Response surface methods are widely used in slope reliability analysis due to the high efficiency. However, they are often criticized of the curse of high dimensionality, problem-dependent accuracy, and mechanism-free interpretation. To address these issues, this study proposes a response surface-guided adaptive slope reliability analysis method for slopes in spatially varying soils. A sparse quadratic polynomial is initialized using a two-fold dimensionality reduction technique. The response surface-based preliminary slope reliability analysis is successfully corrected to an unbiased, finite element-based target slope reliability analysis, during which the response surface updates iteratively with an increasing high accuracy from special emphasis nearby the failure domain. Two spatially varying soil slopes are investigated. Results indicate that the proposed method can provide an efficient and unbiased estimation of finite element-based target slope failure probability with a low variability, develop a more accurate and problem-oriented response surface model for slope reliability analysis, and explore failure mechanisms of slope stability in spatially varying soils. Its performance is insensitive to the accuracy of initial response surface. Additionally, it prominently outperforms both response surface and finite element-based subset simulations, regardless of high-dimensional or low-failure-probability problems. These advantages significantly enhance the application of response surface on practical slope reliability analysis.

由于高效率，响应面法被广泛用于边坡可靠度分析。但是，他们经常被批评高维度，依赖问题的准确性和无机制解释的诅咒。为了解决这些问题，本研究针对空间变​​化的土壤中的边坡提出了一种响应面引导的自适应边坡可靠性分析方法。使用二维降维技术初始化稀疏二次多项式。基于响应面的初步边坡可靠性分析已成功地校正为无偏，基于有限元的目标边坡可靠性分析，在此过程中，响应面通过在失效域附近的特别强调而以更高的精度迭代更新。研究了两个空间变化的土壤坡度。结果表明，所提出的方法可以有效地，无偏差地估计基于有限元的目标边坡破坏概率，为边坡可靠度分析开发更为准确和面向问题的响应面模型，并探索边坡稳定性的破坏机理。在空间变化的土壤中。其性能对初始响应面的精度不敏感。此外，无论高维或低故障概率问题如何，它都明显优于响应面和基于有限元的子集模拟。这些优点极大地增强了响应面在实际边坡可靠性分析中的应用。