30 resultados para Nuclear-Power-Reactor
em Greenwich Academic Literature Archive - UK
Resumo:
The consecutive, partly overlapping emergence of expert systems and then neural computation methods among intelligent technologies, is reflected in the evolving scene of their application to nuclear engineering. This paper provides a bird's eye view of the state of the application in the domain, along with a review of a particular task, the one perhaps economically more important: refueling design in nuclear power reactors.
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In this book, expert energy economists assess the energy policy of thirty-one countries and the role of nuclear power. For many years the shock of Chernobyl took nuclear power off the agenda in most countries. Intense public relations activities by the industry, increasing evidence of climate change and failures to effectively reduce greenhouse gas emissions, have brought nuclear power issues back to the forefront of policy discussion in the nuclear renaissance countries. But some countries are just not prepared to go in that direction and, indeed, are still divesting themselves of their nuclear legacy, the nuclear phase-out countries. And how are nuclear issues being approached in the industrializing countries? An in-depth country-by-country analysis is presented within this framework. Out of such an analysis emerge thematic discussions on, among others, strategy in energy policy; nuclear plant safety, the impacts of nuclear accidents; the adequacy of nuclear power expertise. [Source: publisher's product description].
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An assessment of the impact of the financial crisis on the prospects for new nuclear power plant orders worldwide.
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The inaugural lecture of Professor Stephen Thomas at the University of Greenwich, 4th February 2010. It examines whether further pursuit of competition in energy markets and expansion in the role of nuclear power can be the main elements in a policy to meet goals of security, sustainability and affordability.
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This report examines the credibility of the claim by the UK government that nuclear power plants can be built in the UK without public subsidies and guarantees
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Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.
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This report examines the level of debt of ENEL and how that will be impacted by its plans for new nuclear power plants.
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Although some countries plan to build new nuclear power plants in the near future, in aggregate the data indicates that nuclear power's influence will continue to dwindle across the globe in coming decades.
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This paper describes new crossover operators and mutation strategies for the FUELGEN system, a genetic algorithm which designs fuel loading patterns for nuclear power reactors. The new components are applications of new ideas from recent research in genetic algorithms. They are designed to improve the performance of FUELGEN by using information in the problem as yet not made explicit in the genetic algorithm's representation. The paper introduces new developments in genetic algorithm design and explains how they motivate the proposed new components.
Resumo:
FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.
Resumo:
FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.
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Power electronic modules distinguish themselves from other modules by their high power operation. These modules are used extensively in high power application markets such as aerospace, automotive, industrial and traction and drives. This paper discusses typical packaging technologies for power electronics modules. It also discusses the latest results from a UK research project investigating the physics-of-failure approach to reliability analysis and predictions for power modules. An integrated design enviroment for incorporating of affects of uncertainty into the design environment was outlined.
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This paper discusses the reliability of power electronics modules. The approach taken combines numerical modeling techniques with experimentation and accelerated testing to identify failure modes and mechanisms for the power module structure and most importantly the root cause of a potential failure. The paper details results for two types of failure (i) wire bond fatigue and (ii) substrate delamination. Finite element method modeling techniques have been used to predict the stress distribution within the module structures. A response surface optimisation approach has been employed to enable the optimal design and parameter sensitivity to be determined. The response surface is used by a Monte Carlo method to determine the effects of uncertainty in the design.
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In this paper the reliability of the isolation substrate and chip mountdown solder interconnect of power modules under thermal-mechanical loading has been analysed using a numerical modelling approach. The damage indicators such as the peel stress and the accumulated plastic work density in solder interconnect are calculated for a range of geometrical design parameters, and the effects of these parameters on the reliability are studied by using a combination of the finite element analysis (FEA) method and optimisation techniques. The sensitivities of the reliability of the isolation substrate and solder interconnect to the changes of the design parameters are obtained and optimal designs are studied using response surface approximation and gradient optimization method