Optimization for friction damped post-tensioned steel frame based on simplified FE model and GA

التفاصيل البيبلوغرافية
العنوان: Optimization for friction damped post-tensioned steel frame based on simplified FE model and GA
المؤلفون: Yuan Ye, Liu Haiqing, Zhao Zhongwei, Jian Xiangyang
المصدر: Earthquake Engineering and Engineering Vibration. 21:209-219
بيانات النشر: Springer Science and Business Media LLC, 2021.
سنة النشر: 2021
مصطلحات موضوعية: Materials science, business.industry, Mechanical Engineering, Frame (networking), Connection (vector bundle), Foundation (engineering), Building and Construction, Structural engineering, Geotechnical Engineering and Engineering Geology, Finite element method, Steel frame, Genetic algorithm, Optimal combination, Fe model, business, Civil and Structural Engineering
الوصف: The post-tensioned (PT) energy-dissipating connection for steel frames has drawn the attention of many researchers for its good seismic performance. Friction mechanisms, such as friction damped PT steel connections, are the approaches typically used to improve energy-dissipating capacity. The mechanical behavior of PT connections has been extensively investigated. The seismic performance of PT frames should be optimized by employing a suitable design of a friction device. In this study, the influence of fmax the seismic behavior of a PT frame is investigated. The max static frictional force fmax is optimized based on a genetic algorithm (GA). Results indicate that the reasonable distribution of fmax can evidently improve seismic performance. Consequently, the GA method can be effectively utilized for seeking the optimal combination of fmax if the simplified finite element model is adopted. Results derived will provide a foundation for analysis and design of PT frame structures.
تدمد: 1993-503X
1671-3664
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::bc653a52e50471d40d1bbc8e823514ec
https://doi.org/10.1007/s11803-021-2070-3
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........bc653a52e50471d40d1bbc8e823514ec
قاعدة البيانات: OpenAIRE