Modeling only constitutes one aspect of decision making. The prevailing limitation of applying modeling to practice is the absence of explicit consideration of uncertainties. This review paper covers uncertainty quantification (soil properties, stratification, and model performance) and uncertainty calculation with a focus on how it enhances the role of modeling in decision making (reliability analysis, reliability-based design, and inverse analysis). The key output from a reliability analysis is the probability of failure, where “failure” is defined as any condition that does not meet a performance criterion or a set of criteria. In contrast to the global factor of safety, the probability of failure respects both mechanics and statistics, is sensitive to data (thus opening one potential pathway to digital transformation), and it is meaningful for both system and component failures. Resilience engineering requires system level analysis. As such, geotechnical software can provide better decision support by computing the probability of failure/reliability index as one basic output in addition to stresses, strains, forces, and displacements. It is further shown that more critical non-classical failure mechanisms can emerge from spatially variable soils that can escape notice if the engineer were to restrict analysis to conventional homogeneous or layered soil profiles.

建模仅构成决策的一个方面。将建模应用于实践的普遍限制是没有明确考虑不确定性。这篇评论文章涵盖了不确定性量化（土壤特性、分层和模型性能）和不确定性计算，重点是它如何增强建模在决策制定中的作用（可靠性分析、基于可靠性的设计和逆分析）。可靠性分析的关键输出是故障概率，其中“故障”定义为不符合性能标准或一组标准的任何条件。与全球安全因素相比，故障概率同时涉及力学和统计数据，对数据敏感（因此开辟了一条通往数字化转型的潜在途径），它对系统和组件故障都有意义。弹性工程需要系统级分析。因此，岩土软件可以通过计算故障概率/可靠性指数作为除应力、应变、力和位移之外的一项基本输出来提供更好的决策支持。进一步表明，如果工程师将分析限制在传统的均质或分层土壤剖面，则可能会从空间可变的土壤中出现更关键的非经典破坏机制，这些机制可能会引起注意。