02 آذر 1403
پرويز ملك زاده

پرویز ملک زاده

مرتبه علمی: استاد
نشانی: دانشکده مهندسی - گروه مهندسی مکانیک
تحصیلات: دکترای تخصصی / مهندسی مکانیک
تلفن: 077-31222166
دانشکده: دانشکده مهندسی

مشخصات پژوهش

عنوان
تخمین نیروی اعمالی برمیکرو تیر هدفمند مدرج با استفاده از حل معکوس بر اساس تئوری تنش کوپل اصلاح شده
نوع پژوهش پارسا
کلیدواژه‌ها
Inverse solution, Functionally graded micro-beam, Conjugated Gradient method, Finite element method, Modified couple stress theory.
پژوهشگران امین حسینی (دانشجو) ، محمدرضا گل بهار حقیقی (استاد راهنما) ، عباس بهزاد بهبهانی (استاد راهنما) ، پرویز ملک زاده (استاد مشاور)

چکیده

The estimation of applied dynamic loads on the functionally graded micro-beam under different boundary conditions have been studied. The transverse displacements of functionally graded micro-beam which is obtained under dynamic distributed load and different boundary conditions based on modified couple stress theory, is used as input data for the inverse solution. It is assumed that the material properties are graded and changed along thickness according to rule of mixture law. Governing equations are derived based on Euler- Bernoulli beam theory. Spatial and time discretization of governing equations is done by finite element and Newmark method, respectively. To prove efficiency of these methods which are used and results is validated by comparison with analytical solution and convergence states of results are studied. In the inverse algorithm, the input information displacements caused by mechanical loads that the can be achieved in practical problems using sensors and theoretical problems by simulation method and using direct problem solving. In this study, due to the lack of access to experimental information, solution of equations governing the direct problem is used to simulate this information. For solving the inverse problem, conjugated gradient method and adjoining equation is hired which is one of the most stable method. This method is not sensitive to measurement error and the result of this thesis obviously shows this fact.