Person: ALBAK, EMRE İSA
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ALBAK
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EMRE İSA
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Publication Optimization design for circular multi-cell thin-walled tubes with discrete and continuous design variables(Taylor & Francis Inc, 2022-08-09) Albak, Emre İsa; ALBAK, EMRE İSA; Gemlik Asım Kocabıyık Meslek Yüksekokulu; 0000-0001-9215-0775; I-9483-2017Wall thickness and the number of cells are important elements affecting crashworthiness. While wall thickness is expressed as the continuous design variable, the number of ribs and the number of inner structures are defined as the discrete design variable. Specific energy absorption is determined as the objective, peak crushing force is selected as the constraint. Surrogate models of these functions are obtained with artificial neural networks. A loop has been developed for the selection of the ideal parameters. The study revealed that the use of discrete and continuous design variables together improves crashworthiness.Publication Correlation between objective and subjective tests for vehicle ride comfort evaluations(Sage Publications Ltd, 2022-02-23) Boke, Tevfik Ali; Bozkurt, Rasim; Ergül, Murat; Özturk, Dogan; Emiroğlu, Sinan; KAYA, NECMETTİN; Albak, Emre Isa; Öztürk, Ferruh; ALBAK, EMRE İSA; ÖZTÜRK, FERRUH; Gemlik Asım Kocabıyık Meslek Yüksekokulu; Makine Mühendisliği Bölümü; 0000-0001-9215-0775; 0000-0002-8297-0777; I-9483-2017One of the most important criteria that vehicle customers take into consideration when buying vehicles is ride comfort. Ride comfort is determined in two different ways, called objective and subjective methods. This research presents an approach for subjective and objective evaluations of vehicle ride comfort through road tests. In this study, first, reliable driver evaluation for subjective tests is made and tests are performed with these reliable drivers. Correlation between objective and subjective test results is achieved for different vehicle types and road groups and software is developed to evaluate subjective ride comfort by using objective test data acquired from the vehicle. This software is intended to be used instead of subjective tests in future vehicle development studies.Publication Simplified optimization model and analysis of twist beam rear suspension system(Sage Publications, 2021-04-01) Albak, Emre İsa; Solmaz, Erol; Öztürk, Ferruh; ALBAK, EMRE İSA; SOLMAZ, EROL; ÖZTÜRK, FERRUH; Mühendislik Fakültesi; Otomotiv Mühendisliği Bölümü; 0000-0001-9215-0775; 0000-0001-9369-3552; I-9483-2017; HRA-1531-2023; FRD-1816-2022Twist beam rear suspension systems are frequently used in front wheel drive cars owing to their compactness, lightweight and cost-efficiency. Since the kinematic behavior of twist beam rear suspension systems are determined by the elastic properties of the twist beam, the twist beam is the most critical component of this suspension system. In the study, a simplified optimization model is presented to offer designers the most suitable beam structure in the early stage of the vehicle system development. With the optimization model, designers will be able to obtain the most suitable twist beam structure in a very short time. Opposite wheel travel analysis based on finite element modeling of twist beam is conducted to examine the kinematic performance of the twist beam rear suspension. The cross-section, position and direction of the twist beam are the most important parameters affecting the performance of the twist beam rear suspension system. In this study, optimization studies with 25 design variables including variable cross-sections, twist beam position and twist beam orientation are performed. Nine different optimization studies are carried out to investigate the effects of design variables better. In optimization studies carried out with the genetic algorithm, the objective and constraint functions are obtained with the moving least squares meta-modeling method. In the study, toe angle, camber angle and roll steer are decided as constraints, and mass as the objective function. With the optimization models, lightweight designs up to 25% have been obtained according to the initial design. It is validated that the proposed simplified model and analysis of twist beam rear suspension with connecting bushing is a quite efficient approach in terms of accuracy and to speed up the optimum design process.Publication Multiobjective crashworthiness optimization of graphene type multi-cell tubes under various loading conditions (vol 43, 266, 2021)(Springer Heidelberg, 2021-06-01) Albak, Emre İsa; ALBAK, EMRE İSA; Solmaz, Erol; SOLMAZ, EROL; Öztürk, Ferruh; ÖZTÜRK, FERRUH; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Otomotiv Mühendisliği Bölümü; 0000-0001-9215-0775; 0000-0003-1790-6987; F-7426-2011; I-9483-2017Publication Optimal design of differential mount using nature-inspired optimization methods(Walter de Gruyter Gmbh, 2021-08-31) Albak, Emre İsa; Solmaz, Erol; Öztürk, Ferruh; ALBAK, EMRE İSA; SOLMAZ, EROL; ÖZTÜRK, FERRUH; Hibrit ve Elektrikli Araç Teknolojisi Programı; 0000-0001-9215-0775; I-9483-2017; DTV-6021-2022; JHZ-3155-2023Structural performance and lightweight design are a significant challenge in the automotive industry. Optimization methods are essential tools to overcome this challenge. Recently, nature-inspired optimization methods have been widely used to find optimum design variables for the weight reduction process. The objective of this study is to investigate the best differential mount design using nature-based optimum design techniques for weight reduction. The performances of the nature-based algorithms are tested using convergence speed, solution quality, and robustness to find the best design outlines. In order to examine the structural performance of the differential mount, static analyses are performed using the finite element method. In the first step of the optimization study, a sampling space is generated by the Latin hypercube sampling method. Then the radial basis function metamodeling technique is used to create the surrogate models. Finally, differential mount optimization is performed by using genetic algorithms (GA), particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), ant lion optimizer (ALO) and dragonfly algorithm (DA), and the results are compared. All methods except PSO gave good and close results. Considering solution quality, robustness and convergence speed data, the best optimization methods were found to be MFO and ALO. As a result of the optimization, the differential mount weight is reduced by 14.6 wt.-% compared to the initial design.Publication Optimization for multi-cell thin-walled tubes under quasi-static three-point bending(Springer Heidelberg, 2022-05-01) Albak, Emre İsa; ALBAK, EMRE İSA; Gemlik Asım Kocabıyık Meslek Yüksekokulu; 0000-0001-9215-0775; I-9483-2017Approaches such as changing the cell number, changing the rib direction, and adding internal structure are utilized to acquire a multi-cell thin-walled structure, and these approaches have meaningful effects on the crashworthiness performance of multi-cell thin-walled tubes. In this study, a comprehensive review is done by using and comparing these approaches together under quasi-static three-point bending conditions. A different crashworthiness indicator is better for each of the produced multi-cell thin-walled structures. The overall best tubes are determined by the complex proportion assessment (COPRAS), a multi-criteria decision-making technique. The weights used in the COPRAS technique are calculated by the entropy method. Thus, two different tubes are chosen as the best ones. Then, multi-objective optimization is performed on these tubes with the multi-objective genetic algorithm (MOGA). The surrogate models of PCF and SEA, which are defined as the objectives in multi-objective optimization studies, are obtained by the (radial basis functions) RBF. Multi-objective optimized multi-cell thin-walled W1L1 and W1L1S1 tubes achieved the same SEA values as the W0L0 square tube at 13.1% and 15.4% lower PCF values, respectively.Publication A new approach for battery thermal management system design based on grey relational analysis and latin hypercube sampling(Elsevier, 2021-09-16) Bulut, Emre; BULUT, EMRE; Sevilgen, Gökhan; SEVİLGEN, GÖKHAN; Öztürk, Ferruh; ÖZTÜRK, FERRUH; Albak, Emre İsa; ALBAK, EMRE İSA; Mühendislik Fakültesi; Otomotiv Mühendisliği Bölümü; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; ABG-3444-2020; AAG-8907-2021; I-9483-2017A liquid cooling system is an effective type of battery cooling system on which many studies are presented nowadays. In this research, the effects of the mass flow rate and number of channels on the maximum temperature and pressure drop are investigated for multi-channel serpentine cooling plates. A new approach with LHS and GRA is used to obtain the optimum ranges of design parameters to minimize the pressure drop, maximum temperature and to maximize the convective heat transfer coefficient. In this study, the values of the parameters for the numerical modeling are obtained by the experiments. The width and height of the serpentine channel and mass flow rate are chosen as input parameters and the pressure drop, convective heat transfer coefficient and maximum temperature are selected as output parameters. Comparing with the base design, the optimized design provided up to 40.3% decrease in the pressure drop with a penalty of 11.3% decrease in the convective heat transfer coefficient with a slight decrease in the maximum temperature. The proposed approach can be used to design better cooling plates to keep the batteries in safe temperature ranges and to reduce the power consumption by optimizing the pressure drop and maximum temperature values.Publication Multi-objective optimization of liquid cooling system for a twelve-cell battery module(Begell House Inc, 2022-01-01) Bulut, Emre; Albak, Emre İsa; Sevilgen, Gökhan; Öztürk, Ferruh; BULUT, EMRE; ALBAK, EMRE İSA; SEVİLGEN, GÖKHAN; ÖZTÜRK, FERRUH; Mühendislik Fakültesi; Hibrit ve Elektrikli Araç Teknolojisi Bölümü; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; I-9483-2017; AAG-8907-2021; JCO-2416-2023; FRD-1816-2022In this research, two cooling plates with six parallel channels are designed for a twelve-cell battery module. The heat generated by a Li-ion battery cell is numerically modeled, and the numerical model is validated with the experimental data. The temperature difference of the battery cells in the battery module is an important factor for the capacity usage and cycle life of a battery module. The aim of this study is to design an optimum cooling system that will increase the cycle life of the batteries by decreasing the temperature difference and reducing the parasitic power consumption of the pump by reducing the pressure drop. The channel height, channel width, and the ratio of the outlet height to the inlet height are selected as design variables. In recent years, several evolutionary multi-objective optimization techniques have been presented to improve the performance of thermal management systems. In this study, CMOPSO is used for the optimization of the liquid cooling system. The results of the NSGA-II, NSGA-III, MOPSO, and CMOPSO techniques are evaluated to compare the efficiency of different optimization techniques. The results of four different multi-objective optimization methods are close to each other and have good agreement with the CFD results to reduce the temperature difference and pressure drop. A 30.3% decrease in the temperature difference and a 5.3% decrease in the total pressure drop are achieved with CMOPSO as the optimization technique. The results show the effectiveness of CMOPSO as the optimization technique for the design of battery cooling systems.Publication Prediction and optimization of the design decisions of liquid cooling systems of battery modules using artificial neural networks(Wiley-Hindawi, 2022-01-03) Bulut, Emre; Albak, Emre İsa; Sevilgen, Gökhan; Öztürk, Ferruh; BULUT, EMRE; ALBAK, EMRE İSA; SEVİLGEN, GÖKHAN; ÖZTÜRK, FERRUH; Gemlik Asım Kocabıyık Meslek Yüksekokulu; Otomotiv Mühendisliği Bölümü; 0000-0001-9159-5000; 0000-0001-9215-0775; 0000-0002-7746-2014; I-9483-2017; ABG-3444-2020; AAG-8907-2021; FRD-1816-2022Liquid cooling systems are effective for keeping the battery modules in the safe temperature range. This study focuses on decreasing the power consumption of the pump without compromising the cooling performance. Artificial neural network (ANN) models are created to predict the effects of the height and width of the cooling channel and the mass flow rate on the maximum temperature, convective heat transfer coefficient, and pressure drop. The ANN models are used as surrogate models for the design and optimization of the liquid cooling battery system. Particle swarm optimization (PSO) and genetic algorithm (GA), which are commonly utilized optimization methods in many areas, and chaos game optimization (CGO) and coot optimization algorithm (COOT) methods, which are recently presented methods, are adopted to minimize the power consumption of the pump. The results are compared in terms of computational performance and best, worst, average, and SD values. Despite all of the optimization methods used giving similar results, the CGO method comes forward due to fast converging, SD, and finding the minimum power consumption of the pump among other optimization methods. A 22.4% decrease in the power consumption of the pump is achieved with the use of the ANN-based CGO method while conserving the cooling performance. When comparing the ANN predicted and CFD results, the relative errors are less than 1%.Publication Crashworthiness design and optimization of nested structures with a circumferentially corrugated circular outer wall and inner ribs(Elsevier, 2021-08-03) Albak, Emre İsa; ALBAK, EMRE İSA; Gemlik Asım Kocabıyık Meslek Yüksekokulu; Hibrit ve Elektrikli Araç Teknolojisi; 0000-0001-9215-0775; I-9483-2017Twenty-six nested structures with a circumferentially corrugated circular outer wall and inner ribs are investigated under quasi-static axial compression using the finite element method. The finite element model is validated by literature. Also, theoretical predictions for the nested structures are derived and compared with finite element analyses. Among the structures whose crashworthiness performances are examined, CO1D and CSIN2D are selected as the best ones. The comparisons have shown that the ribs attached to the closest points of the corrugated outer wall provide stable collapse modes and better crash performance. Also, the crashworthiness performance of the nested structures with octagon inner structures is higher than other alternative structures because the number of corner members and the cross-section lengths are more efficient. Finally, the objective functions developed by the surrogate modeling method are optimized by non-dominated sorting genetic algorithm II (NSGA-II), multi-objective particle swarm optimization (MOPSO), paired offspring generation for constrained large-scale multiobjective optimization (POCEA) and an evolutionary algorithm for large-scale many-objective optimization (LMEA). Optimum CO1D and CSIN2D designs obtained by the NSGAII method have 37.00% and 26.68% higher SEA values, respectively than 'Cribs' structure at the same PCF value.