• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.420-429
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• 2004

The local power density should be estimated accurately to prevent fuel rod melting. The local power density at the hottest part of a hot fuel rod, which is described by the power peaking factor, is more important information than the local power density at any other position in a reactor core. Therefore, in this work, the power peaking factor, which is defined as the highest local power density to the average power density in a reactor core, is estimated by fuzzy neural networks using numerous measured signals of the reactor coolant system. The fuzzy neural networks are trained using a training data set and are verified with another test data set. They are then applied to the first fuel cycle of Yonggwang nuclear power plant unit 3. The estimation accuracy of the power peaking factor is 0.45% based on the relative $2_{\sigma}$ error by using the fuzzy neural networks without the in-core neutron flux sensors signals input. A value of 0.23% is obtained with the in-core neutron flux sensors signals, which is sufficiently accurate for use in local power density monitoring.

• Nuclear Engineering and Technology
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• v.41 no.9
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• pp.1181-1190
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• 2009

Knowing more about the Local Power Density (LPD) at the hottest part of a nuclear reactor core can provide more important information than knowledge of the LPD at any other position. The LPD at the hottest part needs to be estimated accurately in order to prevent the fuel rod from melting in a nuclear reactor. Support Vector Machines (SVMs) have successfully been applied in classification and regression problems. Therefore, in this paper, the power peaking factor, which is defined as the highest LPD to the average power density in a reactor core, was estimated by SVMs which use numerous measured signals of the reactor coolant system. The SVM models were developed by using a training data set and validated by an independent test data set. The SVM models' uncertainty was analyzed by using 100 sampled training data sets and verification data sets. The prediction intervals were very small, which means that the predicted values were very accurate. The predicted values were then applied to the first fuel cycle of the Yonggwang Nuclear Power Plant Unit 3. The root mean squared error was approximately 0.15%, which is accurate enough for use in LPD monitoring and for core protection that uses LPD estimation.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1017-1023
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• 2018

The measurement and calculation of neutronic parameters in nuclear research reactors has an important influence on control and safety of the nuclear reactor. The power peaking factors, reactivity coefficients and kinetic parameters are the most important neutronic parameter for determining the state of the reactor. The position of the control shim safety rods in the core configuration affects these parameters. The main purpose of this work is to use the MTR_PC package to evaluate the effect of the partially insertion of the control rod on the neutronic parameters at the operating core of the Tehran Research Reactor. The simulation results show that by increasing the insertion of control rods (bank) in the core, the absolute values of power peaking factor, reactivity coefficients and effective delayed neutron fraction increased and only prompt neutron life time decreased. In addition, the results show that the changes of moderator temperature coefficients value versus the control rods positions are very significant. The average value of moderator temperature coefficients increase about 98% in the range of 0-70% insertion of control rods.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.513-520
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• 2014

In this paper, three types of operational and industrial absorbers used at research reactors, including Ag-In-Cd alloy, $B_4C$, and Hf are selected for sensitivity analyses. Their integral effects on the main neutronic core parameters important to safety issues are investigated. These parameters are core excess reactivity, shutdown margin, total reactivity worth of control rods, thermal neutron flux, power density distribution, and Power Peaking Factor (PPF). The IAEA 10 MW benchmark core is selected as the case study to verify calculations. A two-dimensional, three-group diffusion model is selected for core calculations. The well-known WIMS-D4 and CITATION reactor codes are used to carry out these calculations. It is found that the largest shutdown margin is gained using the $B_4C$; also the lowest PPF is gained using the Ag-In-Cd alloy. The maximum point power densities belong to the inside fuel regions surrounding the central flux trap (irradiation position), surrounded by control fuel elements, and the peripheral fuel elements beside the graphite reflectors. The greatest and least fluctuation of the point power densities are gained by using $B_4C$ and Ag-In-Cd alloy, respectively.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1729-1737
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• 2019

This paper presents neutronics design of VVER-1000 fuel assembly using burnable poison particles (BPPs) for controlling excess reactivity and pin-wise power distribution. The advantage of using BPPs is that the thermal conductivity of BPP-dispersed fuel pin could be improved. Numerical calculations have been conducted for optimizing the BPP parameters using the MVP code and the JENDL-3.3 data library. The results show that by using $Gd_2O_3$ particles with the diameter of $60{\mu}m$ and the packing fraction of 5%, the burnup reactivity curve and pin-wise power distribution are obtained approximately that of the reference design. To minimize power peaking factor (PPF), total BP amount has been distributed in a larger number of fuel rods. Optimization has been conducted for the number of BPP-dispersed rods, their distribution, BPP diameter and packing fraction. Two models of assembly consisting of 18 BPP-dispersed rods have been selected. The diameter of $300{\mu}m$ and the packing fraction of 3.33% were determined so that the burnup reactivity curve is approximate that of the reference one, while the PPF can be decreased from 1.167 to 1.105 and 1.113, respectively. Application of BPPs for compensating the reduction of soluble boron content to 50% and 0% is also investigated.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.608-616
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• 2022

Power peaking factors (PPF) is an important parameter for safe and efficient reactor operation. There are several methods to calculate the PPF at TRIGA research reactors such as MCNP and TRIGLAV codes. However, these methods are time-consuming and required high specifications of a computer system. To overcome these limitations, artificial intelligence was introduced for parameter prediction. Previous studies applied the neural network method to predict the PPF, but the publications using the ANFIS method are not well developed yet. In this paper, the prediction of PPF using the ANFIS was conducted. Two input variables, control rod position, and neutron flux were collected while the PPF was calculated using TRIGLAV code as the data output. These input-output datasets were used for ANFIS model generation, training, and testing. In this study, four ANFIS model with two types of input space partitioning methods shows good predictive performances with R² values in the range of 96%-97%, reveals the strong relationship between the predicted and actual PPF values. The RMSE calculated also near zero. From this statistical analysis, it is proven that the ANFIS could predict the PPF accurately and can be used as an alternative method to develop a real-time monitoring system at TRIGA research reactors.

• Nuclear Engineering and Technology
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• v.15 no.4
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• pp.236-247
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• 1983

Analyzed are the the DNBR(Departure from Nucleate Boiling Ratio) sensitivities to variations in various PWR operating parameters utilizing the Korea Nuclear Unit 1(KNU-1) design and operating data. Studied parameters in the analysis are core power level, system pressure, core inlet flow rate, core inlet temperature, enthalpy rise hot channel factor, and axial power peaking factor and axial offset. The calculations are performed using the steady state and transient thermal-hydraulics computer program, COBRA-IV-K, which is the revised version of COBRA-IV-i that has been adapted, partially modified and verified at KAERI. A reference case is established based on the design and operating condition of the KNU-1 reactor core, and this provides a basis for the subsequent sensitivity analysis. From the calculation results it is concluded that the most sensitive parameter in the DNBR thermal design is the coolant core inlet temperature while the axial power peaking factor is the least sensitive.

• Nuclear Engineering and Technology
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• v.25 no.2
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• pp.193-203
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• 1993

A new heuristic method for loading pattern search has been developed to overcome short-comings of the algorithmic approach. To reduce the size of vast solution space, general shuffling rules, a regionwise shuffling method, and a pattern grouping method were introduced. The entropy theory was applied to classify possible loading patterns into groups with similarity between them. The pattern search program was implemented with use of the PROLOG language. A two-group nodal code MEDIUM-2D was used for analysis of power distribution in the core. The above mentioned methodology has been tested to show effectiveness in reducing of solution space down to a few hundred pattern groups. Burnable poison rods were then arranged in each pattern group in accordance with burnable poison distribution rules, which led to further reduction of the solution space to several scores of acceptable pattern groups. The method of maximizing cycle length(MCL) and minimizing power-peaking factor(MPF) were applied to search for specific useful loading patterns from the acceptable pattern groups. Thus, several specific loading patterns that have low power-peaking factor and large cycle length were successfully searched from the selected pattern groups.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.10a
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• pp.220-220
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• 2003

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1126-1139
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• 2016

In this research, for the first time, a new optimization method, i.e., strength Pareto evolutionary algorithm II (SPEA-II), is developed for the burnable poison placement (BPP) optimization of a nuclear reactor core. In the BPP problem, an optimized placement map of fuel assemblies with burnable poison is searched for a given core loading pattern according to defined objectives. In this work, SPEA-II coupled with a nodal expansion code is used for solving the BPP problem of Kraftwerk Union AG (KWU) pressurized water reactor. Our optimization goal for the BPP is to achieve a greater multiplication factor ($K_{eff}$) for gaining possible longer operation cycles along with more flattening of fuel assembly relative power distribution, considering a safety constraint on the radial power peaking factor. For appraising the proposed methodology, the basic approach, i.e., SPEA, is also developed in order to compare obtained results. In general, results reveal the acceptance performance and high strength of SPEA, particularly its new version, i.e., SPEA-II, in achieving a semioptimized loading pattern for the BPP optimization of KWU pressurized water reactor.