Models of complex technological systems inherently contain interactions and dependencies among their input variables that affect their joint influence on the output. Such models are often computationally expensive and few sensitivity analysis methods can effectively process such complexities. Moreover, the sensitivity analysis field as a whole pays limited attention to the nature of interaction effects, whose understanding can prove to be critical for the design of safe and reliable systems. In this paper, we introduce and extensively test a simple binning approach for computing sensitivity indices and demonstrate how complementing it with the smart visualization method, simulation decomposition (SimDec), can permit important insights into the behavior of complex engineering models. The simple binning approach computes first-, second-order effects, and a combined sensitivity index, and is considerably more computationally efficient than the mainstream measure for Sobol indices introduced by Saltelli et al. The totality of the sensitivity analysis framework provides an efficient and intuitive way to analyze the behavior of complex systems containing interactions and dependencies.

翻译：复杂技术系统的模型本质上包含输入变量之间的相互作用与依赖关系，这些关系会影响其对输出的联合影响。此类模型通常计算成本高昂，而现有敏感性分析方法中能有效处理此类复杂性的方法寥寥无几。此外，敏感性分析领域整体对交互效应本质的关注有限，但其理解对设计安全可靠的系统至关重要。本文提出一种计算敏感性指标的简单分箱方法，并通过广泛测试证明：将其与智能可视化方法——模拟分解（SimDec）相结合，可深入洞察复杂工程模型的行为特征。该简单分箱方法能计算一阶效应、二阶效应及综合敏感性指标，其计算效率显著优于Saltelli等人提出的Sobol指标主流度量方法。完整的敏感性分析框架为分析包含交互作用与依赖关系的复杂系统行为提供了高效直观的途径。