• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3283-3292
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• 2022

Based on the Deep Q-Network(DQN) algorithm of reinforcement learning, an active fault-tolerance method with incremental action is proposed for the control system with sensor faults of the once-through steam generator(OTSG). In this paper, we first establish the OTSG model as the interaction environment for the agent of reinforcement learning. The reinforcement learning agent chooses an action according to the system state obtained by the pressure sensor, the incremental action can gradually approach the optimal strategy for the current fault, and then the agent updates the network by different rewards obtained in the interaction process. In this way, we can transform the active fault tolerant control process of the OTSG to the reinforcement learning agent's decision-making process. The comparison experiments compared with the traditional reinforcement learning algorithm(RL) with fixed strategies show that the active fault-tolerant controller designed in this paper can accurately and rapidly control under sensor faults so that the pressure of the OTSG can be stabilized near the set-point value, and the OTSG can run normally and stably.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3643-3652
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• 2021

Sizing the tube inlet orifice of a Once-Through Steam Generator (OTSG) is important to protect the integrity of the tubes from thermal cycling and vibration wear. In this study, a new sizing criterion is proposed for the tube inlet orifice to suppress the parallel channel instability in an OTSG. A perturbation method is used to capture the essential parts of the thermal-hydraulic phenomena of the parallel channel instability. The perturbation model of the heat transfer regime boundaries is identified as a missing part in existing models for sizing the OTSG tube inlet orifice. Limitations and deficiency of the existing models are identified and the reasons for the limitations are explained. The newly proposed model can be utilized to size the tube inlet orifice to suppress the parallel channel instability without excessive engineering margin.

• Nuclear Engineering and Technology
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• 제55권10호
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• pp.3515-3524
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• 2023

A reinforcement learning framework is proposed for the control problem of outlet steam pressure of the once-through steam generator(OTSG) in this paper. The double-layer controller using Proximal Policy Optimization(PPO) algorithm is applied in the control structure of the OTSG. The PPO algorithm can train the neural networks continuously according to the process of interaction with the environment and then the trained controller can realize better control for the OTSG. Meanwhile, reinforcement learning has the characteristic of difficult application in real-world objects, this paper proposes an innovative pretraining method to solve this problem. The difficulty in the application of reinforcement learning lies in training. The optimal strategy of each step is summed up through trial and error, and the training cost is very high. In this paper, the LSTM model is adopted as the training environment for pretraining, which saves training time and improves efficiency. The experimental results show that this method can realize the self-adjustment of control parameters under various working conditions, and the control effect has the advantages of small overshoot, fast stabilization speed, and strong adaptive ability.

• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1388-1395
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• 2017

The Helically coiled tube Once-Through Steam Generator (H-OTSG) is a key piece of equipment for compact small reactors. The present study developed and verified a thermal-hydraulic design and performance analysis computer code for a countercurrent H-OTSG installed in a small pressurized water reactor. The H-OTSG is represented by one characteristic tube in the model. The secondary side of the H-OTSG is divided into single-phase liquid region, nucleate boiling region, postdryout region, and single-phase vapor region. Different heat transfer correlations and pressure drop correlations are reviewed and applied. To benchmark the developed physical models and the computer code, H-OTSGs developed in Marine Reactor X and System-integrated Modular Advanced ReacTor are simulated by the code, and the results are compared with the design data. The overall characteristics of heat transfer area, temperature distributions, and pressure drops calculated by the code showed general agreement with the published data. The thermal-hydraulic characteristics of a typical countercurrent H-OTSG are analyzed. It is demonstrated that the code can be utilized for design and performance analysis of an H-OTSG.

• Nuclear Engineering and Technology
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• 제55권7호
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• pp.2395-2406
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• 2023

To study the influence of parameter uncertainty in small pressurized water reactor (SPWR) once-through steam generator (OTSG), the nonlinear mathematical model of the SPWR is firstly established. Including the reactor core model, the OTSG model and the pressurizer model. Secondly, a control strategy that both the reactor core coolant average temperature and the secondary-side outlet pressure of the OTSG are constant is adopted. Then, the uncertainty quantification method is established based on Latin hypercube sampling and statistical method. On this basis, the quantitative platform for parameter uncertainty of the OTSG is developed. Finally, taking the uncertainty in primary-side flowrate of the OTSG as an example, the platform application work is carried out under the variable load in SPWR and step disturbance of secondary-side flowrate of the OTSG. The results show that the maximum uncertainty in the critical output parameters is acceptable for SPWR.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.460-474
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• 2023

A simple but accurate mathematical model is crucial for dynamic simulations and controller design of helical coil once-through steam generator (OTSG). This paper presents a three-region movable boundary dynamic model of the helical coil OTSG. Based on the secondary side fluid conditions, the OTSG is divided into subcooled region (two control volumes), two-phase region (two control volumes) and superheated region (three control volumes) with movable boiling boundaries between each region. The nonlinear dynamic model is derived based on mass, energy and momentum conservation equations. And the linear model is obtained by using the transfer function and state space transformation, which is a 37-order model of five input and three output. Validations are made under full-power steady-state condition and four transient conditions. Results show good agreements among the nonlinear model, linear model and the RELAP5 model, with acceptable errors. This model can be applied to dynamic simulations and controller design of helical coil OTSG with constant primary-side flow rate.