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DOI: 10.1615/IHTC13.p22.190
page 12

Ashley F. Emery
University of Washington, Seattle, WA 98195

D. Bardot
University of Washington, Seattle, USA


A critical aspect of any design is a sensitivity analysis to determine the effects of the different parameters, both controlled and implicit. This is usually done by modeling the system, representing the simulated response by a Taylor series, and evaluating the first order derivatives at nominal values of the parameters. Often the parameters are not known a-priori and are determined from experiments using inverse techniques.
Given the possible range of parameter values, the next step is to determine how the system responds as parameters are changed. When there is uncertainty about the parameters, particularly if there are many, the usual approach of Monte Carlo sampling can be computationally infeasible and it is important to restrict the analysis to those variables to which the response is most sensitive.
The problem can be characterized by three steps: a) determining which parameters are the most critical, b) devising experiments from which to infer the parameters, c) characterizing the effects of parameter variations on the system response. All steps can be conveniently accomplished by using Global sensitivity methodology that both defines the most critical variable and quantifies the effects of interactions between the variables.

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Measurement of fluid temperature with an arrangement of three thermocouples FLOW BOILING OF A HIGHLY VISCOUS POLYMER SOLUTION