kg/m3) in the optimization problem, respectively. The regression equation derived from the regression learning process presented an excellent correlation to define the XCOM linear attenuation coefficients. A nonlinear response surface fitted to the regression equation was used as the validation of the PSO results obtained from MATLAB. The results of this study have shown that the proposed method provides satisfactory predictions for the barite concrete radiation-shielding capability depending on the design parameters. In addition, it was found that the linear attenuation coefficient could be increased by 102% by the design of the best shield according to the poorest mixture.
AtıfScopus77WoS66İncele - MakaleYalnız künye2020Scopus SJRQ2Investigating the Optimum Model Parameters for Casting Process of A356 Alloy: A Cross-validation Using Response Surface Method and Particle Swarm Optimization
Şensoy, Abdullah Tahir; Çolak, Murat; Kaymaz, Irfan; Dispinar, Derya
This study aimed to determine the optimal casting parameters for the maximum fluidity of A356 alloy. Gravity die cast method was used. For this purpose, central composite design (CCD) was performed. The input parameters and their limits for the trial design were selected as pre-heating temperature (100–400 °C), casting temperature (680–760 °C), and cross-sectional thickness (1–10 mm). Using the CCD-based simulation results of the feed distance, a highly correlated full-quadratic regression equation was obtained with the highest R2 (0.99), which then was used as the objective function for the particle swarm optimization (PSO) process. The highest value of the response parameter, flow distance, reached up to 491.19 mm when the input parameters were selected as 400 °C, 760 °C and 10 mm, respectively. The sensitivity analysis has shown that the most effective parameter on the fluidity is the cross-sectional thickness. The response surface method (RSM)-based optimization results have been also validated using the PSO method. Although the higher temperatures have been found to result in better fluidity, there may be some drawbacks to working at higher temperatures such as energy cost and mould life. To determine the optimum input parameters, the RSM model suggested in this study can be modified for any type of casting process. Moreover, especially for a complex-shaped part, the manufacturer can be advised regarding operating conditions such as pre-heating and casting temperatures.
AtıfScopus11WoS9OpenAlex13İncele - MakaleAçık Erişim2020Scopus SJRQ3Determining the optimum model parameters for oligosaccharide production efficiency using response surface integrated particle swarm optimization method: an experimental validation study
Şensoy, Abdullah Tahir; İspirli, Hümeyra; Dertli, Enes
Glucansucrases (GTFs) catalyzes the synthesis of α-glucans from sucrose and oligosaccharides in the presence of an acceptor sugar by transferring glucosyl units to the acceptor molecule with different linkages. The acceptor reactions can be affected by several parameters and this study aimed to determine the optimal reaction parameters for the production of glucansucrase-based oligosaccharides using sucrose and maltose as the donor and acceptor sugars, respectively via a hybrid technique of Response Surface Method (RSM) and Particle Swarm Optimization (PSO). The experimental design was performed using Central Composite Design and the tested parameters were enzyme concentration, acceptor:donor ratio and the reaction period. The optimization studies showed that enzyme concentration was the most effective parameter for the final oligosaccharides yields. The optimal values of the significant parameters determined for enzyme concentration and acceptor:donor ratio were 3.45 U and 0.62, respectively. Even the response surface plots for input parameters verified the PSO results, an experimental validation study was performed for the reverification. The experimental verification results obtained were also consistent with the PSO results. These findings will help our understanding in the role of different parameters for the production of oligosaccharides in the acceptor reactions of GTFs.
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