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A statistical sensitivity analysis is used to determine robustness of the optimal PEM fuel cell design.
A statistical sensitivity analysis is used to identify the most uncertain input parameters based on model outputs.
After optimization, the main effects and interactions of these five factors were studied using statistical sensitivity analysis (SA).
Statistical sensitivity analysis (ANOVA analysis) is used to compute the effects and the contributions of the various factors to the fuel cell electrode.
The new analytical method was developed by means of a statistical sensitivity analysis applied to the main parameters influencing the recording, using the full factorial design method combined with the Yates algorithm and the steepest ascent optimization procedure.
In addition, the robustness of the optimum design of the fuel cell with respect to uncertainties in several electrochemical reaction and species transport parameters (e.g., gas diffusivity, agglomerate particle size, etc). is tested using a statistical sensitivity analysis.
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UQ-PyL integrates different kinds of UQ methods, including experimental design, statistical analysis, sensitivity analysis, surrogate modeling and parameter optimization.
Although this was handled in our statistical analysis, sensitivity analysis using several imputation techniques could provide a better understanding of the variability of the estimates.
We have developed MCM (Microbial Community Modeler), a mathematical framework and computational tool that unifies model construction with statistical evaluation, sensitivity analysis and parameter calibration.
BFAO, EI and SH designed and implemented the PM2.5 Risk Assessment methodology; WLJ and BFAO the statistical and sensitivity analysis; PA contributed with the air pollution and meteorological data.
In case of statistical heterogeneity, sensitivity analysis was performed to assess the contribution of each study to the pooled estimate by excluding individual studies one at a time and the pooled estimate was recalculated for the remaining studies.
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