کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5469178 1519227 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Investigation of forming parameters on springback for ultra high strength steel considering Young's modulus variation in cold roll forming
ترجمه فارسی عنوان
بررسی پارامترهای تشکیل دهنده بر روی توربین بادی برای فولاد فوق العاده با استحکام بالا با توجه به تغییرات مدول یانگ در تشکیل رول سرد
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
چکیده انگلیسی
Ultra High-Strength steels (UHSS) is increasingly used in automotive industry to reduce weight and improve consumers' safety. However, prediction of springback in cold roll forming is one of the crucial problems to be solved for ensuring dimensional tolerances. The variation of Young's modulus is a significant challenge to accurate springback prediction. In this work, two mechanically-measured tests, such as uniaxial and loading unloading loading cycle test, were performed to determine the Young's modulus variation with the increase of plastic strain. One mathematical model that considers Young's modulus variation was proposed and applied in 3D Finite Element Analyses (FEA) to simulate the cold roll forming process. Roll forming tests of hat-shaped section and the relational springback analyses were implemented to compare with FEA simulation results. The calculated accuracy of springback used nonlinear elastic modulus considerably improved by 18% to Swift's material model. The springback prediction was significantly improved if the Young's modulus variation was taken into the FEA simulations. The developed model is applied for comparing the effects of different forming parameters on the product springback, showing that springback increases with increasing flange width, sidewall height, roll gap and the distance, decreases with increasing the strip thickness and the web width. The findings are hoped to help roll forming designers predict springback tendency before the roller design is applied in practical production.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Manufacturing Processes - Volume 29, October 2017, Pages 289-297
نویسندگان
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