روش پیشنهادی نوین و کم‌هزینه در محاسبه احتمال خرابی مسائل مبتنی بر روش مونت کارلو

نوع مقاله : مقاله عمران

نویسندگان

1 گروه مهندسی عمران، دانشگاه سیستان و بلوچستان، زاهدان، ایران

2 دانشگاه سیستان و بلوچستان

چکیده

در سال‌های اخیر ارزیابی قابلیت اطمینان سازه‌ها از جمله مباحث رو به گسترش و نیز مورد توجه پژوهشگران سازه بوده است. در این شاخه از مهندسی عمران، برآورد احتمال خرابی سازه با درنظرگرفتن عدم قطعیت‌های احتمالی درپارامترهای مقاومت و بار در فرآیند مدل‌سازی و طراحی سازه‌ها مورد بررسی قرار می‌گیرد. به شکل معمول، ارزیابی دقیق احتمال خرابی توسط روش شبیه‌سازی مونت کارلو انجام می‌پذیرد که مستلزم انجام مدل‌سازی و هزینه زیاد جهت شبیه‌سازی و متعاقباً برآورد احتمال خرابی سازه مورد بررسی است. در مقاله حاضر بر مبنای روش شبیه‌سازی مونت کارلو، روشی موثر ارائه شده است که دفعات انجام مدل‌سازی سازه جهت برآرود احتمال خرابی را به شکل مطلوبی کاهش داده است. در این روش از مفهوم حداقل فاصله ناحیه خرابی از مبدا، در روش FORM به عنوان معیاری برای تشخیص سلامت نمونه‌ها استفاده شده است. سپس با ارائه زیربازه‌هایی در لایه‌های مختلف جهت گروه‌بندی نمونه‌های تولید شده در روش مونت کارلو، امکان کاهش دفعات مدل‌سازی با کنترل خطای احتمالی و دقتی مناسب فراهم آورده شده است. به منظور بررسی کارایی و توانمندی روش پیشنهادی، مثال‌های عددی و مهندسی با توابع حالت حدی پیچیده توسط روش پیشنهادی مورد بررسی قرار گرفته و نتایج حاصله با روش‌های متداول قابلیت-اطمینان مقایسه گردیده‌اند. نتایج بیانگر دقت بالای روش پیشنهادی علی‌رغم کاهش زیاد دفعات مدل‌سازی سازه نسبت به شبیه‌سازی مونت کارلو می‌باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A new and low cost proposed method for failure probability estimation based on Monte Carlo simulation

نویسندگان [English]

  • Hamed Ghohani Arab 1
  • Mohammad Reza Ghasemi 2
1 civil engineering department, university of sistan and baluchestan, Zahedan Iran
2
چکیده [English]

In recent years, evaluation of reliability analysis of structures has become a straightforward and interesting topic among structural researchers. In the field of civil engineering, estimation of structural failure probability is highly investigated, considering probabilistic uncertainties of resistance and load parameters during modeling and designing of structures. To obtain an accurate failure probability, researchers often perform Monte Carlo simulation (MCS) that requires numerous modeling and cost. In the present study, based on MCS, an enhanced technique is developed that efficiently reduces number of structural modeling. The approach works by employing the concept of First Order Reliability Methods (FORMs) to determine closest point to the mean of random variables in failure region. Afterward, by presenting sub-intervals in various layers, to group generated samples in MCS, the possibility of reducing number of structural modeling with well-disciplined error and acceptable accuracy is achieved. In order to investigate the efficiency and robustness of the method, various numerical and engineering examples with complex limit state functions were attempted and the obtained results were compared with those based on the conventional reliability methods in the literature. Results show the high accuracy of proposed approach while the number of requires structural modeling were substantially reduced.

کلیدواژه‌ها [English]

  • failure probability
  • Limit state function
  • Monte Carlo method
  • Sample elimination
  • Sub-interval
  • FORM method
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