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    Analysis of extrusion welding in magnesium alloys - numerical predictions and metallurgical verification
    (Elsevier Science Bv, 2014) Alharthi, Nabeel; Bingol, Sedat; Ventura, Anthony; Misiolek, Wojciech
    Solid-state bonding or extrusion welding takes place during hot extrusion of hollow shapes. The weld integrity is critical for mechanical performance of the produced profiles. To evaluate the weld integrity, a novel modeling method using DEFORM (TM) was proposed by Xu and Misiolek (2011) and modified in the present study. Metallurgical analysis of extruded magnesium alloy AM30 revealed two types of extrusion weld seams. The first seam type does not show a weld line which indicates perfect solid state bonding, and the second type contains a weld line, which could be a potential source of imperfections in the extrudate. (C) 2014 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
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    Application of gene expression programming in hot metal forming for intelligent manufacturing
    (Springer, 2018) Bingol, Sedat; Kihcgedik, Hidir Yanki
    Design of the die in hot metal forming operations depends on the required forming load. There are several approaches in the literature for load prediction. Artificial neural networks (ANNs) have been successfully used by a few researches to estimate the forming loads. This paper aims at using the effectiveness of a new evolutionary approach called gene expression programming (GEP) for the estimation of forging load in hot upsetting and hot extrusion processes. Several parameters such as angle (alpha), L/D ratio (R), friction coefficient (A mu), velocity (v) and temperature (T) were used as input parameters. The accuracy of the developed GEP models was also compared with ANN models. This comparison was evidenced by some statistical measurements (R (2), RMSE, MAE). The outcomes of the study showed that GEP can be used as an effective tool for representing the complex relationship between the input and output parameters of hot metal forming processes.
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    The Decreasing of the Extrusion Time with Varying Ram Speed
    (Taylor & Francis Inc, 2015) Bingol, Sedat
    In the extrusion process, friction and workpiece deformation usually cause an increase in the temperature of the extrudate. During the stroke, this temperature increase may reach a critical level and restrict the ram speed. In this study, extrusion processes, which were conducted under real production conditions, were simulated at different ram speeds using finite element modeling. In this way, the maximum workable constant ram speed was determined according to a defined critical extrusion temperature as a reference value. In the next stage, new ram-speed models were developed as alternatives to the maximum-workable, constant ram speed. The results showed that the time taken to extrude could be significantly shortened by using these models.
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    Effect of cobalt nanoparticles on mechanical properties of Sn-58Bi solder joint (vol 33, pg 22573, 2022)
    (Springer, 2022) Bashir, M. Nasir; Saad, Hafiz Muhammad; Rizwan, Muhammad; Bingol, Sedat; Channa, Iftikhar Ahmed; Gul, Mustabshirha; Haseeb, A. S. M. A.
    [Abstract Not Available]
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    Extrusion load prediction of gear-like profile for different die geometries using ANN and FEM with experimental verification
    (Springer London Ltd, 2015) Bingol, Sedat; Ayer, Onder; Altinbalik, Tahir
    This paper deals with the extrusion of gear-like profiles and uses of finite element method (FEM) and artificial neural network (ANN) to predict the extrusion load. In the study, gear-like components has been manufactured by forward extrusion for the AA1070 aluminum alloy and the process was simulated by using a DEFORM-3D software package to establish a database in order to provide the data for ANN modeling. Serious experiments were performed for only one die set and four teeth gear profile to obtain data for comparing with DEFORM-3D results. After verifying a highly appropriate FEM simulation with the experiment at the same conditions, Results were enhanced for different die lengths, extrusion ratios, and two extra teeth number as three and six using FEM simulations. Subsequently, the data from the performed FEM simulations were submitted for the best obtained ANN model. Finally, a good agreement between FE-simulated and ANN-predicted results was obtained. The proposed ANN model is found to be useful in predicting the forming load of the different die set variations based on the reliable test data.
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    Fatigue life modeling of gear like products using ANN
    (Natl Inst Science Communication-Niscair, 2016) Ayer, Onder; Bingol, Sedat; Altinbalik, Tahir; Kilicgedik, Hidir Yanki
    The expected life of a gear is important parameter especially for the gears to secure of the mechanics of it. Related to this importance, fatigue failure is one of the most seen failures occurred on gears working under cyclic loads. It is not possible to eliminate fatigue failure effects but it is possible to reduce by appropriate materials selection and design criteria. Due to demand for gears with higher load-carrying capacity and increased fatigue life, it is important to determine the fatigue strengths of the gears. hi this study, forward extrusion method with cosine and tapered profile dies is carried out to obtain gear-like products. The products are then tested under cyclic loads to determine the fatigue life. The results obtained from the experiments are used as inputs in developing the ANN models. Different ANN models are developed for cosine curved and straight tapered profiles to obtain the best models. A comparative analysis is performed in order to evaluate the accuracy of the developed models, in terms of statistical measurements (R-2, MSE, MAE). Results revealed that proposed ANN models for both cosine curved and tapered profiles are able to predict the fatigue life of the gear-like profiles.
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    Modeling and comparison of failure load with FEM and ANNs
    (Sage Publications Ltd, 2016) Orcen, Gurbet; Bingol, Sedat; Gur, Mustafa
    In this study, failure analysis was researched in woven glass fiber-reinforced epoxy resin composite plates jointed with two parallel pins under the effect of seawater. The effects of immersion time in seawater and changes in joint geometry on first failure loads were experimentally examined. In addition to this, the experimental results were compared with the results of the finite element analysis and artificial neural network modeling. The specimens were immersed in seawater for periods of 0, 3, and 6 months to observe the effects of seawater. For joint geometry, the parameters of the edge distance-to-upper hole diameter (E/D), the two hole-to-hole center diameter (K/D), the distance from the upper or the lower edge of the specimen to the center of the hole-to-hole diameter (M/D), and the width of the specimen-to-hole diameter (W/D) ratios were selected. In the numerical analysis, the finite elements models of the specimens were realized with the ANSYS 11.0 finite elements modeling and the Tsai-Wu failure criteria were used to predict the first failure loads. The comparison made in this study, results of the experimental, the finite element analysis, and artificial neural network modeling were compared and were found to be in good agreement for the first failure load.
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    A novel approach based on grey simplified best–worst method and grey possibility degree for evaluating materials in semiconductor industries
    (Springer Science and Business Media, 2023) Emamat, Mir Seyed Mohammad Mohsen; Wakeel, Saif; Amiri, Maghsoud; Ahmad, Shafi; Bingol, Sedat
    The reliability of flip-chip packages is significantly impacted by the type of packaging materials, such as underfill, solder, flux, and solder mask. Underfill reduces the coefficient of thermal expansion (CTE) mismatch between the semiconductor chip and printed circuit board, thereby minimizing the chances of thermal fatigue failure of the package. There are a plethora of underfill suppliers and selecting the most suitable underfill for preparing a flip-chip package is critical as there are conflicting criteria. These criteria are limited to glass transition temperature (Tg), CTE, elastic modulus (E), coefficient of moisture expansion, fracture toughness (Kic), shear strength, and flowability. Choosing appropriate alternatives based on the above conflicting criteria is basically a multi-criteria problem. This research proposes a grey simplified best–worst method (GSBWM) to identify the criteria weight. The proposed method has less calculation complexity than the previous grey best–worst methods, and it does not need operations research and modeling knowledge, and optimization software to solve it. The accuracy of the GSBWM is investigated using three data sets. The results showed the high accuracy of the proposed method in all data sets. This study employed the combination of GSBWM and a grey possibility degree based method to select the most suitable underfill material for reliable flip-chip packages as a real-world problem.
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    Optimizing Cutting Conditions and Prediction of Surface Roughness in Face Milling of AZ61 Using Regression Analysis and Artificial Neural Network
    (Hindawi Ltd, 2017) Alharthi, Nabeel H.; Bingol, Sedat; Abbas, Adel T.; Ragab, Adham E.; El-Danaf, Ehab A.; Alharbi, Hamad F.
    In this paper artificial neural network (ANN) and regression analysis were used for the prediction of surface roughness. Five models of neural network were developed and the model that showed best fit with experimental results was with 6 neurons in the hidden layer. Regression analysis was also used to build a mathematical model representing the surface roughness as a function of the process parameters. The coefficient of determination was found to be 94.93% and 93.63%, for the best neural network model and regression analysis, respectively, from the comparison of the models with thirteen validation experimental tests. Optical microscopy was conducted on two machined surfaces with two different values of feed rates while maintaining the spindle speed and depth of cut at the same values. Examining the surface topology and surface roughness profile for the two surfaces revealed that higher feed rate results in relatively thick roughness markings that are distantly spaced, whereas low values of feed rate result in thin surface roughness markings that are closely spaced giving better surface finish.
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    Prediction of Cutting Conditions in Turning AZ61 and Parameters Optimization Using Regression Analysis and Artificial Neural Network
    (Hindawi Ltd, 2018) Alharthi, Nabeel H.; Bingol, Sedat; Abbas, Adel T.; Ragab, Adham E.; Aly, Mohamed F.; Alharbi, Hamad F.
    All manufacturing engineers are faced with a lot of difficulties and high expenses associated with grinding processes of AZ61. For that reason, manufacturing engineers waste a lot of time and effort trying to reach the required surface roughness values according to the design drawing during the turning process. In this paper, an artificial neural network (ANN) modeling is used to estimate and optimize the surface roughness (R-a) value in cutting conditions of AZ61 magnesium alloy. A number of ANN models were developed and evaluated to obtain the most successful one. In addition to ANN models, traditional regression analysis was also used to build a mathematical model representing the equation required to obtain the surface roughness. Predictions from the model were examined against experimental data and then compared to the ANN model predictions using different performance criteria such as the mean absolute error, mean square error, and coeffcient of determination.
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    Prediction of the True Stress of ZE20 Magnesium Alloy at Different Temperatures and Strain Rates
    (Assoc Mechanical Engineers Technicians Slovenia, 2015) Bingol, Sedat; Misiolek, Wojciech
    Compression tests were performed to obtain flow stress curves of a newly developed magnesium ZE20 alloy for automobile applications. The experiments were performed in a temperature range from 200 degrees C to 425 degrees C and the strain rates from 0.01 to 15 s-1 to examine the material responses at various processing conditions. Artificial neural network (ANN) and gene expressing programming (GEP) were used for the estimation of the true stress curves obtained from the experimental tests. Recently, a few studies were performed to estimate the true stress of different magnesium alloys by using ANN modelling method. However, this method has not yet been applied for the ZE20 alloy; therefore, it was the subject in this study. Furthermore, this study is the first attempt of using a GEP model to predict the true stress of a magnesium alloy. Both developed ANN and GEP models successfully predicted the true stress of ZE20 alloy.
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    Review-Gate Oxide Thin Films Based on Silicon Carbide
    (Electrochemical Soc Inc, 2022) Odesanya, Kazeem Olabisi; Ahmad, Roslina; Andriyana, Andri; Bingol, Sedat; Wong, Yew Hoong
    A comprehensive review of the features of silicon carbide (SiC) and various methods of deposition of gate oxides are presented in this report. The SiC material, which is mostly employed as base component in metal oxide semiconductor field effect transistors (MOSFETs) is very promising; for its high voltage, high power, high temperature and high breakdown field properties. These features have made it very attractive for use in power electronic devices over its counterparts in the field. Despite these great features, and the significant progress recorded in the past few years regarding the quality of the material, there are still some issues relating to optimization of the surface and interface processing. This review discusses the effect of surface modification and treatment as a means of enhancing the electrical performance of the SiC-based MOSFETs. It also identifies the challenges of controlling the density of dielectric/SiC interface trap that is needed to improve the values of mobility channels, and several oxidation techniques that could be used to surmount the structural limitations presently encountered by the SiO2/SiC system. Reliability as a significant aspect of electronic structures was also discussed with much emphasis on causes of their breakdown and possible solutions, especially in high thermal applications.