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Inspired by the well-established variance-based methods for globalsensitivity analysis, we develop a local total sensitivity index thatdecomposes the global total sensitivity conditions by independent variables'values. We employ this local sensitivity index in a new method of experimentaldesign that sequentially and adaptively samples the domain of a multivariatefunction according to local contributions to the global variance. The method isdemonstrated on a nonlinear illustrative example that has a three-dimensionaldomain and a three-dimensional codomain, but also on a complex,high-dimensional simulation for assessing the industrial viability of theproduction of bioproducts from biomass.

Adaptively Sampling via Regional Variance-Based Sensitivities