• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3803-3810
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• 2022

OpenMC is a community-driven open-source Monte Carlo neutron and photon transport simulation code. The Weight Window Mesh (WWM) function and an automatic Global Variance Reduction (GVR) method was recently developed and implemented in a developmental branch of OpenMC. This WWM function and GVR method broaden OpenMC's usage in general purposes deep penetration shielding calculations. However, the Local Variance Reduction (LVR) method, which suits the source-detector problem, is still missing in OpenMC. In this work, the Weight Window Generator (WWG) function has been developed and benchmarked for the same branch. This WWG function allows OpenMC to generate the WWM for the source-detector problem on its own. Single-material cases with varying shielding and sources were used to benchmark the WWG function and investigate how to set up the particle histories utilized in WWG-run and WWM-run. Results show that there is a maximum improvement of WWM generated by WWG. Based on the above results, instructions on determining the particle histories utilized in WWG-run and WWM-run for optimal computation efficiency are given and tested with a few multi-material cases. These benchmarks demonstrate the ability of the OpenMC WWG function and the above instructions for the source-detector problem. This developmental branch will be released and merged into the main distribution in the future.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.811-816
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• 2022

This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction β_eff and neutron generation time L. The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting Λ to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for 18 benchmark configurations.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3388-3400
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• 2023

Detailed analysis of the neutron pathway through matter inside the nuclear reactor core is exceedingly needed for safety and economic considerations. Due to the constant development of high-performance computing technologies, neutronics analysis using computer codes became more effective and efficient to perform sophisticated neutronics calculations. In this work, a commercial pressurized water reactor (PWR) presented by Virtual Environment for Reactor Applications (VERA) Core Physics Benchmark are modeled and simulated using a high-fidelity simulation of OpenMC code in terms of criticality and fuel pin power distribution. Various problems have been selected from VERA benchmark ranging from a simple two-dimension (2D) pin cell problem to a complex three dimension (3D) full core problem. The development of the code capabilities for reactor physics methods has been implemented to investigate the accuracy and performance of the OpenMC code against VERA SCALE codes. The results of OpenMC code exhibit excellent agreement with VERA results with maximum Root Mean Square Error (RMSE) values of less than 0.04% and 1.3% for the criticality eigenvalues and pin power distributions, respectively. This demonstrates the successful utilization of the OpenMC code as a simulation tool for a whole core analysis. Further works are undergoing on the accuracy of OpenMC simulations for the impact of different fuel types and burnup levels and the analysis of the transient behavior and coupled thermal hydraulic feedback.

• 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.1
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• pp.373-377
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• 2023

The Monte Carlo (MC) method has become an indispensable part of the nuclear radiation research field. Several widely used and well-known MC packages were developed for simulation of radiation transport and interaction with matter. All these MC packages require users to prepare an input script. The input script can become lengthy for complex models. The process of preparing these input scripts is time-consuming and error-prone. In the present work, we have developed an open-source GUI computer program for modelling radiation transport and interaction in multi-segmented slab phantoms using grid-based system for the widely used PHITS MC package. The developed tools would be useful for future users of PHITS MC package and particularly inexperienced users. The present program is distributed under GPL license and all users can freely download, modify and redistribute the program without any restrictions.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1593-1603
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• 2023

In deterministic and Monte Carlo transport codes, b-delayed emission is included using a group structure where all of the precursors are grouped together in 6 groups or families, but given the increase in computational power, nowadays there is no reason to keep this structure. Furthermore, there have been recent efforts to compile and evaluate all the available b-delayed neutron emission data and to measure new and improved data on individual precursors. In order to be able to perform a transient Monte Carlo simulation, data from individual precursors needs to be implemented in a transport code. This work is the first step towards the development of a tool to explore the effect of individual precursors in a fissile system. In concrete, individual precursor data is included by expanding the capabilities of the open source Monte Carlo code OpenMC. In the modified code - named Time Dependent OpenMC or OpenMC(TD)- time dependency related to β-delayed neutron emission was handled by using forced decay of precursors and combing of the particle population. The data for continuous energy neutron cross-sections was taken from JEFF-3.1.1 library. Regarding the data needed to include the individual precursors, cumulative yields were taken from JEFF-3.1.1 and delayed neutron emission probabilities and delayed neutron spectra were taken from ENDF-B/VIII.0. OpenMC(TD) was tested in a monoenergetic system, an energy dependent unmoderated system where the precursors were taken individually or in a group structure, and in a light-water moderated energy dependent system, using 6-groups, 50 and 40 individual precursors. Neutron flux as a function of time was obtained for each of the systems studied. These results show the potential of OpenMC(TD) as a tool to study the impact of individual precursor data on fissile systems, thus motivating further research to simulate more complex fissile systems.

• Korean Journal of Child Studies
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• v.29 no.6
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• pp.105-119
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• 2008

Investigating cross-cultural differences of family stress and adaptation in Korea and Australia, 49 families in open adoption were administered the Family Index of Regenerativity and Adaptation-General (McCubbin, 1987), Family Problem Solving Communications (McCubbin et al., 1988), and Social Support Index (McCubbin et al., 1982). Data were analyzed by T-test and correlation analysis. Results indicated that adoption itself was the primary stressor in both countries. Korean adoptive families were under stress by family-oriented factors; Australian adoptive families experienced external family stress. Regarding family hardiness, coping efforts and family communication, Australian adoptive families reported significantly higher family functioning than Korean adoptive families. Findings suggested that a broad range of social support is needed to improve family adaptability in both countries.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.1-7
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• 2020

Deep neural networks(DNN), which are used as approximation functions in reinforcement learning (RN), theoretically can be attributed to realistic results. In empirical benchmark works, time difference learning (TD) shows better results than Monte-Carlo learning (MC). However, among some previous works show that MC is better than TD when the reward is very rare or delayed. Also, another recent research shows when the information observed by the agent from the environment is partial on complex control works, it indicates that the MC prediction is superior to the TD-based methods. Most of these environments can be regarded as 5-step Q-learning or 20-step Q-learning, where the experiment continues without long roll-outs for alleviating reduce performance degradation. In other words, for networks with a noise, a representative network that is regardless of the controlled roll-outs, it is better to learn MC, which is robust to noisy rewards than TD, or almost identical to MC. These studies provide a break with that TD is better than MC. These recent research results show that the way combining MC and TD is better than the theoretical one. Therefore, in this study, based on the results shown in previous studies, we attempt to exploit a random balance with a mixture of TD and MC in RL without any complicated formulas by rewards used in those studies do. Compared to the DQN using the MC and TD random mixture and the well-known DQN using only the TD-based learning, we demonstrate that a well-performed TD learning are also granted special favor of the mixture of TD and MC through an experiments in OpenAI Gym.

• Korean journal of medical education
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• v.30 no.4
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• pp.317-326
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• 2018

Purpose: The study examines changes in students' self-assessment of their general communication (GC) and medical communication (MC) competencies, as well as perceptions of MC concepts. Methods: Participants included 108 second year medical students enrolled at a Korean medical school studying an MC curriculum. It was divided into three sections, and participants responded to questionnaires before and after completing each section. To assess perceived GC and MC competency, items based on a 7-point Likert scale were employed; a single open-ended item was used to examine students' perceptions of MC. Statistical analysis was conducted to gauge GC and MC competency, whereas semantic network analysis was used to investigate students' perceptions of MC. Results: Students perceived their GC competency to be higher than MC. Perceived MC competency differed significantly across the three sections, whereas no differences were found for GC. There were no statistically significant differences after completing the curriculum's second and third sections; however, the vocabulary students used to describe MC concepts became more scholarly and professional. In the semantic networks, the link structure between MC-related words decreased in linearity and looseness, becoming more complex and clustered. The words 'information' and 'transfer' proved integral to students' perceptions; likewise, 'empathy' and 'communication' became closely connected in a single community from two independent communities. Conclusion: This study differed from prior research by conducting an in-depth analysis of changes in students' perceptions of MC, and its findings can be used to guide curriculum development.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.803-810
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• 2022

The small modular liquid-metal fast reactor (SMFR) is an important component of advanced nuclear systems. SMFRs exhibit relatively low breeding capability and constraint space for control rod installation. Consequently, control rods are deeply inserted at beginning and are withdrawn gradually to compensate for large burnup reactivity loss in a long lifetime. This paper is committed to investigating the impact of control rod compensation operation on core neutronics characteristics. This paper presents a whole core fine depletion model of long lifetime SMFR using OpenMC and the influence of depletion chains is verified. Three control rod position schemes to simulate the compensation process are compared. The results show that the fine simulation of the control rod compensation process impacts significantly the fuel burnup distribution and absorber consumption. A control rod equivalent position scheme proposed in this work is an optimal option in the trade-off between computation time and accuracy. The control position is crucial for accurate power distribution and void feedback coefficients in SMFRs. The results in this paper also show that the pin level power distribution is important due to the heterogeneous distribution in SMFRs. The fuel burnup distribution at the end of core life impacts the worth of control rods.