Uncertainty and sensitivity analysis of in-vessel phenomena under severe accident mitigation strategy based on ISAA-SAUP program

The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.

Stochastic Analysis Method of Sea Environment Simulated by Numerical Models

This paper proposes the stochastic analysis method of sea environment simulated by numerical models, such as wave height, current field, design sea levels and longshore sediment transport. Uncertainty and sensitivity analysis of input and output factors of numerical models, their long-term distribution and confidence intervals are described in this paper.

Mathematical analysis of a tuberculosis model with imperfect vaccine

Since 1921,the Bacille Calmette Guerin(BCG)vaccine continues to be the most widely used vaccine for the prevention of Tuberculosis(TB).However,the immunity induced by BCG wanes out after some time making the vaccinated individual susceptible to TB infection.In this work,we formulate a mathematical model that incorporates the vaccination of newly born children and older susceptible individuals in the transmission dynamics of TB in a population,with a vaccine that can confer protection on older susceptible individuals.In the absence of disease-induced deaths,the model is shown to undergo the phenomenon of backward bifurcation where a stable disease-free equilibrium(DFE)co-exists with a stable positive(endemic)equilibrium when the associated repro-duction number is less than unity.It is shown that this phenomenon does not exist in the absence of imperfect vaccine,exogenous reinfection,and reinfection of prev iously treated individuals.It is further shown that a special case of the model has a unique endemic equilibrium point(EEP),which is globally asymptotically stable when the associated reproduction number exceeds unity.Uncertainty and sensitivity analysis are carried out to identify key parameters that have the greatest infuence on the transmission dynamics of TB in the population using the total population of latently infected individuals,total number of actively infected individuals,disease incidence,and the effective reproduc-tion number as output responses.The analysis shows that the top five parameters of the model that have the greatest influence on the effective reproduction number of the model are the transmission rate,the fraction of fast disease progression,modification parame-ter which accounts for reduced likelihood to infection by vaccinated individuals due to imperfect vaccine,rate of progression from latent to active TB,and the treatment rate of actively infected individuals,with other key parameters infuencing the outcomes of the other output responses.Numerical simulations suggest that with higher vaccination rate of older susceptible individuals,fewer new born children need to be vaccinated,in order to achieve disease eradication.