• Proceedings of the Korean Nuclear Society Conference
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• 2002.05a
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• pp.66-66
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• 2002

Under Atomic Energy Society of Japan (AESJ) and Japan Atomic Energy Research Institute (JAERO, a Working Party on Reactor Physics of Accelerator-Driven System (ADS-WP) has been set since March 1999 to review and investigate special subjects related to reactor physics research of Accelerator-Driven System (ADS). In the ADSWP, the extensive and aggressive activity is being made by 25 professional members in the field of reactor physics in Japan. The ADS is now studying three subjects related to subcriticality of ADS; (1) calculation accuracy of sub criticality on ADS, (2) critical safety issues of ADS, and (3) theoretical review of subcriticality and its measurement methods. This paper describes two topics related to the subjects (1) and (2); one is an analysis of maximum reactivity potentially inserted to a subcritical core and the other is a benchmark proposal for checking calculation accuracy of sub criticality on ADS. The full specification of the calculation benchmark will be supplied by June 2002. Researchers from overseas, especially from Korea, are welcome to join this benchmark

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.1871-1885
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• 2019

The deterministic MOC code STREAM of the Computational Reactor Physics and Experiment (CORE) laboratory of Ulsan National Institute of Science and Technology (UNIST), was initially designed for the calculation of pressurized water reactor two- and three-dimensional assemblies and cores. Since fast reactors play an important role in the generation-IV concept, it was decided that the code should be upgraded for the analysis of fast neutron spectrum reactors. This paper presents a coupled code - TULIP/STREAM, developed for the fast reactor assembly and core calculations. The TULIP code produces self-shielded multi-group cross-sections using a one-dimensional cylindrical model. The generated cross-section library is used in the STREAM code which solves eigenvalue problems for a two-dimensional assembly and a multi-assembly whole reactor core. Multiplication factors and steady-state power distributions were compared with the reference solutions obtained by the continuous energy Monte-Carlo code MCS. With the developed code, a sensitivity study of the number of energy groups, the order of anisotropic P_N scattering, and the multi-group cross-section generation model was performed on the k_eff and power distribution. The 2D core simulation calculations show that the TULIP/STREAM code gives a k_eff error smaller than 200 pcm and the root mean square errors of the pin-wise power distributions within 2%.

• Nuclear Engineering and Technology
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• v.44 no.2
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• pp.103-122
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• 2012

Significant advances in computational performance have occurred over the past two decades, achieved not only by the introduction of more powerful processors but the incorporation of parallelism in computer hardware at all levels. Simultaneous with these hardware and associated system software advances have been advances in modeling physical phenomena and the numerical algorithms to allow their usage in simulation. This paper presents a review of the advances in computer performance, discusses the modeling and simulation capabilities required to address the multi-physics and multi-scale phenomena applicable to a nuclear reactor core simulator, and present examples of relevant physics simulation codes' performances on high performance computers.

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.54-67
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• 2018

There have been recent efforts to establish methods for high-fidelity and multi-physics simulation with coupled thermal-hydraulic (T/H) and neutronics codes for the entire core of a light water reactor under accident conditions. Considering the computing power necessary for a pin-by-pin analysis of the entire core, subchannel-scale T/H analysis is considered appropriate to achieve acceptable accuracy in an optimal computational time. In the present study, the applicability of in-house code CUPID of the Korea Atomic Energy Research Institute was extended to the subchannel-scale T/H analysis. CUPID is a component-scale T/H analysis code, which uses three-dimensional two-fluid models with various closure models and incorporates a highly parallelized numerical solver. In this study, key models required for a subchannel-scale T/H analysis were implemented in CUPID. Afterward, the code was validated against four subchannel experiments under unheated and heated single-phase incompressible flow conditions. Thereafter, a subchannel-scale T/H analysis of the entire core for an Advanced Power Reactor 1400 reactor core was carried out. For the high-fidelity simulation, detailed geometrical features and individual rod power distributions were considered in this demonstration. In this study, CUPID shows its capability of reproducing key phenomena in a subchannel and dealing with the subchannel-scale whole core T/H analysis.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.66-66
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.66.1-66.1
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• 2004

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.165-169
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• 2018

An assessment for determining N-16 activity concentrations during the operation condition of Bangladesh Atomic Energy Commission TRIGA Research Reactor was performed employing several governing equations. The radionuclide N-16 is a high energy (6.13 MeV) gamma emitter which is predominately created by the fast neutron interaction with O-16 present in the reactor core water. During reactor operation at different power level, the concentration of N-16 at the reactor bay region may increase causing radiation risk to the reactor operating personnel or the general public. Concerning the safety of the research reactor, the present study deals with the estimation of N-16 activity concentrations in the regions of reactor core, reactor tank, and reactor bay at different reactor power levels under natural convection cooling mode. The estimated N-16 activity concentration values with 500 kW reactor power at the reactor core region was $7.40{\times}10^5Bq/cm^3$ and at the bay region was $3.39{\times}10^5Bq/cm^3$. At 3 MW reactor power with active forced convection cooling mode, the N-16 activity concentration in the decay tank exit water was also determined, and the value was $4.14{\times}10^{-1}Bq/cm^3$.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.359-367
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• 2018

Long-lived Small Modular Reactors are being promoted as an innovative way of catering to emerging markets and isolated regions. They can be operated continuously for decades without requiring additional fuel. A novel configuration of long-lived reactor core employs a mixed neutron spectrum, providing an improvement in nonproliferation metrics and in safety characteristics. Starting with a base sodium reactor design, moderating material is inserted in outer core assemblies to modify the fast spectrum. The assemblies are shuffled once during core lifetime to ensure that every fuel rod is exposed to the thermalized spectrum. The Mixed Spectrum Reactor is able to maintain a core lifetime over two decades while ensuring the plutonium it breeds is below the weapon-grade limit at the fuel discharge. The main drawbacks of the design are higher front-end fuel cycle costs and a 58% increase in core volume, although it is alleviated to some extent by a 48% higher power output.

• Nuclear Engineering and Technology
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• v.53 no.10
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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.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1219-1225
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• 2017

In this work, a scalable algorithm for model calibration in nuclear engineering applications is presented and tested. The algorithm relies on the construction of surrogate models to replace the original model within the region of interest. These surrogate models can be constructed efficiently via reduced order modeling and subspace analysis. Once constructed, these surrogate models can be used to perform computationally expensive mathematical analyses. This work proposes a surrogate based model calibration algorithm. The proposed algorithm is used to calibrate various neutronics and thermal-hydraulics parameters. The virtual environment for reactor applications-core simulator (VERA-CS) is used to simulate a three-dimensional core depletion problem. The proposed algorithm is then used to construct a reduced order model (a surrogate) which is then used in a Bayesian approach to calibrate the neutronics and thermal-hydraulics parameters. The algorithm is tested and the benefits of data assimilation and calibration are highlighted in an uncertainty quantification study and requantification after the calibration process. Results showed that the proposed algorithm could help to reduce the uncertainty in key reactor attributes based on experimental and operational data.