• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1715-1720
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• 2019

Jozef Stefan Institute (JSI), TRIGA Mark II reactor employs the homogeneous mixture of uranium and zirconium hydride fuel type. Since its upgrade, a series of fresh fuel steady state experimental benchmarks have been conducted. The benchmark results have provided data for testing computational neutronics codes which are important for reactor design and safety analysis. In this work, we investigated the JSI TRIGA Mark II reactor neutronics characteristics: the effective multiplication factor and two safety parameters, namely the control rod worth and the fuel temperature reactivity coefficient using SuperMC. The modeling and real-time cross section generation methods of SuperMC were evaluated in the investigation. The calculation analysis indicated the following: the effective multiplication factor was influenced by the different cross section data libraries; the control rod worth evaluation was better with Monte Carlo codes; the experimental fuel temperature reactivity coefficient was smaller than calculated results due to change in water temperature. All the results were in good agreement with the experimental values. Hence, SuperMC could be used for the designing and benchmarking of other TRIGA Mark II reactors.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.2034-2041
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• 2019

Public acceptance has become the most critical question for sustainable development of nuclear energy in recent decades. Many researches concentrated on risk and benefit perception, which were deemed as the most influential factors of Public Acceptance of Nuclear Energy (PANE). But few researches focused on psychological factors including regulatory focus. Therefore, this paper aimed to explore the moderating effect of regulatory focus on PANE based on Regulatory Focus Theory in order to find ways to increase/decrease PANE. An Internet-based survey had been carried out in China nationwide. The results indicated that trust in government was positively related to PANE and this relationship was mediated by risk and benefit perception. In addition, the strength of the associations between risk and benefit perception and PANE were moderated by regulatory focus, consisting of prevention focus and promotion focus. Prevention focus strengthened the negative relationship between risk perception and PANE, while promotion focus weakened. Moreover, promotion focus weakened the positive relationship between benefit perception and PANE, but no significant moderating effect of prevention focus was founded on the relationship between benefit perception and PANE. Some policy implications were also proposed on the basis of above-mentioned findings.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.103-110
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• 2021

In the development of a Risk Monitor probabilistic safety assessment (PSA) model from the basic PSA model of a nuclear power plant, the modeling of common-cause failure (CCF) is very important. At present, some approximate modeling methods are widely used, but there lacks criterion of modeling accuracy and error analysis. In this paper, aiming at ensuring the accuracy of risk assessment and minimizing the Risk Monitor PSA models size, we present three basic issues of CCF model resulted from the changes of a nuclear power plant configuration, put forward corresponding modeling methods, and derive accuracy criteria of CCF modeling based on minimum cut sets and risk indicators according to the requirements of risk monitoring. Finally, a nuclear power plant Risk Monitor PSA model is taken as an example to demonstrate the effectiveness of the proposed modeling method and accuracy criteria, and the application scope of the idea of this paper is also discussed.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3897-3908
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• 2022

High-fidelity nuclear data libraries and neutronics simulation tools are essential for the development of fast reactors. The IAEA coordinated research project on "Neutronics Benchmark of CEFR Start-Up Tests" offers valuable data for the qualification of nuclear data libraries and neutronics codes. This paper focuses on the verification and validation of the CEFR start-up modelling using OpenMC Monte-Carlo code against the experimental measurements. The OpenMC simulation results agree well with the measurements in criticality, control rod worth, sodium void reactivity, temperature reactivity, subassembly swap reactivity, and reaction distribution. In feedback coefficient evaluations, an additional state method shows high consistency with lower uncertainty. Among 122 relative errors in the benchmark of the distribution of nuclear reaction, 104 errors are less than 10% and 84 errors are less than 5%. The results demonstrate the high reliability of OpenMC for its application in fast reactor simulations. In the companion paper, the influence of cross-section libraries is investigated using neutronics modelling in this paper.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3639-3647
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• 2023

This paper defines a 3D full core neutronics benchmark which is based on the NuScale small modular reactor (SMR) concept. The paper provides a detailed description of the NuScale-like core, a list of expected outputs, and a reference solution to the benchmark exercises obtained with the Monte Carlo code Serpent. The benchmark was developed in the framework of the Euratom McSAFER project and can be used for verification of computational chains dedicated to 3D full-core neutronics simulations of water cooled SMRs. The paper is supplemented with a digital data set to ease the modeling process.

• Nuclear Engineering and Technology
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• v.44 no.2
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• pp.161-176
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• 2012

McCARD is a Monte Carlo (MC) neutron-photon transport simulation code. It has been developed exclusively for the neutronics design of nuclear reactors and fuel systems. It is capable of performing the whole-core neutronics calculations, the reactor fuel burnup analysis, the few group diffusion theory constant generation, sensitivity and uncertainty (S/U) analysis, and uncertainty propagation analysis. It has some special features such as the anterior convergence diagnostics, real variance estimation, neutronics analysis with temperature feedback, $B_1$ theory-augmented few group constants generation, kinetics parameter generation and MC S/U analysis based on the use of adjoint flux. This paper describes the theoretical basis of these features and validation calculations for both neutronics benchmark problems and commercial PWR reactors in operation.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2452-2459
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• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.518-524
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• 2016

The thermal aging effects on mechanical properties and microstructures in China low-activation martensitic steel have been tested by aging at $550^{\circ}C$ for 2,000 hours, 4,000 hours, and 10,000 hours. The microstructure was analyzed by scanning and transmission electron microscopy. The results showed that the grain size and martensitic lath increased by about $4{\mu}m$ and $0.3{\mu}m$, respectively, after thermal exposure at $550^{\circ}C$ for 10,000 hours. MX type particles such as TaC precipitated on the matrix and Laves-phase was found on the martensitic lath boundary and grain boundary on aged specimens. The mechanical properties were investigated with tensile and Charpy impact tests. Tensile properties were not seriously affected by aging. Neither yield strength nor ultimate tensile strength changed significantly. However, the ductile-brittle transition temperature of China low-activation martensitic steel increased by $46^{\circ}C$ after aging for 10,000 hours due to precipitation and grain coarsening.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3150-3163
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• 2023

To improve the performance of blanket: maximizing the tritium breeding rate (TBR) for tritium self-sufficiency, and minimizing the Dose of backplate for radiation protection, most previous studies are based on manual corrections to adjust the blanket structure to achieve optimization design, but it is difficult to find an optimal structure and tends to be trapped by local optimizations as it involves multiphysics field design, which is also inefficient and time-consuming process. The artificial intelligence (AI) maybe is a potential method for the optimization design of the blanket. So, this paper aims to develop an intelligent optimization method based on an improved multi-objective NSGA-III algorithm and an adaptive BP neural network to solve these problems mentioned above. This method has been applied on optimizing the radial arrangement of a conceptual design of CFETR HCSB blanket. Finally, a series of optimal radial arrangements are obtained under the constraints that the temperature of each component of the blanket does not exceed the limit and the radial length remains unchanged, the efficiency of the blanket optimization design is significantly improved. This study will provide a clue and inspiration for the application of artificial intelligence technology in the optimization design of blanket.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.313-342
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• 2014

A Nuclear Energy Agency (NEA), Organization for Economic Co-operation and Development (OECD) benchmark for Uncertainty Analysis in Modeling (UAM) is defined in order to facilitate the development and validation of available uncertainty analysis and sensitivity analysis methods for best-estimate Light water Reactor (LWR) design and safety calculations. The benchmark has been named the OECD/NEA UAM-LWR benchmark, and has been divided into three phases each of which focuses on a different portion of the uncertainty propagation in LWR multi-physics and multi-scale analysis. Several different reactor cases are modeled at various phases of a reactor calculation. This paper discusses Phase I, known as the "Neutronics Phase", which is devoted mostly to the propagation of nuclear data (cross-section) uncertainty throughout steady-state stand-alone neutronics core calculations. Three reactor systems (for which design, operation and measured data are available) are rigorously studied in this benchmark: Peach Bottom Unit 2 BWR, Three Mile Island Unit 1 PWR, and VVER-1000 Kozloduy-6/Kalinin-3. Additional measured data is analyzed such as the KRITZ LEU criticality experiments and the SNEAK-7A and 7B experiments of the Karlsruhe Fast Critical Facility. Analyzed results include the top five neutron-nuclide reactions, which contribute the most to the prediction uncertainty in keff, as well as the uncertainty in key parameters of neutronics analysis such as microscopic and macroscopic cross-sections, six-group decay constants, assembly discontinuity factors, and axial and radial core power distributions. Conclusions are drawn regarding where further studies should be done to reduce uncertainties in key nuclide reaction uncertainties (i.e.: $^{238}U$ radiative capture and inelastic scattering (n, n') as well as the average number of neutrons released per fission event of $^{239}Pu$).