نمایش منو
صفحه اصلی
جستجوی پیشرفته
فهرست کتابخانه ها
عنوان
Surrogate SDOF models for probabilistic performance assessment of multistory buildings:
پدید آورنده
Vaseghiamiri, SMahsuli, MGhannad, MAZareian, F
موضوع
رده
کتابخانه
مرکز و کتابخانه مطالعات اسلامی به زبانهای اروپایی
محل استقرار
استان:
قم
ـ شهر:
قم
تماس با کتابخانه :
32910706
-
025
شماره کتابشناسی ملی
شماره
LA40d416m3
عنوان و نام پديدآور
عنوان اصلي
Surrogate SDOF models for probabilistic performance assessment of multistory buildings:
نام عام مواد
[Article]
نام نخستين پديدآور
Vaseghiamiri, SMahsuli, MGhannad, MAZareian, F
عنوان اصلي به قلم نويسنده ديگر
Methodology and application for steel special moment frames
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
© 2020 This paper proposes a methodology for generating surrogate single-degree-of-freedom (SDOF) models that can be utilized to estimate the probability distribution of the roof drift ratio of multistory buildings at various ground motion intensity measures. The use of an SDOF model as a surrogate for multistory buildings can significantly alleviate the high computational cost for probabilistic seismic demand assessment considering both model uncertainty and record-to-record variability. The surrogate SDOF model generated herein explicitly accounts for model uncertainties and can be used as an alternative to the nonlinear dynamic analysis of detailed building structures. Applications for such surrogate models include regional risk and resilience analyses and comprehensive parametric studies. To showcase the proposed methodology, an SDOF surrogate model for steel special moment frame (SMF) buildings is developed using the suggested surrogate SDOF model generating methodology. The properties of the surrogate model representing a multi-degree-of-freedom (MDOF) structure are computed using a probabilistic function of the fundamental period of the structure developed using Bayesian linear regression. To validate the surrogate model for SMFs, the response statistics produced using detailed multistory SMF models are compared with those of the corresponding surrogate SDOF models. The results show that the proposed surrogate SDOF model captures the probability distribution of the roof drift ratio of SMFs up to collapse with acceptable accuracy while reducing the runtime by at least one order of magnitude.
مجموعه
تاريخ نشر
2020
عنوان
UC Irvine
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب
اطلاعات رکورد کتابشناسی
نوع ماده
[Article]
کد کاربرگه
278671
اطلاعات دسترسی رکورد
سطح دسترسي
a
تكميل شده
Y
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