Application of Elasto-HydroDynamic (EHD) Model to Predict Erosive Wear Failure in Conrod Bearing
محل انتشار: مجله علم مهندسی خودرو، دوره: 11، شماره: 1
سال انتشار: 1399
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 43
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJAEIU-11-1_003
تاریخ نمایه سازی: 4 دی 1402
چکیده مقاله:
Erosive wear damage is common damage in the bearing shell of engines which causes a change in bearing profile and affects the oil film pressure and durability of bearing shell. The objective of the present paper is to present an appropriate algorithm for prediction and failure analysis of wear in BE bearing of engines using the Elasto-HydroDynamic (EHD) model. The mentioned model incorporating a mass-conserving algorithm is utilized to compute the lubrication characteristics of bearing, such as minimum oil film thickness and maximum oil film pressure. In EHD analysis, bearing housing is modeled by the finite element method to consider the bearing deformation. To estimate the wear volume, a code was written in MATLABÒ software which modifies the bearing profile and surface roughness during the analysis. A modified Archard model is used to model the lubricated sliding wear of rough contacting surface. Change in bearing surface roughness due to wear is modeled by the Abbot curve. Finally wear damage progression of BE bearing during engine operation is calculated and the results are thoroughly discussed. The numerical simulation results confirm that the wear rate at the initial stage of engine running is significant. It is concluded that wear adapts the bearing geometry in proper condition and improves the contact problem at the edges of bearing.
کلیدواژه ها:
نویسندگان
Hadiseh karimaei
Aerospace Research Institute, Ministry of Science, Research and Technology
Hamidreza Chamani
Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله 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 مقاله لینک شده اند :