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LIU Lang, ZHAO Yifei, SONG Yumin. Improvement in Numerical Solution of Probability Density Evolution Equation and Slope Stability Analysis[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20250470
Citation: LIU Lang, ZHAO Yifei, SONG Yumin. Improvement in Numerical Solution of Probability Density Evolution Equation and Slope Stability Analysis[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20250470

Improvement in Numerical Solution of Probability Density Evolution Equation and Slope Stability Analysis

doi: 10.3969/j.issn.0258-2724.20250470
  • Received Date: 15 Sep 2025
  • Rev Recd Date: 22 Jan 2026
  • Available Online: 19 Oct 2026
  • To improve the computational accuracy and efficiency of the probability density evolution method in analyzing high-dimensional stochastic responses of complex structures, a total variation diminishing (TVD) scheme using Van Leer’s flux limiter and a hypersphere-based uniform point selection method are proposed. First, for the TVD scheme in difference solving, the limitations of the Roe-Sweby flux limiter are analyzed. Van Leer’s flux limiter is selected to optimize numerical solution accuracy, and its effectiveness is verified through numerical examples. Second, based on existing mathematical findings, the probability calculation formulas for the n-dimensional standard normal distribution within hyperspheres and hypercubes are derived, by which the hypersphere-based high-dimensional point selection method is quantitatively validated. Furthermore, a hypersphere-based good lattice point method is developed to generate uniform point sets and perform probability calculations within hyperspheres. Finally, taking a high slope project under construction as a case study, a probability density evolution equation for slope stability is established, and the proposed improved method is applied to calculate the slope stability coefficient. The results show that under normal service conditions and rainfall conditions, compared with 10 000 Monte Carlo simulations, the minimum errors of the probability integral for the slope stability coefficient are 0.4% and 0.2%, and the maximum errors are 2.9% and 4.2%, respectively. When addressing high-dimensional stochastic structural problems, the proposed numerical solution method demonstrates satisfactory computational accuracy and efficiency.

     

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