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Lif takviyeli plastik malzemeler ürün hafifletme çalışmalarında kullanılan kompozit malzemelerdendir. Anizotropik yapıda olan bu malzemelerin enjeksiyon prosesinde, akışa bağlı olarak lifler farklı yönlerde dağılabilmektedir. Bu malzemelerden imal edilen ürünlerin sonlu elemanlar modellemelerinde lif yönlerinin proses ortamından transfer edilerek tanımlanması analizin doğruluğunu artırmaktadır. Bu çalışmada, enjeksiyon kalıplama ile üretilen kısa lif takviyeli plastikten elde edilen araç pedalının sonlu elemanlar modeli oluşturularak yapısal analizi, lif oryantasyon verileri de modellemeye dahil edilerek gerçekleştirildi. Lif oryantasyon verileri, enjeksiyon simülasyonu sonucunda elde edildi ve anizotropinin de dahil edildiği çok ölçekli malzeme modelinde kullanıldı. %30 cam lif katkılı poliamid malzeme kullanılarak üretilen pedal sonuçları, takviyesiz plastik malzeme ve çelik malzeme kullanılarak üretilen pedal verileri ile karşılaştırıldı. Çelik pedala kıyasla takviyeli plastik malzemeden elde edilen pedalın yer değiştirme sonuçlarında %2.5 oranında artış, gerilme değerlerinde ise %7 oranında artış görülür. Takviyeli plastiğin 294 MPa olan akma gerilmesi referans alındığında bu artışın kısıt değerlerin altında kaldığı sonucuna varılır. Ayrıca çelik malzemeye kıyasla %20 oranında daha hafif pedal elde edilir. Fiber reinforced plastic materials are composite materials used in product lightening studies. In the injection process of these anisotropic materials, the fibers may disperse in different directions depending on the flow. In the finite element modeling of products manufactured from these materials, the identification of fiber directions by transferring them from the process environment increases the accuracy of the analysis. In this study, a finite element model of the vehicle pedal obtained from short fiber reinforced plastic produced by injection molding and structural analysis was carried out by including fiber orientation data were created. Fiber orientation data were obtained as a result of injection simulation used in the multi-scale material model including anisotropy. Pedal results produced using 30% glass fiber reinforced polyamide material were compared with pedal data produced using non-reinforced plastic material and steel material. Compared to the steel pedal, the displacement results of the pedal made of reinforced plastic material increase by 2.5% and the stress values increase by 7%. When the yield stress of reinforced plastic, which is 294 MPa, is taken as reference, it is concluded that this increase is below the constraint values. In addition, 20% lighter pedal is obtained compared to steel material.

This paper focuses on creating an optimum design and development of thermo-plunger parts for commercial vehicles in order to save material, reduce mass and make more sustainable automobiles. In this paper, natural frequency analysis, topology, and topography optimization methods have been used to create a new design for the thermo-plunger part. Thermo-plunger means an electric heater that is used for heating the inside of automobiles effectively and quickly and providing customer thermal comfort. It is positioned in the vehicle body, and its support parts have been developed by structural optimization techniques because there is not enough space in the engine compartment for automatic transmission commercial vehicles. The aim of this study is to make a lightweight and reinforced thermo-plunger support part design. Initially, a draft design was created in 3D model software. After that, topology and topography optimizations were applied on this draft design. At the end of studies, a final optimum support design has been obtained. The final design is 41.1% lighter than the initial design. At the same time, above 50 Hz natural frequency value has been obtained on the final design to avoid resonance problems. Bu makale, malzemeden tasarruf etmek, kütleyi azaltmak ve daha sürdürülebilir otomobiller yapmak üzere ticari araçlar için optimum bir termo-piston parçası tasarımı ve geliştirilmesine odaklanmaktadır. Bu makalede, termo-piston parçasında yeni tasarım oluşturmak için doğal frekans analizi, topoloji ve topografya optimizasyon yöntemleri kullanılmıştır. Termo-piston, otomobillerin içini etkin ve hızlı bir şekilde ısıtmak için kullanılan ve müşteriye ısıl konfor sağlayan elektrikli ısıtıcı anlamına gelir. Bu parça araç gövdesinde konumlandırılmış olup, otomatik şanzımanlı ticari araçlar için motor bölmesinde yeterli alan olmadığı için destek parçaları yapısal optimizasyon teknikleri ile geliştirilmiştir. Bu çalışmanın amacı, hafif ve güçlendirilmiş bir termo-piston destek parçası tasarımı yapmaktır. İlk olarak 3B modelleme yazılımında taslak tasarım oluşturulmuştur. Daha sonra bu taslak tasarım üzerinde topoloji ve topografya optimizasyonları uygulanmıştır. Çalışmalar sonunda nihai bir optimum destek parça tasarımı elde edilmiştir. Nihai tasarım, ilk tasarıma göre %41.1 daha hafiftir. Aynı zamanda, rezonans sorununu önlemek için nihai tasarımda 50 Hz'in üzerinde doğal frekans değeri elde edilmiştir.

İnsanlar gün içerisindeki faaliyetlerinin büyük bölümünü kapalı alanlarda geçirir. Bu nedenle insanlar için kapalı mahallerde iyi bir havalandırma ve iklimlendirme sistemi tasarlamak son derece kritiktir. İyi bir havalandırma, insanlarda hem vücut sağlığı hem de çalışma verimleri adına önemli bir kıstastır. Sıcaklık maruziyeti, vücudun fizyolojik ve psikolojik dengesini, çalışma verimini önemli ölçüde etkileyen ve çalışma ortamında sıkça karşılaşılan problemlerdendir. Isıl konfor ise, kişinin bulunduğu ortamın sıcaklığı ile uyumun sağlanması ve memnuniyetsizliğin bertaraf edilmesi anlamına gelmektedir. Termal konfor şartlarının tam olarak sağlanamadığı ortamlarda çalışmak zorunda kalan çalışanların verimlerinin düştüğü, güvenli çalışma durumunun zayıfladığı ve buna bağlı olarak iş kazasına maruz kalma sıklıklarının arttığı gözlemlenmiştir. Bu yüzden ısıl işlemin zorunlu olduğu, sıcaklık maruziyetinin kaynağında yok edilemediği durumlarda çalışan kişilerin termal konfor şartlarının iyileştirilmeleri öncelikle çalışanların sağlığına sonrasında ise üretim verimine olumlu katkılar sağlayacaktır. Bu çalışmada, ısıl konforu belirleyen parametreler üzerine incelemeler yapılmış olup, örnek mahal olan sıcak şekillendirme prosesi kullanılarak sac şekillendirme yapan hatta çalışan işçilerin ısıl konfor için çalışma koşulları gözlenmiştir. Isıl konforu sağlamak adına soğuk yelek üretilmiş ve ısı transferi dikkate alınarak iyileştirici faaliyetler belirlenmiştir. People spend most of their activities during the day in closed areas. Therefore, it is extremely critical to design a good ventilation and air-conditioning system in closed spaces for people. Good ventilation is an important criterion for both human health and working efficiencies. Temperature exposure is one of the most frequently encountered problems in the working environment, which significantly affects the physiological and psychological balance of the body and the working efficiency. Thermal comfort means compliance with the temperature of the person's environment and eliminating dissatisfaction. It was observed that the efficiency of the employees who had to work in the environments where the thermal comfort conditions could not be fully decreased, the safety status of the workers had weakened and the frequency of exposure to work accidents increased. Therefore, if the thermal treatment is compulsory and the temperature exposure cannot be eliminated at the source, the improvement of the thermal comfort conditions of the employees will firstly contribute to the health of the employees and then to the production efficiency. In this study, the parameters determining thermal comfort were investigated and the working conditions of the workers who worked on the sheet metal forming even by the hot forming process were observed. In order to provide thermal comfort, cold vests were produced and healing activities were determined considering heat transfer. Beyçelik

Günümüz lider üretim teknolojilerinden biri olan lazer kaplama prototip, onarım ve imalatuygulamalarında kullanılmakta olup havacılık, uzay, otomotiv, savunma sanayi, tıp vb. alanlarda genişuygulama alanına sahiptir. Üretim yöntemi, lazer ışını kullanılarak toz malzemenin ergimesi ve temelmalzeme ile nüfuziyetine dayanmaktadır. Lazer kaplama prosesinde, malzemenin nihai kalite özellikleriişlem parametrelerinden doğrudan etkilenmektedir. Bu parametrelerin önemi, malzeme makro ve mikroyapısının incelenmesi üzerine yapılan çalışmalarla ortaya konulmaktadır. Bu derleme çalışmada, lazerkaplama prosesi detaylı olarak incelenerek lazer gücü, ilerleme hızı, toz besleme hızı ve koruyucu gazproses parametrelerinin kaynak bölgesine etkileri irdelenmiş olup literatürde yer alan sonuçlarderlenmiştir., Laser cladding method, which is the one of leading manufacturing technologies of today, is used in various applications such as prototyping, product repair and material coating. It has a wide application areas: aviation, space, automotive, defense industry, medicine, etc. The production method is based on the melting of the powder material using a laser beam and its penetration with the substrate. In the laser cladding process, the final quality properties of the material are directly affected by the process parameters. The importance of these parameters is revealed by the studies on the macrostructure and microstructure of the material. In this review article, the laser cladding process has researched in detail, the effects of laser power, welding speed, powder feed rate, shielding gas process parameters on the welding area have examined, and the results obtained have given by gathered together.

Bu çalışmada PV panellerinin; anlık ışınım şiddeti değerlerinin hesabıyla; aylık, mevsimlik ve yıllık optimum eğim açıları bulunmuş, çevre sıcaklığı ve rüzgar hızı gibi parametrelerin panel verimleri ve panel elektrik gücü üzerinde etkileri incelenmiştir. Bu çalışmada kullanılan farklı optimum eğim açısı hesaplama yönteminde; eğik düzlem üzerine gelen anlık ışınım değerlerinin gün boyunca toplamı hesaplanmış ve bu hesaplama 365 gün için ayrı ayrı yapılmıştır. Böylece günlük, aylık, mevsimlik ve yıllık ışınım hesaplamaları yapılarak bu ışınım değerlerini maksimum yapan optimum açı değerleri elde edilmiştir. Elde edilen sonuçlar, aylık ortalama günlük ışınım değerleri kullanılarak bulunan optimum eğim açısı değerlerinden 3-5 o daha farklı bulunmuştur. Bu hesaplamalar 6 farklı il için yapılarak optimum eğim açıları bulunmuş, PV panellerinin optimum eğim açısı ile yerleştirilmesi durumunda panel üzerine gelen anlık ışınım, anlık panel verimleri ve üretilen elektrik gücü değerleri hesaplanmıştır. Bu hesaplamalarda çevre sıcaklığı ve rüzgar hızının etkisi de dikkate alınmıştır. In this study, PV panels; By calculating the instantaneous total radiation values; The monthly, seasonal and annual optimum tilt angles were found, and the effects of parameters such as environmental temperature and wind speed on panel efficiency and panel electrical power were investigated. In the different method of optimum tilt angle calculation used in this study; The sum of instantaneous total radiation values coming on the titled surface during the day was calculated and this calculation was made separately for 365 days. Thus, daily, monthly, seasonal and annual radiation calculations were made and optimum tilt angle values that maximize these radiation values were obtained. The results obtained were found to be 3-5 o different from the optimum tilt angle values obtained by using monthly average radiation values. These calculations were made for 6 different provinces and optimum tilt angles were found. In case the PV panels are placed with the optimum tilt angle, the instantaneous radiation on the panel, instantaneous panel efficiencies and generated electrical power values were calculated. In these calculations, the effect of environmental temperature and wind speed is also taken into account.

This study introduces the evolutionary multi-objective version of seagull optimization algorithm (SOA), entitled Evolutionary Multi-objective Seagull Optimization Algorithm (EMoSOA). In this algorithm, a dynamic archive concept, grid mechanism, leader selection, and genetic operators are employed with the capability to cache the solutions from the non-dominatedPareto. The roulette-wheel method is employed to find the appropriate archived solutions. The proposed algorithm is tested and compared with state-of-the-art metaheuristic algorithms over twenty-four standard benchmark test functions. Four real-world engineering design problems are validated using proposedEMoSOAalgorithm to determine its adequacy. The findings of empirical research indicate that the proposed algorithm is better than other algorithms. It also takes into account those optimal solutions from theParetowhich shows high convergence. VC Research

Utilizing electricity from renewable resources is very attractive to decrease the dependence on fossil fuels. As a result, hybrid power systems are gaining more attention. This paper focuses on the optimal design and dynamic simulation of renewable-based, hybrid standalone power systems. The designed system is able to meet the energy need of a building with 5 kW peak electricity demand. Both the technical and economic feasibility of the system was investigated under various climatic conditions of Turkey. Diesel fuel consumption, energy cost and annual CO2 emissions were estimated and compared with the diesel generator-only system. A parametric analysis was also conducted to understand the impact of the capacity of the PV array, wind turbine and the battery on the CO2 emissions and the levelized cost of energy. The system in each location was optimized based on the minimum energy cost and CO2 emissions. (C) 2020 Elsevier Ltd. All rights reserved.

In this paper, the sine-cosine optimization algorithm (SCO) is used to solve the shape optimization of a vehicle clutch lever. The design problem is posed for the shape optimization of a clutch lever with a mass objective function and a stress constraint. Actual function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm, and sine-cosine algorithm are used for shape optimization. The results show the ability of the sine-cosine optimization algorithm to optimize automobile components in the industry. King Fahd University of Petroleum and Minerals Khon Kaen University

In today’s world, reducing fuel consumption is one of the most important goals for the automotive industry. For this reason, weight reduction is one of the main topics in this research and for various companies. In this research, topology optimization was conducted on a suspension arm as a means of ensuring balance in automobiles. Subsequently, the model, formed by topology optimization was filled with a lattice structure and re-optimized by size optimization to obtain optimum dimensions for the model. These operations are described as lattice structure optimization. Additive manufacturing (3D printer) is necessary to produce complex models (after topology and lattice structure optimization). A static analysis of the new models was conducted by using the finite element method, and the results were compared with those of the initial design of the model. As a result of the comparison, positive results were obtained, and it was shown that topology optimization and lattice structural optimization could be used in the design of vehicle elements. According to the results obtained from lattice structure optimization, design structure can be formed more reliably than via topology optimization. In addition, both configurations and layouts of the cellular structures have a special effect on the overall performance of the lattice structure.

The shape optimization of mechanical and automotive component plays a crucial role in the development of automotive technology. Presently, the use of derivative-free metaheuristics in combination with finite element analysis for mechanical component design is one of the most focused on topics due to its simplicity and effectiveness. In this research paper, the mine blast algorithm (MBA) is used to solve the problem of shape optimization for a vehicle door hinge to prove how the MBA can be used for solving shape optimization problems in designing electrical vehicles. The results show the advantage of the MBA for designing optimal components in the automotive industry.

Due to harsh competitive conditions and the transition to new vehicles such as hybrid and full-electrical, the interest in the design of light and low-cost vehicles is increasing. In this paper, a recent metaheuristic procedure which is an equilibrium optimization algorithm (EOA) is used to solve a structural design optimization problem for a vehicle seat bracket to prove how the EOA can be used in solving industrial design problems. This paper is the first application of the EAO to real-world problems in the literature. The results strongly prove the capability of the EOA for designing optimum components in the automotive industry. Isringhausen-Aunde Teknik King Fahd University of Petroleum and Minerals Khon Kaen University

The population of the world is increasing day by day. Accordingly, the amount of production and consumption are increasing. Due to the continuous and rapid development of technology, the duration of the use of some products becomes shorter. That is why the more efficient use of limited resources is even more important. In the developing and growing automotive industry, companies are currently focusing on weight and cost reduction methods to compete. In this study, the optimum design has been achieved by using topology and shape optimization in the suspension cover used in suspension systems. As a result of the topology and shape optimization efforts, The mass of the optimum design achieved was reduced by 35.203 % according to the first design.

This work presents a thermodynamic evaluation of an operating geothermal ORC power plant. The model is realized by using measured data of AFJET geothermal power plant which has 3MWe net power output capacity. Thermodynamic assessment of the system is conducted to see the energy and exergy efficiencies of each component, and the whole plant. Additionally, a parametric study is conducted to understand the effects of various operating conditions on the system performance. Different from previous studies, daily and annual net power output profile of the plant was investigated with considering ambient temperature fluctuations. Results revealed that net power output can drop as significant as 36% from winter to summer months. Also, between nighttime to daytime, the net power expectation may decrease by 5%. The exergy destruction rate of re-injection process constitutes the most significant part (38.1%) of the total exergy destruction of the plant. The conversion and exergy efficiencies of the system are calculated as 11.24% and 39.03%, respectively. Also, to enhance the performance of the plant, an internal heat recovery system is recommended. The analyses show that the implementation of an internal heat recovery system improves the energy and exergy efficiencies of the plant by 15%.

This paper introduces a new hybrid optimization algorithm (HWOANM) based on the Nelder-Mead local search algorithm (NM) and whale optimization algorithm (WOA). The aim of hybridization is to accelerate global convergence speed of the whale algorithm for solving manufacturing optimization problems. The main objective of our study on hybridization is to accelerate the global convergence rate of the whale algorithm to solve production optimization problems. This paper is the first research study of both the whale algorithm and HWOANM for the optimization of processing parameters in manufacturing processes. The HWOANM is evaluated using the well-known benchmark problems such as cantilever beam problem, welded beam problem, and three-bar truss problem. Finally, a grinding manufacturing optimization problem is solved to investigate the performance of the HWOANM. The results of the HWOANM for both the design and manufacturing problems solved in this paper are compared with other optimization algorithms presented in the literature such as the ant colony algorithm, genetic algorithm, scatter search algorithm, differential evolution algorithm, particle swarm optimization algorithm, simulated annealing algorithm, artificial bee colony algorithm, improved differential evolution algorithm, harmony search algorithm, hybrid particle swarm algorithm, teaching-learning-based optimization algorithm, cuckoo search algorithm, grasshopper optimization algorithm, salp swarm optimization algorithm, mine blast algorithm, gravitational search algorithm, ant lion optimizer, multi-verse optimizer, whale optimization algorithm, and the Harris hawks optimization algorithm. The results show that the HWOANM provides better exploration and exploitation properties, and can be considered as a promising new algorithm for optimizing both design and manufacturing optimization problems.

There is a growing interest in designing lightweight and low-cost vehicles. In this research, the Harris hawks optimization algorithm (the HHO), the salp swarm algorithm (SSA), the grasshopper optimization algorithm(GOA), and the dragonfly algorithm (DA) are introduced to solve shape optimization problems in the automotive industry. This research is the first application of the HHO, the SSA, the GOA, and the DA to shape design optimization problems in the literature. In this paper, the HHO, the SSA, and the DA algorithms are used for shape optimization of a vehicle brake pedal to prove how the HHO, the SSA, the GOA, and the DA can be used for solving shape optimization problems. The results show the ability of the HHO, the SSA, the GOA, and the DA to design better optimal components.

Solving practical mechanical problems is considered as a real challenge for evaluating the efficiency of newly developed algorithms. The present article introduces a comparative study on the application of ten recent meta-heuristic approaches to optimize the design of six mechanical engineering optimization problems. The algorithms are: the artificial bee colony (ABC), particle swarm optimization (PSO) algorithm, moth-flame optimization (MFO), ant lion optimizer (ALO), water cycle algorithm (WCA), evaporation rate WCA (ER-WCA), grey wolf optimizer (GWO), mine blast algorithm (MBA), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). The performances of the algorithms are tested quantitatively and qualitatively using convergence speed, solution quality, and the robustness. The experimental results on the six mechanical problems demonstrate the efficiency and the ability of the algorithms used in this article. British Association for Psychopharmacology Benemérita Universidad Autónoma de Puebla

Gears are one of the most important power transmission elements in every area of the industry. Because of its importance, the gear design must be carefully performed. Unfortunately, due to the changing of the boundary conditions, gears are exposed to failures such as cracks, pitting, tooth missing etc. during the operation. Thus the gear diagnostic and monitoring become a very critical phenomenon for the gearboxes. A dynamic transmission error (DTE) based numerical fault detection model is proposed. Firstly, numerical finite element model is created to calculate single tooth stiffness with different crack levels. Furthermore, the model is used for the asymmetric gear profile which has a great importance nowadays for different areas. After that, the time-varying mesh stiffness is calculated by using single tooth stiffness with different crack levels for both symmetric and asymmetric types of the gears. To understand the effects of the gear cracks along the tooth thickness on dynamic transmission error of the gear system and to detect the gear crack faults for symmetric and asymmetric gear profiles, a four-degree of freedom dynamic model is created. The results show that with the increment of the crack level, the mesh stiffness of the gears is decreased.

This study presents the application of seven recent meta-heuristic optimization algorithms to automate design of disk cam mechanism with translating roller follower regarding four follower motion laws. The algorithms are: salp swarm algorithm (SSA), moth–flame optimization (MFO), ant lion optimizer (ALO), multi verse optimizer (MVO), grey wolf optimizer (GWO), evaporation rate water cycle algorithm (ER-WCA), and mine blast algorithm (MBA). The optimum cam design problem is formulated with three objectives including the minimum congestion, maximum performance, and maximum strength resistance of the cam. Moreover, the effect of selecting follower motion law on the optimal design of mechanism is investigated. The computational results clearly indicate that the utilized algorithms are very competitive in structural design optimization, especially MBA, ER-WCA, MFO and GWO techniques. Among the four follower motion laws, the polynomial 3-4-5 degree is the best one.

This paper introduces a new adaptive mixed differential evolution (NAMDE) algorithm for mechanical design optimisation problems. The algorithm uses a self-adaptive mechanism to update the values of mutation and crossover factors. Moreover, elitism is used where the best-found individual in each generation is retained. The performance of NAMDE is evaluated by solving 11 well-known constrained mechanical design problems and two industrial applications. Further, comparison results between NAMDE and other recently published methods, for the first problems, clearly illustrate that the proposed approach is an important alternative to solve current real-world optimisation problems. Besides this, new optimal solutions for some engineering problems are obtained and reported in this paper. For the coupling with a bolted rim problem, the objective function improved by 10%. Whereas for the spur minimisation problem, the final design provides a reduction in gearing mass by 7.5% compared to those published in previous works.

This work proposes a multi-surrogate-assisted optimisation and performance investigation of several newly developed metaheuristics (MHs) for the optimisation of vehicle crashworthiness. The optimisation problem for car crashworthiness is posed to find the shape and size of a crash box while the objective function is to maximise the total energy absorption subject to a mass constraint. Two main numerical experiments are conducted. Firstly, the performance of different surrogate models along with the proposed multi-surrogate model is investigated. Secondly, several MHs are applied to tackle the proposed crashworthiness optimisation problem by employing the best obtained surrogate model. The results reveal that the proposed multi-surrogate model is the best performer. Among the several MHs used in this study, sine cosine algorithm is the best algorithm for the proposed multi-surrogate model. Based on this study, the application of the proposed multi-surrogate model is better than using one particular traditional surrogate model, especially for constrained optimisation. Thailand Research Fund (TRF)