Vibration Analysis of the Sandwich Beam with Electro-Rheological Fluid Core Embedded Within Two FG Nanocomposite Faces Resting on Pasternak Foundation
Publish place: Journal of Solid Mechanics، Vol: 12، Issue: 4
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 159
This Paper With 15 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JSMA-12-4_001
تاریخ نمایه سازی: 18 اردیبهشت 1400
Abstract:
This investigation deals with the vibration analysis of the sandwich beam with electro-rheological (ER) core embedded within two functionally graded (FG) carbon nanotubes (CNTs) reinforced composite (FG-CNTRC) layers. In this regard, the governing equations are extracted by the Hamilton principle and the rule of mixture is employed to calculate the effective mechanical and physical properties of the CNTRCs face-sheets. Don and Yalcintas shear modulus models are applied to simulate shear modules of the ER core of the beam. The elastic medium is simulated by Winkler-Pasternak model and then, the governing equations are analytically solved. Finally, a parametric study is carried out in details and the effects of some main designing parameters such as applied voltage, Winkler coefficient, Pasternak coefficient, core to face-sheets thickness ratios and the different pattern of the CNTs along the face-sheets and loss factors are examined on the natural frequency. Based on the obtained results, volume fraction of CNTs in face-sheets have significant influence on the natural frequency in which by increasing the volume fractions the flexural rigidity of the sandwich beam increases as well as natural frequency.
Keywords:
Authors
A.H Ghorbanpour-Arani
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
A Rastgoo
School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :