With the application of risk-informed safety margin characterization methodology, the computational risk assessment approach has become a useful measure to integrate both the traditional PSA and BEPU approaches to perform a risk-informed safety margin evaluation. In the traditional calculation of the event sequence success criteria in a classical PSA modeling, without proper uncertainty analysis a sequence can only be either success (zero) or failure (unity). Consequently, the traditional PSA modeling technique can be insensitive to a design change of limited scope. To make the traditional PSA model sensitive to a minor system impact, the uncertainties of associated stochastic and mechanistic parameters of related probabilistically significant sequences (PSS) need to be analyzed. In this paper, two probabilistically significant SBO sequences of a typical three-loop PWR, namely the loss of heat sink dominant group and the seal failure dominant group, were identified and revised with the consideration of both stochastic and mechanistic uncertainties for further ΔCDF evaluation when system power uprate by 5%.Particularly, to make the revised modeling of dominant SBO sequences more sensitive to a system impact of limited scope, the effective sampling range of the stochastic parameters, such as system power recover time, needs to be narrowed down reasonably. By applying the limit surface method, the effective sampling range of system power recover time lies only within a conditional success time interval defined by the tmin and tmax; when power recover time is early than tmin, the associated PSS will surely success, and vice versa for the time later than tmax. In the future application of the revised PSA computation risk assessment model to evaluate a power uprate of 5%, it was expected that both the tmin and tmax will be quantitatively reduced. Besides, the conditional exceedance probability (Pce) derived from the distribution of PCTs for the conditional success evaluation also will be recalculated. With new branching probabilities and Pce, a new conditional CDF of a SBO PSS can be evaluated for a power rate of limited scope.In our study, it was also demonstrated that with proper uncertainty analysis, the revised CDF of a SBO PSS can even be reduced by a factor of 8.75 to 3.10 compared to traditional PSA approach.