Occupational Radiation Exposure at Commercial Nuclear Power Reactors and Other Facilities 2008

This report summarizes the occupational exposure data that are maintained in the U.S. Nuclear Regulatory Commission (NRC) Radiation Exposure Information and Reporting System (REIRS). The bulk of the information contained in the report was compiled from the 2008 annual reports submitted by five of the seven categories1 of NRC licensees subject to the reporting requirements of 10 CFR 20.2206. The annual reports submitted by these licensees consist of radiation exposure records for each monitored individual. These records are analyzed for trends and presented in this report in terms of collective dose and the distribution of dose among the monitored individuals. Because there are no geologic repositories for high-level waste currently licensed and no low-level waste disposal facilities in operation, only five categories will be considered in this report

Effect of non-uniform reactor cooling on fracture and constraint of a reactor pressure vessel

In the lifetime prediction and extension of a nuclear power plant, a reactor pressure vessel (RPV) has to demonstrate the exclusion of brittle fracture. This paper aims to apply fracture mechanics to analyse the non‐uniform cooling effect in case of a loss‐of‐coolant accident on the RPV integrity. A comprehensive framework coupling reactor system, fluid dynamics, fracture mechanics, and probabilistic analyses for the RPVs integrity analysis is proposed. The safety margin of the allowed RTNDT is increased by more than 16°C if a probabilistic method is applied. Considering the non‐uniform plume cooling effect increases KI more than 30%, increases the failure frequency by more than 1 order of magnitude, and increases the crack tip constraint due to the resulting higher stress. Thus, in order to be more realistic and not to be nonconservative, 3D computational fluid dynamics may be required to provide input for the fracture mechanics analysis of the RPV

Development of simulation-based testing environment for safety-critical software

Recently, a software program has been used in nuclear power plants (NPPs) to digitalize many instrumentation and control systems. To guarantee NPP safety, the reliability of the software used in safety-critical instrumentation and control systems must be quantified and verified with proper test cases and test environment. In this study, a software testing method using a simulation-based software test bed is proposed. The test bed is developed by emulating the microprocessor architecture of the programmable logic controller used in NPP safety-critical applications and capturing its behavior at each machine instruction. The effectiveness of the proposed method is demonstrated via a case study. To represent the possible states of software input and the internal variables that contribute to generating a dedicated safety signal, the software test cases are developed in consideration of the digital characteristics of the target system and the plant dynamics. The method provides a practical way to conduct exhaustive software testing, which can prove the software to be error free and minimize the uncertainty in software reliability quantification. Compared with existing testing methods, it can effectively reduce the software testing effort by emulating the programmable logic controller behavior at the machine level

The role of the reactor size for an investment in the nuclear sector: an evaluation of not-financial parameters

The literature presents many studies about the economics of new Nuclear Power Plants (NPPs). Such studies are based on Discounted Cash Flow (DCF) methods encompassing the accounts related to Construction, Operation & Maintenance, Fuel and Decommissioning. However the investment evaluation of a nuclear reactor should also include not-financial factors such as siting and grid constraints, impact on the national industrial system, etc. The Integrated model for the Competitiveness Assessment of SMRs (INCAS), developed by Politecnico di Milano cooperating with the IAEA, is designed to analyze the choice of the better Nuclear Power Plant size as a multidimensional problem. In particular the INCAS’s module “External Factors” evaluates the impact of the factors that are not considered in the traditional DCF methods. This paper presents a list of these factors, providing, for each one, the rationale and the quantification procedure; then each factor is quantified for the Italian case. The IRIS reactor has been chosen as SMR representative. The approach and the framework of the model can be applied to worldwide countries while the specific results apply to most of the European countries. The results show that SMRs have better performances than LRs with respect to the external factors, in general and in the Italian scenario in particular