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Roudak, Mohammad, Farahani, Melika, Badiezadeh, Sepideh, Amiri Beirami, Mobina, Kiashemshaki, Sheida, Karamloo, Mohammad. (1404). A novel and efficient simulation method of structural reliability for Gaussian distributed variables by the introduction of a truncated probability density function. , (), -. doi: 10.22059/ceij.2025.392268.2275
Mohammad Amin Roudak; Melika Farahani; Sepideh Badiezadeh; Mobina Amiri Beirami; Sheida Kiashemshaki; Mohammad Karamloo. "A novel and efficient simulation method of structural reliability for Gaussian distributed variables by the introduction of a truncated probability density function". , , , 1404, -. doi: 10.22059/ceij.2025.392268.2275
Roudak, Mohammad, Farahani, Melika, Badiezadeh, Sepideh, Amiri Beirami, Mobina, Kiashemshaki, Sheida, Karamloo, Mohammad. (1404). 'A novel and efficient simulation method of structural reliability for Gaussian distributed variables by the introduction of a truncated probability density function', , (), pp. -. doi: 10.22059/ceij.2025.392268.2275
Roudak, Mohammad, Farahani, Melika, Badiezadeh, Sepideh, Amiri Beirami, Mobina, Kiashemshaki, Sheida, Karamloo, Mohammad. A novel and efficient simulation method of structural reliability for Gaussian distributed variables by the introduction of a truncated probability density function. , 1404; (): -. doi: 10.22059/ceij.2025.392268.2275

A novel and efficient simulation method of structural reliability for Gaussian distributed variables by the introduction of a truncated probability density function

Civil Engineering Infrastructures Journal
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 13 آبان 1404    اصل مقاله (1.81 M)
شناسه دیجیتال (DOI): 10.22059/ceij.2025.392268.2275
نویسندگان
Mohammad Amin Roudak* 1؛ Melika Farahani2؛ Sepideh Badiezadeh2؛ Mobina Amiri Beirami2؛ Sheida Kiashemshaki2؛ Mohammad Karamloo3
1Department of Civil Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.
2Department of Civil Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran
3Department of Civil Engineering, Shahid Rajaee Teacher Training University, Lavizan, Tehran, Iran
چکیده
In structural reliability analysis, finding an effective way to estimate the probability of failure of structures, is one of the most fundamental challenges. Monte Carlo simulation is recognized as a common method for computing the probability of failure among the various existing approaches. However, its inefficiency is still a significant drawback. Since a large number of samples is required to estimate the probability of failure accurately, the Monte Carlo simulation is a time-consuming process. In this paper, a new method is proposed to improve the efficiency of the Monte Carlo simulation. This is carried out by reducing the number of required samples. The basic concept of the presented method is to generate a smaller number of samples, mostly concentrated on the failure region. To accomplish this goal, a specific distance from the mean of the variables is eliminated from the sample generation space. In fact, the samples are generated based on a truncated joint probability density function. This leads to a significant reduction in the number of generated samples, enhancing the efficiency of the estimation. The accuracy and efficiency of the presented method are validated using various examples.
کلیدواژه‌ها
Monte Carlo simulation؛ Probability of failure؛ Truncated joint probability density function؛ Sampling approach
آمار
تعداد مشاهده مقاله: 110
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