Yazar "Sensoy, Abdullah Tahir" seçeneğine göre listele

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    Determining the optimum model parameters for oligosaccharide production efficiency using response surface integrated particle swarm optimization method: an experimental validation study
    (Taylor & Francis Inc, 2020) Sensoy, Abdullah Tahir; Ispirli, Humeyra; Dertli, Enes
    Glucansucrases (GTFs) catalyzes the synthesis of alpha-glucans from sucrose and oligosaccharides in the presence of an acceptor sugar by transferring glucosyl units to the acceptor molecule with different linkages. The acceptor reactions can be affected by several parameters and this study aimed to determine the optimal reaction parameters for the production of glucansucrase-based oligosaccharides using sucrose and maltose as the donor and acceptor sugars, respectively via a hybrid technique of Response Surface Method (RSM) and Particle Swarm Optimization (PSO). The experimental design was performed using Central Composite Design and the tested parameters were enzyme concentration, acceptor:donor ratio and the reaction period. The optimization studies showed that enzyme concentration was the most effective parameter for the final oligosaccharides yields. The optimal values of the significant parameters determined for enzyme concentration and acceptor:donor ratio were 3.45 U and 0.62, respectively. Even the response surface plots for input parameters verified the PSO results, an experimental validation study was performed for the reverification. The experimental verification results obtained were also consistent with the PSO results. These findings will help our understanding in the role of different parameters for the production of oligosaccharides in the acceptor reactions of GTFs.
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    Development of particle swarm and topology optimization-based modeling for mandibular distractor plates
    (Elsevier, 2020) Sensoy, Abdullah Tahir; Kaymaz, Irfan; Ertas, Umit
    Mandibular Distraction Osteogenesis (MDO) is a common clinical procedure to correct mandibular retrognathia. However, since there is not a gold standard for determining the screw positions for current MDO operations, deviation of distraction direction and malocclusion increases. This case results in need of additional operations that affect the callus stability. In these cases, relapse risk increases and remodelling period gets longer. On the other hand, large volume of the distractor plates results in more invasive treatment and negatively affects the patients' comfort. To overcome these problems, this study offers a new method including; virtual surgery simulation, determining the optimum screw configuration using particle swarm optimization loop linked between MATLAB-PYTHON-ANSYS programs and the design of distractor plate geometry with topology optimization. In order to test the proposed method, two different Finite Element (FE) models, CM and OM, were established based on conventional and optimum method, respectively. FEA results of the current study reveals that OM has 33.56% less displacement compared to CM, and the most critical screw in terms of screw loosening for OM has 35.29% less strain value than CM. These outcomes show OM shows superior callus stability in comparison with CM. On the other hand, redesign of the distractor plates using topology optimization according to the best screw positions provides 43.32% reduction in the total implant volume which means reduced cost and a less invasive MDO operation. Therefore, the clinical use of this protocol is expected to increase the success of the operation by shortening the recovery period.
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    Investigating the Optimum Model Parameters for Casting Process of A356 Alloy: A Cross-validation Using Response Surface Method and Particle Swarm Optimization
    (Springer Heidelberg, 2020) Sensoy, Abdullah Tahir; Colak, Murat; Kaymaz, Irfan; Dispinar, Derya
    This study aimed to determine the optimal casting parameters for the maximum fluidity of A356 alloy. Gravity die cast method was used. For this purpose, central composite design (CCD) was performed. The input parameters and their limits for the trial design were selected as pre-heating temperature (100-400 degrees C), casting temperature (680-760 degrees C), and cross-sectional thickness (1-10 mm). Using the CCD-based simulation results of the feed distance, a highly correlated full-quadratic regression equation was obtained with the highestR(2)(0.99), which then was used as the objective function for the particle swarm optimization (PSO) process. The highest value of the response parameter, flow distance, reached up to 491.19 mm when the input parameters were selected as 400 degrees C, 760 degrees C and 10 mm, respectively. The sensitivity analysis has shown that the most effective parameter on the fluidity is the cross-sectional thickness. The response surface method (RSM)-based optimization results have been also validated using the PSO method. Although the higher temperatures have been found to result in better fluidity, there may be some drawbacks to working at higher temperatures such as energy cost and mould life. To determine the optimum input parameters, the RSM model suggested in this study can be modified for any type of casting process. Moreover, especially for a complex-shaped part, the manufacturer can be advised regarding operating conditions such as pre-heating and casting temperatures.
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    Optimal Material Selection for Total Hip Implant: A Finite Element Case Study
    (Springer Heidelberg, 2019) Sensoy, Abdullah Tahir; Colak, Murat; Kaymaz, Irfan; Findik, Fehim
    The selection of most proper materials in engineering design is known as an important stage of the design process. In order to successfully complete this stage, it is necessary to have sufficient knowledge about the structure of materials, density, melting point, thermal expansion coefficient, tensile and yield strength, elongation, modulus of elasticity, hardness and many other properties. There are several selection systems that help the design engineer to choose most suitable material that meet the required properties. In the field of bioengineering, the selection of materials and the development of new materials for the clinical needs are increasingly important. In this study, the cases of optimal implant stabilization were investigated, material alternatives for hip prosthesis were evaluated, and optimal materials were determined. Using computerized tomography data with MIMICS software, virtual surgery was applied the hip bone and the implant was attached to bone. Boundary conditions and material properties have been defined, and finite element model has been created. FEA investigation of the mechanical behavior of the hip implant for various material alternatives determined by the CES software showed that the best material candidate is austenitic, annealed and biodurable stainless steel in terms of the micromotions at the implant-bone cement interface regarding osseointegration. This candidate showed 20.69% less strain value than the most commercially used hip implant material, Ti6Al4V. Therefore, the findings of this study suggest that the use of some specific stainless steel materials for implants may reduce the operation cost and increase the operation success for the total hip arthroplasty.