تخمین پاسخ‌های فروریزش سازه با در نظر گرفتن عدم قطعیت‌های مدل‌سازی با استفاده از روش سطح پاسخ و شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی عمران، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران

2 گروه سازه و زلزله، دانشکده مهندسی عمران، واحد نجف آباد، دانشگاه آزاد اسلامی، نجف آباد، ایران

3 دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

در این تحقیق ارزیابی پاسخ­‌های فروریزش یک سازه قاب خمشی بتنی با در نظر گرفتن عدم قطعیت­‌های مدل‌سازی مورد بررسی قرار گرفته است. عدم قطعیت‌­های مدل‌سازی برای ارزیابی پاسخ فروریزش، پارامترهای مربوط به منحنی ممان- چرخش اصلاح شده ایبارا-کراوینکر در تیرها و ستون های سازه می­‌باشد. برای آنالیز عدم قطعیت، همبستگی بین پارامترهای مدل در یک جز و بین پارامترهای دو جز سازه­ای در نظر گرفته شده است. برای تولید متغیرهای تصادفی مستقل از روش LHS و از تجزیه چولسکی برای ایجاد متغیرهای تصادفی وابسته استفاده شده است. با تولید 281 شبیه سازی برای عدم قطعیت‌­ها با در نظر داشتن همبستگی بین آن­ها، آنالیزهای دینامیکی افزایشی با 44 شتاب‌نگاشت دور از گسل انجام شده است. پاسخ­‌های فروریزش برای هر شبیه­‌سازی شامل میانگین ظرفیت فروریزش، میانگین دریفت فروریزش و میانگین بسامد سالیانه فروریزش به‌ دست آمده و سپس با استفاده از روش سطح پاسخ و شبکه‌­های عصبی پاسخ­‌های فروریزش پیش‌­بینی شده است. نتایج نشان می­‌دهند که مقادیر ضریب همبستگی بین داده‌­های هدف حاصل از تحلیل­‌های دینامیکی افزایشی و داده­ه‌ای خروجی حاصل از پیش­‌بینی، به روش سطح پاسخ و شبکه عصبی مصنوعی برای پاسخ‌­های فروریزش بالای0/98 به‌ دست آمده است و حداکثر خطای پیش‌بینی برای میانگین ظرفیت فروریزش و میانگین دریفت فروریزش کمتر از 5% و برای میانگین بسامد سالیانه سالیانه فروریزش کمتر از 10% در روش سطح پاسخ و شبکه عصبی مصنوعی می‌­باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Estimating Structural Collapse Responses Considering Modeling Uncertainties using Artificial Neural Networks and Response Surface Method

نویسندگان [English]

  • Mohammad Amin Bayari 1
  • Esmaeel Izadi Zaman Abadi 2
  • Naser Shabakhty 3
1 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
3 School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
چکیده [English]

This research investigates the collapse responses of a concrete moment frame considering modeling uncertainties. These modeling uncertainties are considered for evaluating a collapse response related to the modified Ibarra-Krawinkler moment-rotation parameters for beam and column elements of a given structure. To analyze these uncertainties, the correlations between the model parameters in one component and between two structural components were considered. Latin Hypercube Sampling (LHS) method was employed to produce independent random variables. Moreover, Cholesky decomposition was adopted to produce correlated random variables. Performing 281 simulations for the uncertainties involved considering their inter-correlations, incremental dynamic analysis (IDA) was done using 44 far-field accelerograms to determine structural collapse responses. Collapse responses of each simulation, including mean collapse capacity, mean collapse drift and mean annual frequency, were obtained. Then, the collapse responses were predicted using the response surface method and artificial neural network. The results show that the Correlation coefficients (R) between the target data resulted from incremental dynamic analysis (IDA), output data resulted from response surface method (RSM), and artificial neural network (ANN) were obtained for the collapse responses above 0.98. The maximum prediction errors for mean collapse capacity and mean collapse drift are less than 5% and for mean annual frequency less than 10% under the response surface method (RSM) and artificial neural network (ANN).

کلیدواژه‌ها [English]

  • Uncertainty analysis
  • Incremental dynamic analysis
  • Structural Collapse Responses
  • Response Surface Method
  • Artificial Neural Network
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