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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 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.

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.

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.

Gear dynamics is one of the most critical subjects in gear design because of its remarkable effect on vibration levels, load-carrying capacity, and noise. The tip relief modification is known as a simple method to decrease dynamic loads in the industry. The primary goal of this study is to understand the influence of tip relief modification on the dynamic performance of the spurs gears. In this paper, the meshing process and gear mesh stiffness calculation method are defined. A dynamic model with two- degree-of-freedom is created to find the dynamic response of the spur gear pair. The simulations are carried out with standard and different tip modified spur gear pairs. It is observed that the tip relief modification has an excellent effect on the gear dynamic response. However, this effect is restricted until a certain amount of tip relief modification. After the optimum amount of tip relief modification, the dynamic loads are increased considerably. Thus, a computer program is developed to find the optimum amount of tip relief modification in MATLAB® for the gear designers. The program outputs are given for two different case studies. As a result of the study, the dynamic factor behaves like a “V form” according to the tip relief modification, and the dynamic force decreased approximately 25% for optimum profile modification. Dişli dinamiği; titreşim seviyeleri, yük taşıma kapasitesi ve gürültü üzerindeki dikkat çekici etkileri sebebi ile dişli çark tasarımındaki en kritik unsurlardan bir tanesidir. Dişli çark uç modifikasyonu endüstride dişli çarklar üzerindeki dinamik kuvvetleri azaltmak için kullanılan bir yöntem olarak bilinmektedir. Bu çalışmanın amacı; dişli uç modifikasyonunun düz dişli çarkların dinamik performansı üzerindeki etkilerinin anlaşılmasıdır. Bu kapsamda, düz dişli çarkların kavrama sürecine ve kavrama rijitliğinin hesaplamasına yönelik bir yöntem tanımlanmıştır. Dişli çark çiftinin dinamik cevabının bulunması için iki serbestlik dereceli bir dinamik model geliştirilmiştir. Dişli uç modifikasyonun dişli çarkların dinamik performansı üzerindeki etkilerinin incelenmesi için nümerik simülasyonlar hem standart hem de uç modifikasyonu uygulanmış dişli çark çiftleri için gerçekleştirilmiştir. Uç modifikasyonu uygulamasının dişli çarkların dinamik cevabı üzerinde mükemmel bir etkisi olduğu tespit edilmiştir. Ancak, belirtilen bu pozitif etkinin de belirli bir optimum değer ile sınırlı olduğu görülmüştür. Optimum dişli uç modifikasyonu miktarı aşıldıktan sonra dişli çark üzerindeki dinamik yükler ciddi bir şekilde artmaktadır. Bu çalışmada, MATLAB® ortamında dişli çark tasarımcılarının optimum uç modifikasyonu miktarını hesaplamasına olanak sağlayacak bir bilgisayar programı geliştirilmiştir. Program çıktıları iki farklı vaka çalışması için değerlendirilerek sunulmuştur. Sonuç olarak, dinamik faktörün profil modifikasyonu ile birlikte V formda değiştiği ve optimum modifikasyon değerinde yaklaşık olarak %25 azaldığı tespit edilmiştir.

WOS:000543104900020 This paper investigates the factors affecting the optimum insulation thickness and its pay-back period, such as heating and cooling energy requirements of building, lifetime, present worth factor, costs of insulation material and installation, costs of energy sources for heating and cooling, heating and cooling system efficiencies, and solar radiation. For this purpose, by considering two cities characterizing the hot and cold climatic conditions, the optimum insulation thickness and its payback period have been calculated and a detailed parametric analysis has been carried out. To achieve practical results, the ranges of the parameters considered in the study include the values typically reported in the literature. The variations in the optimum insulation thickness and the pay-back period with all parameters are presented in graphical form. Finally, order of importance and contribution ratios of the examined parameters on the optimum insulation thickness are determined with the help of Taguchi method. It is found that heating degree-days is the most efficient parameter on the optimum insulation thickness with an impact ratio of 27.33% of the total effect while the least efficient parameter is the efficiency of heating system with an impact ratio of 3.21%.

In the literature, energetic and exergetic performance of Organic Rankine Cycle (ORC) were investigated by various researchers. The working parameters affecting the cycle's performance were determined but the impact weights and the order of importance of these parameters were not discussed with a statistical approach. In this context, nine fundamental process parameters such as working fluid type, pinch point temperature differences in the evaporator and condenser, superheating temperature, evaporation and condensation temperatures, heat exchanger effectiveness, turbine and pump efficiencies have been selected for the statistical evaluation. A comprehensive statistical analysis has been carried out to observe the effect of the parameters on the first and second law efficiencies of the ORC. The impact ratios and order of importance of these parameters on the system's performance indicators have been determined. While Taguchi method is performed to determine the optimum levels of each parameter, ANOVA method is used to obtain the impact weights of the parameters on objective functions. In addition to these methods, Grey Relational Analysis (GRA) method is used to optimize the multi-objective function. Evaporator temperature, turbine efficiency, effectiveness of heat exchanger, condenser temperature are obtained as main process parameters on the multiple performance characteristics of ORC and the impact ratios of these parameters are calculated as 31.37%, 19.53%, 16.64%, and 16.61%, respectively. The best condition for the multiple performance characteristics is determined as A(1)B(1)C(3)D(3)E(3)F(3)G(1)H(3)I(3) and under these operating conditions, the first and second law efficiencies of the system are found as 18.1% and 65.52%, respectively.

In this paper, an evaluation of the static and dynamic behavior of bimetallic spur gears with different gear parameters is performed numerically. Bimetallic lightweight spur gears working without a decrease in the performance of the gear mechanisms have many potential benefits in automotive and aerospace applications. A bimetallic spur gear consists of two metals which are steel on the gear teeth and aluminum on the hub region. The dynamic performance of these gears is evaluated by using a two degree of freedom (2-DOF) dynamic model. The finite element method is used to calculate maximum root stress for varying ring thicknesses and other gear parameters for gears with symmetric and asymmetric teeth. These stress values and the weight reduction ratios are taken into consideration to optimize the ring thickness. Tooth deflection is also calculated to determine tooth stiffness by finite element analysis (FEA). Dynamic simulations are carried out to investigate the effects of gear parameters on the dynamic force and static transmission error (STE). Sample simulation results are illustrated with numerical examples. The results indicate that, if properly designed, bimetallic gears can provide a high potential to reduce the weight in power transmission systems without adverse effects on stress and dynamic behavior. (C) 2019 Elsevier Ltd. All rights reserved.

There are various factors having an impact on the energetic and exergetic performance (i.e., COP and eCOP) of an absorption refrigeration systems (ARS) such as the temperatures of the generator, condenser, evaporator and absorber, effectiveness of solution, refrigerant and solution-refrigerant heat exchangers and isentropic efficiency of the solution pump. Many studies have focused on these process parameters, but the importance order and contribution ratios of the parameters due to thermodynamic performance have not been determined by using statistical methods. Firstly, in this study, cycles’ thermodynamic model is established and the variation of the COP and eCOP are calculated for different working conditions with different parameters ranges. The effects of these parameters on the COP and eCOP are examined separately on a statistical basis. The importance order of the parameters are determined by using Taguchi and ANOVA methods and the results are compared. Optimum operating conditions are determined by means of statistical analysis for the COP and eCOP. Under these operating conditions, the COP and eCOP of the system are calculated as 0.697 and 0.2829, respectively. Furthermore, for the simultaneous maximization of these two performance indicators, Taguchi-Grey Relational Analysis (GRA) is used. By using this analysis, importance order of the examined parameters on multiple performance characteristics are determined. The absorber and evaporator temperatures are the most efficient parameters on multiple performance characteristics with a contribution ratio of 29.66% and 26.34% of the total effect while the least efficient parameters are the pump efficiency and effectiveness of solution-refrigerant heat exchanger with a contribution ratio of 0.48% and 2.41%, respectively. For the best condition considering the multiple performance characteristics, COP and eCOP of the system are found as 0.6255 and 0.2829, respectively.

In the present study, the fatigue behaviour of a clutch diaphragm spring is investigated experimentally and numerically. Differential evolution optimisation algorithm and response surface methodology are used to define optimal variables of the diaphragm springs under constraints both minimum stress and required clamp load. The required clamp load is checked by the chi-square theorem vs. to target clamp load curve. Ten design variables are considered for creating a design of experiment with two steps, including finger shape optimisation with eight variables, load, and stress optimisation with two variables as the aim of maximum fatigue definition. One hundred seventy-five different designs are analysed numerically. As a result of the optimisation study, the optimum design is provided an endless lifetime subject to the required load, minimum stress, and minimum weight. The optimum design is manufactured and tested experimentally. Valeo

In this paper, nine recent meta-heuristics have been employed to search for optimal design of an automatic planetary gear train. The function of the designed system is to automatically transmit power and motion in automobiles. Nine mixed decision parameters are considered in the optimisation procedure. The geometric conditions such as the undercutting, the maximum overall diameter of the transmission, as well as the spacing of multiple planets are taken into account to ensure an optimum design. All the above algorithms are tested both quantitatively and qualitatively for solution quality, robustness, and their time complexity is determined. Results obtained illustrate that the utilised approaches can effectively solve the planetary gearbox problem. Besides this, the comparative study indicates that roulette wheel selection-elitist differential evolution (ReDE) outperforms the other algorithms in terms of the statistical results, and FA has the best convergence behaviour. Meanwhile, multi-verse optimisation (MVO) and butterfly optimisation algorithm (BOA) performed better than the other used algorithms when computation time was considered. King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia

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)