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 Sobol' indices. 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交互作用和依赖关系，这些因素共同影响它们对输出的联合影响。此类模型的计算成本通常很高，而能够有效处理这种复杂性的敏感性分析方法寥寥无几。此外，整个敏感性分析领域对交互效应本质的关注有限，而理解这些效应对于设计安全可靠的系统至关重要。本文介绍并广泛测试了一种用于计算敏感性指数的简单分箱方法，并展示了将其与智能可视化方法——仿真分解（SimDec）相结合，如何能深入洞察复杂工程模型的行为。该简单分箱方法可计算一阶效应、二阶效应及综合敏感性指数，其计算效率远高于Sobol'指数。该敏感性分析框架整体提供了一种高效且直观的方式，用于分析包含交互作用和依赖关系的复杂系统的行为。