Uncertainty and sensitivity analysis of food pathway results with the MACCS reactor accident consequence model

Abstract

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the food pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 87 imprecise] y-known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, milk growing season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and 1-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, 1-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of (3-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, tranfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk.

Identification and Review of Sensitivity Analysis Methods

“…As one example, Helton et al . (1995) used stepwise regression analysis for sensitivity analysis of a model for contamination of food pathways associated with a severe accident at a nuclear power station.…”

“…As one example, Helton et al (1995) used stepwise regression analysis for sensitivity analysis of a model for contamination of food pathways associated with a severe accident at a nuclear power station. A probabilistic analysis was done and forward stepwise regression analysis was used to help identify which of the input distributions contributed most to uncertainty in the mean population dose.…”

Investigation of the uncertainty of the in-plane mechanical properties of composite laminates

“…At present, only a few studies have been conducted to obtain the sensitivity indicators for models with correlated input variables. [12][13][14][15][16][17][18][19] However, all these methods can only derive an overall sensitivity index of one parameter, which is not convenient for engineering decision-making. Chonggang et al 20 remarked that the contribution of uncertainty to model output by an individual input variable should be divided into two parts: the uncorrelated contribution and the correlated one.…”

Cost per severe accident as an index for severe accident consequence assessment and its applications

“…The deterministic effect is the "injury in populations of cells, characterised by a threshold dose and an increase in the severity of the reaction as the dose is increased further", where the stochastic effects are the "malignant disease and heritable effects for which the probability of an effect occurring, but not its severity, is regarded as a function of dose without threshold" [46]. Both effects are typically considered as the health effects from the radiological accidents [7][8][9][10][11][12][13][14][15][16]. However, we decided not to include the deterministic effects into the scope of assessment.…”

“…ADD module uses the source term information and meteorological data to simulate the advection and diffusion of the released radioactive materials and their deposition amounts. MS preprocessor code uses the bin sampling method [29] to pick up 248 representative sequences from 8,760 typical meteorological sequences to consider the effects of the meteorological conditions (8,760 meteorological sequences were obtained by recording the meteorological data of the selected location every hour for one year). These meteorological sequences are selected in a manner that can take into account all kinds of weather conditions in a year from very moderate to very extreme.…”