نویسندگان

گروه مهندسی عمران، دانشگاه زابل، زابل

چکیده

‌‌براورد صحیح احتمال خرابی همراه با حجم محاسبات پایین، دغدغه اصلی در قابلیت اعتماد سازه‌ها به‌شمار می‌آید. روش‌ شبیه‌‌سازی مونت‌کارلو، به‌سادگی می‌تواند ‌‌براورد صحیحی از احتمال خرابی ارائه دهد. اما، برای مسائل پیچیده مهندسی با احتمال خرابی پایین زمان‌بر بوده و ممکن است ‌‌براورد ناکارامدی از احتمال خرابی ارائه دهد. در این مقاله، بر اساس یک روش وزنی، کارایی روش شبیه‌سازی ‌‌مونت‌کارلو بهبود بخشیده شده است. بر مبنای یک تابع نمایی، وزن نمونه‌ها به‌صورت تصادفی در فضای طراحی تنظیم شده و داده‌های تنظیم شده تصادفی، برای بهبود روش مونت‌کارلو استفاده شده است. عملکرد همگرایی روش وزنی تصادفی شبیه‌‌سازی مونت‌‌کارلو مانند صحت و میزان ‌‌براورد تابع عملکرد، به‌کمک چندین مثال غیرخطی ریاضی و سازه‌ای با متغیرهای تصادفی نرمال و غیرنرمال با روش شبیه‌‌سازی مونت‌کارلو مقایسه شده است. نتایج حاکی از آن است که روش پیشنهادی، نتایج صحیحی ‌‌براورد کرده و در حدود 100 تا 1000 برابر حجم محاسبات را نسبت به روش ‌‌مونت‌کارلو کاهش داده است.

 

کلیدواژه‌ها

عنوان مقاله [English]

Random - weighted Monte Carlo Simulation Method for Structural Reliability Analysis

نویسندگان [English]

  • S. Saravani
  • B. Keshtegar

چکیده [English]

The computational burdens and more accurate approximations for the estimation of the failure probability are the main concerns in the structural reliability analyses. The Monte Carlo simulation (MCS) method can simply provide an accurate estimation for the failure probability, but it is a time-consuming method for complex reliability engineering problems with a low failure probability and may efficiently approximate the failure probability. In this paper, the efficiency of MCS for the computations of the performance function is improved using a random-weighted method known as the random-weighted MCS (RWMC) method. By using the weighted exponential function, the weights of random data points generated by MCS are  adjusted by selecting the random point in the design space. The convergence performances including the computational burdens for evaluating the limit sate function and the accuracy of failure probabilities of RWMC are compared with MCS by using several nonlinear and complex mathematical and structural problems with normal and no-normal random variables. The results indicate that the proposed RWMC method can estimate the accurate results with the less computational burdens, about 100 to 1000 times faster than MCS
 

کلیدواژه‌ها [English]

  • Monte Carlo simulation
  • Structural reliability analysis
  • Failure possibility
  • Random- weighted Monte Carlo simulation
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