Person: HARTOMACIOĞLU, SELİM
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HARTOMACIOĞLU
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SELİM
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Publication Metadata only Comparison and validation of finite element analysis with a servo-hydraulic testing unit for a biodegradable fixation system in a rabbit model(CHURCHILL LIVINGSTONE, 2014) ATALI, ONUR; Atali, O.; Varol, A.; Basa, S.; Ergun, C.; Hartomacioglu, S.The aim of this study was the biomechanical validation of three-dimensional finite element analysis (FEA) with a servo-hydraulic testing unit (STU) for a resorbable fixation system (RFS) in a rabbit model. Bilateral mandibular vertical body osteotomies (BMVBO) were performed in 15 female New Zealand rabbits. The animals were divided into three groups. The STU and FEA tests were done immediately after surgery in group 1 (1 day), at the first postoperative month in group 2, and at the third postoperative month in group 3. Both stress tests were carried out by applying vertical forces at the lower incisal edge, loading from 0 N force and increasing this until breakage occurred at the bone. The maximum forces that the hemimandibles could stand and the amount of deformation were recorded and analysed with the FBA and STU tests. We found the STU and FEA test results to be similar and that they could be used interchangeably for groups 1 and 3. However, the FEA results differed most from the real STU values in group 2 because of callus formation that had not ossified at the osteotomy line.Publication Open Access CFD analysis for predicting cooling time of a domestic refrigerator with thermoelectric cooling system(ELSEVIER SCI LTD, 2021-03) ONAT, AYHAN; Soylemez, Engin; Alpman, Emre; Onat, Ayhan; Hartomacioglu, SelimIn this work, Computational Fluid Dynamics (CFD) analysis was conducted considering three different turbulence (viscous) models for a fresh food compartment of a domestic refrigerator (DR), in order to not only gain idea on cooling down time rate of fresh food compartment but also present air and temperature distribution inside the compartment when it is loaded. The refrigerator composes of three compartments: Fresh food (FFC), chill (CC) and freezer (FC). The FFC compartment is cooled by a thermoelectric/Peltier cooler (TEC) while the other compartments are handled by a vapour compression (VC) system. To measure cooling times, tests were conducted according to new IEC62552:2015 standard in climatic chambers and the cooling time was measured as 146.5 min. The predictions of developed CFD model clearly visualize the airflow and temperature fields inside the FFC. Concerning numerical predictions for the packages in the upper regions were in better agreement (below 10%) with measurements than the predictions for the packages in the lower regions mainly due to convective heat transfer behaviour. (C) 2020 The Author(s). Published by Elsevier Ltd.Publication Metadata only Numerical (CFD) and experimental analysis of hybrid household refrigerator including thermoelectric and vapour compression cooling systems(ELSEVIER SCI LTD, 2019) ONAT, AYHAN; Soylemez, Engin; Alpman, Emre; Onat, Ayhan; Yukselenturk, Yalcin; Hartomacioglu, SelimNumerical and experimental analysis of a previously investigated hybrid household refrigerator (HHR), HHR I, were conducted in this study. To determine the optimum location for the thermoelectric cooler installed in HHR I, CFD analysis was performed. As a result of the CFD predictions, two new HHRs, namely HHR II and III, were created and experimentally investigated. CFD predictions showed a more uniform air velocity and temperature distributions inside the fresh food compartments of HHR II and III compared to HHR I. Additionally, experimental measurements indicated a considerable increase in the energy efficiency of HHR II and III. Their energy consumption was nearly identical and improvements of up to 10% and 27% at the ambient temperatures of 16 degrees C and 32 degrees C, respectively, were observed when compared to HHR I. Regarding the cooling time, no effect of the relocation of the TEC was observed at the TEC's nominal voltage of 24 V. (C) 2019 Elsevier Ltd and IIR. All rights reserved.Publication Metadata only Using an rtificial neural network approach for supplier evaluation process and a sectoral application(2011-01-01) YAYLA, AYŞE; HARTOMACIOĞLU, SELİM; YAYLA A., HARTOMACIOĞLU S.In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN) model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network\"s independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network\"s input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network\"s inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network\"s outputs. The data set of the network\"s are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.Publication Open Access Determination of penetration depth at high velocity impact using finite element method and artificial neural network tools(ELSEVIER SCIENCE BV, 2015-06) EKİCİ, BÜLENT; Kilic, Namik; Ekici, Bulent; Hartomacioglu, SelimDetermination of ballistic performance of an armor solution is a complicated task and evolved significantly with the application of finite element methods (FEM) in this research field. The traditional armor design studies performed with FEM requires sophisticated procedures and intensive computational effort, therefore simpler and accurate numerical approaches are always worthwhile to decrease armor development time. This study aims to apply a hybrid method using FEM simulation and artificial neural network (ANN) analysis to approximate ballistic limit thickness for armor steels. To achieve this objective, a predictive model based on the artificial neural networks is developed to determine ballistic resistance of high hardness armor steels against 7.62 mm armor piercing ammunition. In this methodology, the FEM simulations are used to create training cases for Multilayer Perceptron (MLP) three layer networks. In order to validate FE simulation methodology, ballistic shot tests on 20 mm thickness target were performed according to standard Stanag 4569. Afterwards, the successfully trained ANN(s) is used to predict the ballistic limit thickness of 500 HB high hardness steel armor. Results show that even with limited number of data, FEM-ANN approach can be used to predict ballistic penetration depth with adequate accuracy. Copyright (C) 2015, China Ordnance Society. Production and hosting by Elsevier B.V. All rights reserved.