تخمین قابلیت اطمینان فروریزش سازه با استفاده از روش سطح پاسخ و هیبرید شبکه‌های عصبی- فازی با الگوریتم‌های فرا‌ابتکاری

نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 دانشکده مهندسی عمران، واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران

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

چکیده

به­ دلیل اهمیت اثرات فروریزش، تمرکز اصلی این تحقیق بر تخمین قابلیت اطمینان فروریزش در سازه­ های پیچیده است که فرم صریح تابع شرایط حدی برای آن­ها وجود ندارد، در این تحقیق، پارامترهای مربوط به منحنی ممان- چرخش اصلاح‌شده ایبارا (Ibarra)، مدینا (Medina) و کراوینکلر (Krawinkler) مربوط به مفاصل پلاستیک متمرکز در تیرها و ستون ها در سازه­ های قاب خمشی به ­عنوان عدم قطعیت ­های شناختی در نظر گرفته شده است. با توجه به عدم وجود تابع حالت حدی صریح در تعیین قابلیت اطمینان فروریزش سازه، ابتدا با استفاده از روش­ های شبیه ­سازی، 105 نمونه بر مبنای مشخصات آماری و توزیع احتمالاتی عدم قطعیت­ ها با در نظرگرفتن همبستگی بین آن­ها، تولید می ­شود و با لحاظ کردن 44 شتاب‌نگاشت و استفاده از تحلیل­ های دینامیکی افزایشی (IDA) پاسخ فروریزش سازه برای نمونه­ های تولیدی به­ دست می­ آید و تابع حالت حدی ضمنی برای سازه ایجاد می ­شود. برای تولید تابع حالت حدی صریح از روش سطح پاسخ استفاده شده و سپس با به­ کارگیری روش ­های مرتبه اول، مرتبه دوم قابلیت اطمینان و روش مونت کارلو (Monte Carlo)، قابلیت اطمینان فروریزش سازه تخمین­ زده می­ شود. در مرحله بعد با استفاده از تابع حالت حدی ضمنی تولید شده، با به‌کارگیری شبکه ­های عصبی- فازی هیبرید شده با الگوریتم­ های فراابتکاری در ترکیب با روش مونت کارلو قابلیت اطمینان فروریزش سازه تخمین زده می ­شود. نتایج نشان می­ دهند که با استفاده از روش سطح پاسخ و هیبرید شبکه­ های عصبی- فازی با الگوریتم­ های فراابتکاری می­توان قابلیت اطمینان فروریزش سازه را با خطای ناچیز و دقت قابل‌قبول تخمین زد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Estimation of Structural Collapse Reliability via Response Surface Method and a Hybrid of Neuro-Fuzzy Networks with Meta-heuristic Algorithms

نویسندگان [English]

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

Earthquakes are catastrophic natural phenomena that occasionally lead to the collapse of structures. Considering the importance of collapse impacts, the present study primarily focuses on estimating the reliability of collapse probability for complicated structures for which no explicit limit state functions exist. Different simulation methods are used for combining uncertainties, including the Monte Carlo, Latin Hypercube Sampling, and the importance of sampling approaches. Simulation methods require several samples to cover the probabilistic distribution of uncertainties. To deal with this problem, the response surface method (RSM) and artificial neural networks (ANNs) integrated with the simulation method have been proposed for reducing the computation effort (Beheshti-Aval et al., 2015; Khojastehfar et al., 2015). Common methods applied to evaluate reliability include 1) reliability-based methods, involving the first-order reliability method (FORM) and second-order reliability method (SORM) and 2) Monte Carlo simulation methods (Nowak and Collins, 2000).

کلیدواژه‌ها [English]

  • Collapse reliability
  • Explicit limit state function
  • Implicit limit state function
  • Response surface method
  • Neuro-fuzzy network
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