<i>Control of Nuclear Reactors and Power Plants</i>

Schultz, M. A.; Teichmann, T.

doi:10.1063/1.3059852

Cited by 54 publications

(26 citation statements)

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“…where transform equations and (4)(5) and thus the reactor model is stable if Go<--Ax ( go 5 J x 1011) , which ' i is in agreement with other studies of xenon induced instabilities (26,38,41 In this chapter the problem of xenon induced flux instabilities will be examined employing one energy group, time and space dependent diffusion theory.…”

Section: Substituting Original Parameters Into Equation (3-24) Givesmentioning

confidence: 55%

Xenon-135 Induced Instabilities of the Neutron Flux in Nuclear Reactors

Sandquist¹

1964

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Section: Substituting Original Parameters Into Equation (3-24) Givesmentioning

confidence: 55%

Xenon-135 Induced Instabilities of the Neutron Flux in Nuclear Reactors

Sandquist¹

1964

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“…The reactor model for observer design in this paper is the point kinetics with one equivalent delayed neutron group and temperature feedback from both the fuel and coolant temperature, which is given as follows [6][7][8]29]:…”

Section: Dynamic Model For Observer Designmentioning

confidence: 99%

A Neural-Network-Based Nonlinear Adaptive State-Observer for Pressurized Water Reactors

Dong

2013

Energies

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Abstract:Although there have been some severe nuclear accidents such as Three Mile Island (USA), Chernobyl (Ukraine) and Fukushima (Japan), nuclear fission energy is still a source of clean energy that can substitute for fossil fuels in a centralized way and in a great amount with commercial availability and economic competitiveness. Since the pressurized water reactor (PWR) is the most widely used nuclear fission reactor, its safe, stable and efficient operation is meaningful to the current rebirth of the nuclear fission energy industry. Power-level regulation is an important technique which can deeply affect the operation stability and efficiency of PWRs. Compared with the classical power-level controllers, the advanced power-level regulators could strengthen both the closed-loop stability and control performance by feeding back the internal state-variables. However, not all of the internal state variables of a PWR can be obtained directly by measurements. To implement advanced PWR power-level control law, it is necessary to develop a state-observer to reconstruct the unmeasurable state-variables. Since a PWR is naturally a complex nonlinear system with parameters varying with power-level, fuel burnup, xenon isotope production, control rod worth and etc., it is meaningful to design a nonlinear observer for the PWR with adaptability to system uncertainties. Due to this and the strong learning capability of the multi-layer perceptron (MLP) neural network, an MLP-based nonlinear adaptive observer is given for PWRs. Based upon Lyapunov stability theory, it is proved theoretically that this newly-built observer can provide bounded and convergent state-observation. This observer is then applied to the state-observation of a special PWR, i.e., the nuclear heating reactor (NHR), and numerical simulation results not only verify its feasibility but also give the relationship between the observation performance and observer parameters. OPEN ACCESSEnergies 2013, 6 5383

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“…The control-rod drives are located at the top of the reactor. Water flows through the reactor in three passes: (1) it enters near the bottom of the reactor and flows up through the thermal shields, (2) it flows down through the outer portion of the core, and (3) it flows up through the center of the core and out through the top of the reactor. A diagrammatic representation of the reactor, primary-coolant loop, and boiler is shown in Figure 1.…”

Section: Description Of the Reactor Power Plantmentioning

confidence: 99%