• Nuclear Engineering and Technology
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• 제51권6호
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• pp.1596-1609
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• 2019

The fuel rod performance has great importance for the safety and economy of an operating reactor. The fuel rod performance analysis code, which considers the thermal-mechanical response and irradiation effects of fuel rod, is usually developed in order to predict fuel rod performance accurately. The FRIPAC (${\underline{F}}uel$ ${\underline{R}}od$ ${\underline{I}}ntegral$ ${\underline{P}}erformance$ ${\underline{A}}nalysis$ ${\underline{C}}ode$) is such a fuel rod performance analysis code that has been developed recently by China Nuclear Power Technology Research Institute Co. Ltd. The code aims at the computational simulation of the Pressurized Water Reactor fuel rod behavior for both steady-state and power ramp condition. A brief overview of FRIPAC is presented including the computational framework and the main behavioral models. Validation of the code is also presented and it focuses on the fuel rod behavior including fuel center temperature, fission gas release, rod internal pressure/internal void volume, cladding outer diameter and cladding corrosion thickness. The validation is based on experimental data from several international projects. The validation results indicate that FRIPAC is an accurate and reliable fuel rod performance analysis code because of the satisfactory comparison results between the experimental measurements and the code predictions.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3665-3674
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• 2021

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.1085-1097
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• 2022

A printed circuit steam generator (PCSG) is being considered as the component for pressurized water reactor (PWR) type small modular reactor (SMR) that can further reduce the physical size of the system. Since a steam generator in many PWR-type SMR generates superheated steam, it is expected that dryout front oscillation can potentially cause thermal fatigue failure due to cyclic thermal stresses induced by the transition in boiling regimes between convective evaporation and film boiling. To investigate the fatigue issue of a PCSG, a reference PCSG is designed in this study first using an in-house PCSG design tool. For the stress analysis, a finite element method analysis model is developed to obtain the temperature and stress fields of the designed PCSG. Fatigue estimation is performed based on ASME Boiler and pressure vessel code to identify the major parameters influencing the fatigue life time originating from the dryout front oscillation. As a result of this study, the limit on the temperature difference between the hot side and cold side fluids is obtained. Moreover, it is found that the heat transfer coefficient of convective evaporation and film boiling regimes play an essential role in the fatigue life cycle as well as the temperature difference.

• Nuclear Engineering and Technology
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• 제53권5호
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• pp.1491-1510
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• 2021

This work presents an illustration of Nagra's AMAC (Advanced Methodology for Activation Characterization) approach to the South Korean pressurized water reactor Kori-1 decommissioning. The results achieved are supported by the existing experience from the detailed AMAC applications to Swiss NPPs and are used not only for a demonstration of the applicability of AMAC to South Korean NPPs, but also for a first approximation of the activated waste volumes to be expected from Kori-1. A packaging concept based on the above activation characterization is also presented, using the AMAC algorithmic optimization software ALGOPACK leading to the minimum number of waste containers needed given the selected packaging constraints. Nagra's AMAC enables effective planning before and during NPP decommissioning, including recommendations for cutting profiles for diverse reactor components and building structures. Finally, it is expected to lead to significant cost savings by reducing the number of expensive waste containers, by optimizing a potential melting strategy for metallic waste as well as by significantly limiting the number of radiological measurements. All information about Kori-1 used for the purpose of this study was collected from publicly available sources.

• Nuclear Engineering and Technology
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• 제52권12호
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• pp.2821-2835
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• 2020

The phenomenon identification and ranking table (PIRT) is an important basis in the nuclear power plant (NPP) thermal-hydraulic analysis. This study focuses on the importance ranking of the input parameters when lacking the PIRT, and the target scenario is the small break loss of coolant accident (SBLOCA) in a pressurized water reactor (PWR) CPR1000. A total of 54 input parameters which might have influence on the figure of merit (FOM) were identified, and the sensitivity measure of each input on the FOM was calculated through an optimized moment-independent global sensitivity analysis method. The importance ranking orders of the parameters were transformed into the Savage scores, and the parameters were categorized based on the Savage scores. A parameter importance ranking table for the SBLOCA scenario of the CPR1000 reactor was obtained, and the influences of some important parameters at different break sizes and different accident stages were analyzed.

• Nuclear Engineering and Technology
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• 제54권12호
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• pp.4534-4550
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• 2022

Integrated severe accident codes should be capable of simulating not only specific physical phenomena but also entire plant behaviors, and in a sufficiently fast time. However, significant uncertainty may exist owing to the numerous parametric models and interactions among the various phenomena. The primary objectives of this study are to present best-practice uncertainty and sensitivity analysis results regarding the evolutions of severe accidents (SAs) and fission product source terms and to determine the effects of mitigation measures on them, as expected during a short-term station blackout (STSBO) of a reference pressurized water reactor (optimized power reactor (OPR)1000). Three reference scenarios related to the STSBO accident are considered: one base and two mitigation scenarios, and the impacts of dedicated severe accident mitigation (SAM) actions on the results of interest are analyzed (such as flammable gas generation). The uncertainties are quantified based on a random set of Monte Carlo samples per case scenario. The relative importance values of the uncertain input parameters to the results of interest are quantitatively evaluated through a relevant sensitivity/importance analysis.

• Nuclear Engineering and Technology
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• 제56권6호
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• pp.2208-2219
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• 2024

Kylin-2 is an advanced neutronics lattice code, developed by Nuclear Power Institute of China. High-precision multigroup cross section library is need for KYLIN-2 to carry out simulation of current pressurized water reactor (PWR) and advanced reactor. In this paper a multigroup cross section library generation system named TPAMS was developed, the methods in TPAMS dealing with resonance data such as subgroup parameters, lambda factor, resonance integral were discussed. Moreover, the depletion chain simplification method was studied. TPAMS can produce multigroup library in binary and ASIIC formats, including detailed data contents for resonance, transport and depletion calculations. A multigroup cross section library has been generated for KYLIN-2 based on TPAMS system. The multigroup cross section library was verified through the analysis of various criticality and burnup benchmarks, the values of multiplication factor and isotope density were compared with the experiment data. Numerical results demonstrate the accuracy of the multigroup cross section library and the reliability of the multigroup cross section library generation system TPAMS.

• Nuclear Engineering and Technology
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• 제35권5호
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• pp.426-441
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• 2003

A reactor inlet header break experiment, B9401, performed in the RD-14M multi channel test facility was analyzed using RELAP5/MOD3.2 and RELAP5/CANDU[1]. The RELAP5 has been developed for the use in the analysis of the transient behavior of the pressurized water reactor. A recent study showed that the RELAP5 could be feasible even for the simulation of the thermal hydraulic behavior of CANDU reactors. However, some deficiencies in the prediction of fuel sheath temperature and transient behavior in athe headers were identified in the RELAP5 assessments. The RELAP5/CANDU has been developing to resolve the deficiencies in the RELAP5 and to improve the predictability of the thermal-hydraulic behaviors of the CANDU reactors. In the RELAP5/CANDU, critical heat flux model, horizontal flow regime map, heat transfer model in horizontal channel, etc. were modified or added to the RELAP5/MOD3.2. This study aims to identify the applicability of both codes, in particular, in the multi-channel simulation of the CANDU reactors. The RELAP5/MOD3.2 and the RELAP5/CANDU analyses demonstrate the code's capability to predict reasonably the major phenomena occurred during the transient. The thermal-hydraulic behaviors of both codes are almost identical, however, the RELAP5/CANDU predicts better the heater sheath temperature than the RELAP5/MOD3.2. Pressure differences between headers govern the flow characteristics through the heated sections, particularly after the ECI. In determining header pressure, there are many uncertainties arisen from the complicated effects including steady state pressure distribution. Therefore, it would be concluded that further works are required to reduce these uncertainties, and consequently predict appropriately thermal-hydraulic behaviors in the reactor coolant system during LOCA analyses.

• Nuclear Engineering and Technology
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• 제47권1호
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• pp.47-58
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• 2015

Four recycling scenarios involving pyroprocessing of spent fuel (SF) have been investigated for a 600-MWe transmutation sodium-cooled fast reactor (SFR), KALIMER. Performance evaluation was done with code system REBUS connected with TRANSX and TWODANT. Scenario Number 1 is the pyroprocessing of Canada deuterium uranium (CANDU) SF. Because the recycling of CANDU SF does not have any safety problems, the CANDU-Pyro-SFR system will be possible if the pyroprocessing capacity is large enough. Scenario Number 2 is a feasibility test of feed SF from a pressurized water reactor PWR. Thefsensitivity of cooling time before prior to pyro-processing was studied. As the cooling time sensitivity of cooling time before prior to pyro-processing was studied. As the cooling time increases, excess reactivity at the beginning of the equilibrium cycle (BOEC) decreases, thereby creating advantageous reactivity control and improving the transmutation performance of minor actinides. Scenario Number 3 is a case study for various levels of recovery factors of transuranic isotopes (TRUs). If long-lived fission products can be separated during pyroprocessing, the waste that is not recovered is classified as low- and intermediate-level waste, and it is sufficient to be disposed of in an underground site due to very low-heat-generation rate when the waste cooling time becomes >300 years at a TRU recovery factor of 99.9%. Scenario Number 4 is a case study for the recovery factor of rare earth (RE) isotopes. The RE isotope recovery factor should be lowered to ${\leq}20%$ in order to make sodium void reactivity less than <7$, which is the design limit of a metal fuel.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.