基于蒙特卡罗模拟的维纳过程首次超越失效概率分析
CSTR:
作者:
作者单位:

长沙理工大学 土木工程学院,湖南 长沙 410114

作者简介:

张振浩(1980—),男,教授,从事结构动力可靠度理论及其应用研究。

通讯作者:

中图分类号:

TU528

基金项目:


Analysis of the first -passage failure probability of the Wiener process based on Monte Carlo simulation
Author:
Affiliation:

Changsha University of Science and Technology, School of Civil Engineering, Changsha 410114 , Hunan, China

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    首次超越可靠性分析是结构动力可靠性分析的重要方面。文章针对维纳过程,基于蒙特卡罗模拟法进行了维纳过程首次超越安全界限问题的研究,阐述了维纳过程仿真思路与步骤,选用生成随机数的直接法在 MATLAB 中实现维纳过程的模拟。然后,以混凝土耐久性退化符合维纳过程为例,基于蒙特卡罗模拟法计算首超失效概率,将其计算结果与数学解析法计算结果进行对比。结果表明:蒙特卡罗模拟法的计算精度和解析解非常接近, 且在应用范围和计算便捷性上更具优势。本研究可为相关领域应用维纳过程计算首超失效概率提供数值解法。

    Abstract:

    Analytically solving the first passage failure probability of the Wiener process is extremely significant. Therefore, this paper conducts research on the problem of the first passage of the Wiener process across the safety boundary based on the Monte Carlo simulation method. Firstly, the simulation ideas and steps of the Wiener process are elaborated, where the direct method for generating random numbers is adopted to implement Wiener process simulation in MATLAB. Then, taking concrete durability degradation following a Wiener process as an engineering case, the first passage failure probability is calculated using the Monte Carlo simulation method. Comparative analysis with mathematical analytical solutions demonstrates that the Monte Carlo method achieves computational accuracy comparable to analytical solutions, while exhibiting superior advantages in application scope and operational convenience. This research provides a numerical solution approach for calculating first passage failure probabilities using Wiener processes in relevant engineering fields.

    参考文献
    相似文献
    引证文献
引用本文

张振浩,陈滔,袁方.基于蒙特卡罗模拟的维纳过程首次超越失效概率分析[J].工程建设,2025,57(10):75-80

复制
分享
相关视频

文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2025-02-27
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2025-11-06
  • 出版日期:
文章二维码