Yazar "Sezgen, Hasmet Cagri" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    A Novel Design of Interval Type-2 Neuro-Fuzzy Controller for Flexible Structure
    (Kaunas Univ Technol, 2021) Tinkir, Mustafa; Kalyoncu, Mete; Sezgen, Hasmet Cagri
    The aim of this research is to develop a novel design of interval type-2 neuro-fuzzy (IT2NF) controller for active vibration control of a flexible structure during an earthquake. For this purpose, two adaptive neural network based fuzzy logic controllers are designed and combined to create the novel design of an IT2NF controller to reduce the vibrations of two-storey flexible building model that occur during earthquake disturbance effects. Accordingly, dynamic modeling of a flexible structure is realized and simulated using the MATLAB / SimMechanics. Then, an experimental setup consisting of two-storey flexible structure, active mass damper (AMD) and shaker is established. Additionally, IT2NF controller is implemented in simulation and experimental models, and the effectiveness and performance of the IT2NF controller are tested under the scaled Northridge Earthquake acceleration. The obtained simulations and experimental responses are evaluated in terms of cart displacements, deflections, and accelerations of the flexible floors showing a good agreement between the simulations and the experimental results. The results show that the designed novel IT2NF controller reduced the total deflections of first and second floor by 72.3% and 68.7%, respectively, when compared with the uncontrolled system. Additionally, it is also found that the designed IT2NF controller is able to reduce the accelerations of the first and second floor by 64.8% and 54.6%, respectively. The proposed and designed control method reported in this study can be employed as an active vibration controller for multi-degree of freedom of flexible systems under the disturbances such as earthquake excitations.
  • Küçük Resim Yok
    Öğe
    Optimization of torsional vibration damper of cranktrain system using a hybrid damping approach
    (Elsevier - Division Reed Elsevier India Pvt Ltd, 2021) Sezgen, Hasmet Cagri; Tinkir, Mustafa
    The focus of this research is to develop the optimum design of torsional vibration damper using hybrid damping approach to decrease the torsional vibrations in the cranktrain system of internal combustion engines (ICE). For this purpose, a double mass rubber and viscous torsional vibration damper (DMRVTVD) are combined. The optimization procedure is carried out using genetic algorithm (GA) to determine the best hybrid damping performance on cranktrain system of a four stroke and four cylinder diesel engine. Accordingly, twelve degrees of freedom lumped mass mathematical model of the proposed crank train system is created. The stiffness and damping coefficients of viscous and rubber materials used in DMRV-TVD model are verified by modal test and finite element natural frequency analysis. Then, the excitation torque is calculated considering the inertia forces and gas force, and Fourier series expansion is performed to obtain the harmonics of driven torque as the input load on the relevant masses. The relative angular deflection of the front end point of the crankshaft is determined. Additionally, in order to decrease the torsional vibrations of the crankshaft, DMRV-TVD model is optimized depending on the viscous material parameters by defining the boundary conditions and objective function of the genetic algorithm. The comparative results show that the developed hybrid design of optimized DMRV-TVD reduced the torsional vibrations by 50.17% when compared to the non-optimized DMRV-TVD. This achieved reduction in the torsional vibrations is expected to increase the engine performance and its durability as well as providing a better driving comfort and fuel efficiency. (C) 2021 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).