• Nuclear Engineering and Technology
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• 제36권5호
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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.

• 상하수도학회지
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• 제11권3호
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• pp.51-58
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• 1997

Determining sizes and the locations of reservoirs in the water distribution system(WDS) with multi-reservoirs is much difficult than that with single reservoir. The extended period simulation(EPS) models provide more comprehensive analysis of water distribution systems than the steady-state models can do. Therefore, EPS models should be applied to the WDS with multi-reservoirs. This study is to investigate the variations of required reservoir sizes and residual nodal pressures according to reservoir locations. In this study, EPS was applied to analyze an artificial and a real WDS under several water demand patterns. As a result, it was found that water demand patterns make no significant differences in the determining of the reservoir size, if they have similar peaking factors. And the variations of the peaking factor should be carefully checked in the design and the analysis of the WDS with multi-reservoirs, because the peaking factor itself will affect the minimum allowable sizes of reservoirs in those systems.

• Nuclear Engineering and Technology
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• 제41권9호
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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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• 제50권7호
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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.

• 한국음향학회지
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• 제19권3호
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• pp.63-71
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• 2000

본 논문에서는 표준 대역통과 필터와 무증폭 바이패스 이득의 조합을 이용한 구조에 근거하여 전문가용 디지털 오디오에 적합한 정교한 주파수응답을 갖고, 실시간 시스템에서 적은 계산량과 메모리로 구현이 용이한 2차 디지털 픽킹 필터의 설계방식을 제안하였다. 이와 같이 설계된 디지털 픽킹 필터는 이득요인에 따라 필터의 대역폭이 왜곡되는 단점을 Q-보정을 통해 제거하였으며, 컨포말 변환에 의한 설계보다 수학적으로 간단하고 구현이 용이하며, 적은 계산량 및 메모리를 필요로 한다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1999년도 춘계학술발표회요약집
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• pp.21-21
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• 1999

• Nuclear Engineering and Technology
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• 제54권2호
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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.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2004년도 추계학술발표회 발표논문집
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• pp.845-846
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• 2004

• Nuclear Engineering and Technology
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• 제46권4호
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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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• 제51권7호
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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.