Assessment and predicting the axial power distribution effect on the thermal-mechanical parameters of the NuScale nuclear reactor core loaded with TVS-2 M fuel assemblies as well as axial Offset optimizing for load-following operation

IF 1.9 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY
M.H. Zahedi yeganeh, G.R. Ansarifar, H.Zayermohammadi Rishehri
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引用次数: 0

Abstract

This study evaluates and examines the thermal–mechanical behavior of a NuScale reactor core which utilizes TVS-2 M hexagonal fuel assemblies. The efficiency of the fuel rods is validated using the FRAPCON code. Initially, the reactor’s core is modeled with the MCNP code to locate the control banks. The design phase ensures the capability to shut down the reactor in two scenarios. In the Hot Zero Power (HZP) scenario, MCNP simulation reveals a sub-critical state with a multiplication factor of 0.94481 ± 0.00023. In the Cold Zero Power (CZP) scenario, the multiplication factor of 0.9935 ± 0.00023 confirms the adequacy of control assemblies. Subsequently, a thermal–mechanical analysis is conducted on the fuel rod over 1330 days, confirming its acceptable design and operational effectiveness in the core. Also, one of the parameters that can be examined during reactor control and load-following operations is Axial Offset (AO). Therefore, the study investigates the impact of AO on fuel rod’s thermal–mechanical changes. The MCNP code was used to simulate control rod inputs and obtain power distribution data for each AO deviation. Based on assessments regarding the association between AO and the thermal–mechanical characteristics of fuel, it has been determined that the impact of power distribution increases significantly over time, particularly towards the end of the operational period. Afterward, based on FRAPCON results, an artificial neural network (ANN) estimator is developed to predict thermal–mechanical parameters at the beginning of the cycle (BOC). The ANN proves to be a powerful method for estimation. By employing the ANN estimator and exploring different cost functions based on thermal–mechanical parameters, the optimal AO is determined using a genetic algorithm, which enhances the reactor’s performance, particularly in load-following operations. The attained optimal AO value for various cost functions are as follows: −0.10316, −0.19635, and −0.25817. This approach allows for the selection of the most efficient AO, leading to improved performance of the NuScale reactor core loaded with TVS-2 M hexagonal fuel assemblies. Indeed, optimization of AO is very important and useful for load-following operation.
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来源期刊
Nuclear Engineering and Design
Nuclear Engineering and Design 工程技术-核科学技术
CiteScore
3.40
自引率
11.80%
发文量
377
审稿时长
5 months
期刊介绍: Nuclear Engineering and Design covers the wide range of disciplines involved in the engineering, design, safety and construction of nuclear fission reactors. The Editors welcome papers both on applied and innovative aspects and developments in nuclear science and technology. Fundamentals of Reactor Design include: • Thermal-Hydraulics and Core Physics • Safety Analysis, Risk Assessment (PSA) • Structural and Mechanical Engineering • Materials Science • Fuel Behavior and Design • Structural Plant Design • Engineering of Reactor Components • Experiments Aspects beyond fundamentals of Reactor Design covered: • Accident Mitigation Measures • Reactor Control Systems • Licensing Issues • Safeguard Engineering • Economy of Plants • Reprocessing / Waste Disposal • Applications of Nuclear Energy • Maintenance • Decommissioning Papers on new reactor ideas and developments (Generation IV reactors) such as inherently safe modular HTRs, High Performance LWRs/HWRs and LMFBs/GFR will be considered; Actinide Burners, Accelerator Driven Systems, Energy Amplifiers and other special designs of power and research reactors and their applications are also encouraged.
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