14 آذر 1403
محمدرضا گل بهار حقيقي

محمدرضا گل بهار حقیقی

مرتبه علمی: دانشیار
نشانی: دانشکده مهندسی - گروه مهندسی مکانیک
تحصیلات: دکترای تخصصی / مهندسی مکانیک
تلفن: -
دانشکده: دانشکده مهندسی

مشخصات پژوهش

عنوان
ارزیابی عمر خستگی مواد تحت بارگذاری تک محوری تصادفی با استفاده از روشهای تنش پایه در صفحه بحرانی
نوع پژوهش پارسا
کلیدواژه‌ها
Fatigue life; Fatigue failure; Uniaxial random loading; Stress-based criterion; Critical plane
پژوهشگران فریبا کازرونی (دانشجو) ، محمدرضا گل بهار حقیقی (استاد راهنما) ، غلام رضا احمد زاده ریشهری (استاد مشاور)

چکیده

In this thesis, fatigue life undergoing constant amplitude and uniaxial random loading conditions is evaluated using stress-based damage models and available stress-strain laboratory data. For this study, data from fatigue tests of steel samples under uniaxial loading were used. These data are in form of stress data, strain range and fatigue life. Various methods and criterions are used to estimate the fatigue and results are presented in logarithmic graphs. By comparing the estimated fatigue life against the experimental results, the capability of each estimation method and criteria is examined and evaluated. These criteria vary in the critical plane orientations and material constants and relate fatigue fracture to three different combinations of stresses in critical plane. In the first category, fatigue life is estimated in terms of the linear combination of shear and normal stresses acting on the critical plane. The second group includes the linear combination of shear parameter with hydrostatic stress. And, the third group offers nonlinear combination of shear and normal stresses acting on the critical plane. For random loading conditions, the rainflow cycle counting technique is applied to determine the number of cycles over block loading histories. Finally, the technical equations of two of the existing criterions were modified, and the new estimation results were compared with the previous ones. The results showed that the modified McDermid model and Macha model have the best results.