Refuelling Process Research Articles

Numerical simulations of corrosion product activity in the purification system of a typical PWR under nonlinearly rising corrosion and flow rate perturbations

Numerical simulations of corrosion product activity in the purification system of a Pressurised Water Reactor (PWR) are presented. The computer programme code Corrision Product Activity in Reactors (CPAIR-RC), developed by the authors, has been used to find corrosion product activity in the ion exchanger and filters of PWR under nonlinearly rising corrosion rates and flow rate perturbations. For nonlinearly rising corrosion rates, a typical value of removal rate 750 cm³ s−1 is taken, for which the saturation value of the activity has been found sufficiently low (0.27 µCi cm−3). The simulation results shows that for the constant refuelling and purification process, the activity, due to 59Fe, 99Mo and 56Mn, reaches saturation values within about 1000 h of reactor operation. However, two major contributors to radioactive buildup, 58Co and 60Co, keep on accumulating and do not saturate within this period. When the flow rate is decreased by 10% of the rated flow rate after 500 h of reactor operation, a dip in the activity is seen (which reaches the value of 0.0182 µCi cm−3), then it begins to rise again and reaches a saturation value of 0.271 µCi cm−3. The computed values of corrosion product activity from CPAIR-RC have been compared with some of the experimental data that are available in the literature and a fair agreement between them has been found.

Condition monitoring of an advanced gas-cooled nuclear reactor core

A critical component of an advanced gas-cooled reactor station is the graphite core. As a station ages, the graphite bricks that comprise the core can distort and may eventually crack. Since the core cannot be replaced, the core integrity ultimately determines the station life. Monitoring these distortions is usually restricted to the routine outages, which occur every few years, as this is the only time that the reactor core can be accessed by external sensing equipment. This paper presents a monitoring module based on model-based techniques using measurements obtained during the refuelling process. A fault detection and isolation filter based on unknown input observer techniques is developed. The role of this filter is to estimate the friction force produced by the interaction between the wall of the fuel channel and the fuel assembly supporting brushes. This allows an estimate to be made of the shape of the graphite bricks that comprise the core and, therefore, to monitor any distortion on them.

An intelligent system for interpreting the nuclear refuelling process within an advanced gas-cooled reactor

Evaluation of the data produced during the refuelling process in a nuclear power plant is required to ensure proper ‘set-down’ of the fuel assembly, thereby allowing the continued and safe operation of the station. The process of evaluating the data can be time consuming owing to the large amounts of data requiring considerable domain experience and interpretation. This paper presents an intelligent system (IS) to automate the process of data analysis, thereby shortening the evaluation time and providing an explanation of the reasoning behind its conclusions. The intelligent system utilizes a knowledge-based system (KBS), neural network based classification, K-means clustering techniques and rule induction methods to evaluate the data and inform the operator of any errors encountered.

Forecasting and Prediction Applications in the Field of Power Engineering

Within the field of power engineering, forecasting and prediction techniques underpin a number of applications such as fault diagnosis, condition monitoring and planning. These applications can now be enhanced due to the improved forecasting and prediction capabilities offered through the use of artificial neural networks. This paper demonstrates the maturity of neural network based forecasting and prediction through four diverse case studies. In each case study the authors have developed diagnostic, monitoring or planning applications (within the power engineering field) using neural networks and industrial data. The engineering applications discussed in the paper are: condition monitoring and fault diagnosis applied to a power transformer; condition monitoring and fault diagnosis applied to an industrial gas turbine; electrical load forecasting; monitoring of the refuelling process within a nuclear power station. For each case study the data sources, data preparation, neural network methods and implementation of the resulting application is discussed. The paper will show that the forecasting and prediction techniques discussed offer significant engineering benefits in terms of enhanced decision support capabilities.

Safety barrier function analysis in a process industry: A nuclear power application

Accidents in complex industrial systems often originate from interacting technical, organizational and human failures. Barrier functions protect the systems from the negative consequences of failures and errors. The purpose of the present study was to present a general model for and analyse the reliability of the existing barrier functions in the refuelling process in a nuclear power plant. A first step in the analysis was to identify the barrier functions in the refuelling process by constructing an Event and Barrier Function Model. Seventeen barrier functions were identified and classified as technical, human or human/organizational. Secondly, the reliability of the barrier functions were assessed using ratings from two personnel groups working in the process, sixteen plant operators and eleven external operators. Five performance shaping factors (PSFs) as well as six task-specific characteristics (TSCs) were also assessed. The plant operators rated the overall barrier function strength as significantly lower than the external operators. For judgments of contribution to a broken barrier function from PSFs and TSCs there were no significant difference between the two groups. Across groups, two PSFs, fatigue and night shift were rated as contributing more to the possibility of a broken barrier function. This analysis can provide a benchmark for comparison of safety in the refuelling task before and after a technical and organizational intervention.

Optimization of refuelling truck fleets at an airport

This paper considers the process of aircraft refuelling using refuelling trucks at an airport. The problem which arises is to determine the minimum number of refuelling trucks and their routes for the given demand (schedule and fuel quantities). The constraint is that there is no aircraft departure delay due to the refuelling process. The optimum solution is found here using the branch-and-bound technique. This solution is compared with results obtained on the basis of random assignment and a few conclusions are made. The paper also presents a model application example based on real life data from a medium-sized airport.