چکیده مقاله
The structural damping ratio, a measure of energy dissipation in structures subjected to dynamic loads, is a key factor in building seismic design and assessment Despite its significance in seismic design and evaluation, it is commonly approached as an estimated value during the design process or handled as a flexible parameter depending on the structural type, as indicated in seismic design codes This study determines the system equivalent damping ratio by equating the total dissipated energy, including hysteretic and elastic strain energies, by summating the energy dissipated in individual members This calculation employs Jacobsen's approach, which provides a systematic framework for energy equivalence in dynamic systems For this purpose, several tree ensemble based machine learning algorithms estimate the members' hysteretic and strain energies and evaluate them using various statistical metrics The PEER dataset, consisting of experimental results from 353 rectangular reinforced concrete columns, is the basis for training and evaluating the models The findings demonstrate 96% and 92% accuracy for predicting elastic strain energy and hysteretic energy, respectively, based on the R² metric achieved by the XGBoost algorithm
کلیدواژهها
نویسندگان
Zohreh Jabari Salmi
Ph D , Department of Civil Engineering, Semnan University, Semnan, Iran
فرهاد بهنام فر
Professor, Department of Civil Engineering, Isfahan University of Technology, Isfahan ۸۴۱۵۶۸۳۱۱۱, Iran
شیوه ارجاع
Jabari Salmi, Zohreh and Behnamfar, Farhad,1404,An Efficient Machine Learning Method for Estimating the Damping Ratio of RC Moment-Resisting Frames,14th International Congress on Civil Engineering,Tehran
ارائهشده در
مجموعه مقالات چهاردهمین کنگره بین المللی مهندسی عمران29 مهر 1404 · تهران