28 شهریور 1400

محسن عباسی

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی نفت، گاز و پتروشیمی - گروه مهندسی شیمی
تحصیلات: دکترای تخصصی / مهندسی شیمی
تلفن: 07731221495
دانشکده: دانشکده مهندسی نفت، گاز و پتروشیمی

مشخصات پژوهش

عنوان
تحلیل غیرخطی نوسانگر موج ارشمیدس
نوع پژوهش پارسا
کلیدواژه‌ها
Renewable energy, Sea wave energy, Nonlinear analysis, Archimedes wave swing
پژوهشگران عقیل اندخش (دانشجو) ، روح اله فاتحی (استاد راهنما) ، محسن عباسی (استاد راهنما) ، پرویز ملک زاده (استاد مشاور)

چکیده

In this thesis, the nonlinear behavior of the Archimedes Wave Swing (AWS) has been studied and analyzed. The AWS is one of the methods for sea wave transformation. The apparatus under study is fully submerged in sea water and transforms the cyclic movement of the waves into electric energy by the linear generator which is located inside the apparatus. In this investigation, the swinging movement of the AWS under various loads, which some of them have nonlinear behaviors, has been studied. The procedure of this thesis has been explained in the following. First, by applying the forces on the AWS, its equation of motion in a linear and a nonlinear model has been derived. Then, due to the absence of analytical solution for the respective nonlinear equation, the approximate analytical methods of standard perturbation, homotopy perturbation, multiple scale perturbation, and variational iteration have been used to solve it. After that, in order to examine the accuracy of these methods, the respective equation has been solved in Matlab software using the Runge-Kutta method. Also, the utilized methods have been validated and the convergence of the perturbation series has been discussed. After validating the methods, the effects of the changes of the parameters and the effective forces on the AWS equations on its behaviors have been studied. Since the amount of the output power in the power transitions systems is important, in the following, the resultant power output from the AWS generator in a linear and a nonlinear model will be discussed. Further, the power has been numerically calculated and reported to validate the theoretical relations for power. Moreover, the effects of the important parameters of the problem on power have been analyzed by illustrating respective diagrams. Finally, the mean power of the AWS has been optimized based on the intended model using the Particle Swarm Optimization (PSO) method. Based on some assumptions, the optimum values of the physical ch