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The effect of three categories of key controller parameters on dominant eigenvalues is studied by sensitivity analysis, including: 1) active power drooping coefficient; 2) reactive power drooping coefficient; 3) parameters of outer loop excitation current control.
In this study, the nodalization of APR-1400 was modified to reflect the characteristic of upper region temperature, and the effect of nodalization and temperature of reactor upper region on LBLOCA consequence was evaluated by sensitivity analysis including best estimate plus uncertainty (BEPU) calculation.
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The sensitivity of the results to possible uncertainties in key parameters will be explored by a full sensitivity analysis, including a probabilistic sensitivity analysis.
Several approaches are employed for sensitivity analysis, including an approach featuring relation factors and a sensitivity analysis methodology.
An additional sensitivity analysis, including all cancer incidents, was performed.
The sensitivity analysis includes five repetitions, from F1 to F10, by considering all the hyper-parameter combinations.
Our sensitivity analysis included cases of single-time infection.
Table 5 shows results of tolerancing by sensitivity analysis method.
However, predictive models obtained by discriminant analysis including additional variables showed better AUC values and more accurate predictions in our study population (90.5 95.2% sensitivity and 95.5 100% specificity).
Subsequently they performed a sensitivity analysis by including the study site as a covariate.
However, we conducted a sensitivity analysis by including the difference between paternal and maternal age as a covariate.
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