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The objective of the present work is to simulate the nuclear coupled thermal–hydraulic fast transient case studies for a vertically up-flowing supercritical pressure water channel of circular cross section. The emphasis is on analyzing the phenomenon of the deterioration in heat transfer (DHT) inside the channel subjected to sharp pressure variations.

The thermal–hydraulic model, THRUST, is integrated with the neutron point kinetic (NPK) solver to account for the non-linear interactions between the thermal–hydraulic and neutronic temperature and density reactivity feedback effects. The model implemented and studied accounts for the time-dependent reactor power and is used to analyze various steady-state and flow-induced transient case studies (time-dependent and step change in exit pressure).

There is good agreement in the predicted behavior of the supercritical water pressure system with that of the available experimental data for the steady-state case. The event of DHT in the second transient case (step decrease in exit pressure) is found to be more severe than that of exponential pressure decrease.

This study evaluated a novel implementation of the thermal–hydraulic model, THRUST, integrated with NPKs applied to supercritical pressure water systems for predicting DHT.

To present dynamical analysis of axisymmetric and three‐dimensional (3D) simulations of a nuclear fluidized bed reactor. Also to determine the root cause of reactor power fluctuations.

We have used a coupled neutron radiation (in full phase space) and high resolution multiphase gas‐solid Eulerian‐Eulerian model.

The reactor can take over 5 min after start up to establish a quasi‐steady‐state and the mechanism for the long term oscillations of power have been established as a heat loss/generation mechanism. There is a clear need to parameterize the temperature of the reactor and, therefore, its power output for a given fissile mass or reactivity. The fission‐power fluctuates by an order of magnitude with a frequency of 0.5‐2 Hz. However, the thermal power output from gases is fairly steady.

The applications demonstrate that a simple surrogate of a complex model of a nuclear fluidised bed can have a predictive ability and has similar statistics to the more complex model.

This work can be used to analyze chaotic systems and also how the power is sensitive to fluctuations in key regions of the reactor.

The work presents the first 3D model of a nuclear fluidised bed reactor and demonstrates the value of numerical methods for modelling new and existing nuclear reactors.

Advanced heavy water reactor (AHWR) is a pressure tube type of heavy water reactor. It eliminates high-pressure heavy water coolant resulting in a reduction of heavy water leakage losses and eliminating heavy water recovery system. It recovers the heat generated in the moderator for feed water heating. However, it requires a satisfactory technological response to develop an effective controller that attains the challenges of the very high-level safety system. Hence, they require application-specific improvement for better controlling performance.

The purpose of this study intends to propose a system for controlling state vectors v₁ and v₂and in AHWR using Grey Wolf second-order sliding mode control (GW-SoSMC) technique. The main aim of the paper is to minimize the errors between the predicted and desired azimuthal angles of the system. With this proposed method, it is possible to mitigate both the chattering phenomenon and controlling performance of AHWR system. It implements a SoSMC controller based on GWO algorithm for the purpose of controlling the state vectors in the AHWR system. It aims to accomplish a controller for improving the performance of the AHWR system.

Through the performance analysis, the efficiency of the proposed GW-SoSMC technique was verified by comparing it with various conventional algorithms, such as GW-SMC, FF-SoSMC, ABC-SoSMC, GS-SoSMC and GA-SoSMC. From the analysis, it was obtained that the implemented GW-SoSMC technique was 65.3 per cent superior to GW-SMC, 65.32 per cent superior to both FF-SoSMC and 65 per cent superior to ABC-SoSMC, 65.8 per cent superior to the GS-SoSMC and 58 per cent superior to the GA-SoSMC methods. Thus, the effectiveness of the proposed method in controlling the state vectors in AHWR was obtained.

This paper presents a technique for controlling the state vectors in the AHWR system using GWO algorithm. This is the first work that uses GWO-based optimization for controlling state vectors in the AHWR system.