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arXiv · 1803.10722

Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model

Daniel Inman·Laura J. Vimmerstedt·Brian Bush·Dana Stright·Steve Peterson
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Abstract

Variance-based sensitivity methods can provide insights into large computational models. We present a novel application of sensitivity analysis to the Biomass Scenario Model (BSM) a large and complex system dynamics model of the developing biofuels industry in the United States. We apply a two-stage sensitivity approach consisting of an initial sensitivity screening, followed by a variance decomposition approach. Identifying key system levers and quantifying their strength is not straightforward in complex system dynamics models that have numerous feedbacks and nonlinear results. Variance-based sensitivity analysis (VBSA) offers a systematic, global approach to assessing system dynamics models because it addresses nonlinear responses and interactive effects. Especially when a large model's size makes manual exploration of the input space difficult and time-consuming, the approach can help to provide a comprehensive understanding of interactions that drive model behaviors.

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Daniel Inman, Laura J. Vimmerstedt, Brian Bush, Dana Stright, Steve Peterson. 2018-03-28. Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model. https://arxiv.org/abs/1803.10722

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