• Nuclear Engineering and Technology
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• 제53권3호
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• pp.894-900
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• 2021

This paper examines sorption of Pd(II) onto illite, MX-80 bentonite, and Queenston shale in Na-Ca-Cl solutions of varying ionic strength (IS) from 0.01 to 6.0 mol/L (M) and pH_c ranging from 3 to 9 under atmospheric conditions. A 2-site protolysis non-electrostatic surface complexation and cation exchange model was applied to the Pd sorption onto illite and MX-80 using PHREEQC, and the model results were compared to the experimental ones obtained in this work. Surface complexation and cation exchange constants were estimated for both illite and MX-80 through the optimization process to bring the predicted distribution coefficients from the model into alignment with the experimentally derived values. These optimized surface complexation constants were compared to existing linear free energy relationships (LFER).

• 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.

• 한국전문물리치료학회지
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• 제14권1호
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• pp.82-89
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• 2007

The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is a valid and widely used instrument for the assessment of osteoarthritis patients. In this study, data was obtained from the out-patients with painful osteoarthritis of the knee. One hundred-three out-patients were interviewed by physical therapists. In an exploratory way, a Korean version of the KWOMAC was analyzed for unidimensionality, item separation, and item difficulty using the Winsteps programs. Ninety-five patients with osteoarthritis of the knee over 65 years were analyzed for Rash analysis. In the analysis several functional items poorly fit to the model. These items included "heavy domestic duties" and "standing". In the pain domain, one item ("at night while in bed") did not fit the model. In the stiffness domain one item ("after sitting, lying, or resting later in the day") did not fit the model. Although 4 items from the 3 domains (pain, stiffness, function domain) do not fit well, the KWOMAC domains were confirmed by Rasch analysis. Thus the KWOMAC needs to be further examined before it can be used to properly determine the health status of the elderly with OA.

• 한국ITS학회 논문지
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• 제17권6호
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• pp.25-39
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• 2018

본 연구에서는 최근 활발하게 활용되고 있는 머신러닝 기법을 교통분야에 적용하여 효율적인 돌발상황 검지 알고리즘을 개발하는 것을 목적으로 하였다. 미시교통시뮬레이션 모형을 통하여 대상지의 네트워크를 구축하였고 돌발상황에 영향을 줄 것으로 예상되는 변수의 여러 조합을 통해 시나리오를 설정하여 가상의 돌발상황 데이터를 수집하였다. 다음으로 대표적인 돌발상황 검지 알고리즘인 McMaster 알고리즘과 본 연구에서 개발한 나이브 베이즈 분류기를 구현하여 비교 평가하였다. 비교 결과, 나이브 베이즈 분류기가 McMaster 알고리즘에 비해 돌발상황 검지 간격에 따른 부정적인 영향이 적었고 더 우수한 검지율을 보였다. 하지만 검지율이 증가하는 만큼 오검지율 또한 증가하는 것을 확인할 수 있었다. McMaster 알고리즘은 4주기를 통해 검지가 가능하지만 나이브 베이즈 분류기는 1주기(30초)만으로 돌발상황을 판단할 수 있다. 본 연구를 통해 개발한 나이브 베이즈 분류기가 효율적으로 돌발을 파악할 수 있다는 것을 확인할 수 있었다.

• 재활치료과학
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• 제10권3호
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• pp.83-96
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• 2021

목적 : 개인의 성장과 사회적 활동에 영향을 미치는 국내 가족기능 요소를 개발하기 위해, 가족기능 평가도구인 McMaster 모델을 기반으로 국내 문화와 적합한 내용을 도출하여 가족기능에 영향을 주는 요소들을 델파이 기법을 통해 확인하고자 하였다. 연구방법 : 가족기능과 관련이 깊은 분야의 전문가 패널 12명을 대상으로 델파이 기법을 실시하였다. 기간은 2020년 5월부터 6월까지 총 7주간 진행되었으며, 델파이 조사는 2회 실시하였다. 1차 조사에서는 McMaster 모델의 국내 문화와 적합한 내용을 선정 및 한글화를 진행한 후, 구성요소에 관한 폐쇄형 항목 및 개방형 항목을 사용하여 전문가들의 의견을 수집하였다. 2차 조사에서는 구성요소의 적합도 및 중요도를 조사하였다. 결과 : 1차 델파이 조사 결과, 제시된 53개의 항목에서 18개의 항목이 삭제되었고, 11개의 항목이 추가되었으며, 의미가 중복되는 항목을 제외하여 40개의 항목이 선정되었다. 이 후 이해가 어려운 문장을 친숙한 어휘로 수정하고 2차 조사지를 구성하였다. 2차 델파이 결과에서는 총 33개의 항목이 선정되었으며, 최종 선정된 구성요소에 대한 내용타당도 비율은 0.76, 안정도는 0.28로 도출되었다. 결론 : 본 연구를 통해 도출된 국내 가족기능 평가를 위한 영향요소들은 가족기능을 포함하고 임상현장 또는 관련연구에서 가족기능 평가 및 중재를 시행하는데 활용되기를 기대한다.

• Nuclear Engineering and Technology
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• 제50권5호
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• pp.794-800
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• 2018

The proliferation resistance (PR) of Th/U and Th/Pu fuels used in CANada Deuterium Uranium for the deep geological repository was assessed by combining the multiattribute utility analysis proposed by Chirayath et al., 2015 with the transport model of radionuclides in the repository and comparing with that of the used natural U fuel case. It was found that there was no significant advantage for Th/U and Th/Pu fuels from the viewpoint of the PR in the repository. It was also found that the PR values for used nuclear fuels in the repository of Th/U, Th/Pu, and natural U was comparable with those for enrichment and reprocessing facilities in the pressurized water reactor (PWR) nuclear fuel cycle. On the other hand, the PR values considering the transport of radionuclides in the repository were found to be slightly smaller than those without their transport after the used nuclear fuels started dissolving after 1,000 years.

• 방사성폐기물학회지
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• 제20권2호
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• pp.151-160
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• 2022

The sorption of Eu on MX-80 bentonite in Na-Ca-Cl solutions is investigated at a molal proton concentration (pH_m) range of 3 to 10 and an ionic strength (I) range of 0.1 to 6 m (mol·kgw^-1). The sorption equilibrium of Eu on MX-80 is achieved within 14 to 21 d at I = 0.1 and 6 m. The sorption distribution coefficient (K_d) values of Eu for MX-80 increase as pH_m increases from 3 to 6 for all I values, and they are independent of pH_m between 8 and 10 at I ≥ 0.5 m. Meanwhile, at I = 0.1 m, the K_d value at pH_m = 10 is slightly lower than those at pH_m = 8 and 9. The K_d values are not affected by the I values between 0.5 m and 6 m, whereas the K_d value at I = 0.1 m is greater than those at I ≥ 0.5 m, except at pH_m = 10. A two-site protolysis nonelectrostatic surface complexation and cation exchange sorption model is applied to the Eu sorption data for I ≤ 4 m, and the equilibrium constants of the sorption reactions are estimated.

• Nuclear Engineering and Technology
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• 제51권6호
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• pp.1540-1553
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• 2019

A nuclear power plant (NPP) is a highly complex system-of-systems as manifested through its internal systems interdependence. The negative impact of such interdependence was demonstrated through the 2011 Fukushima Daiichi nuclear disaster. As such, there is a critical need for new strategies to overcome the limitations of current risk assessment techniques (e.g. the use of static event and fault tree schemes), particularly through simulation of the nonlinear dynamic feedback mechanisms between the different NPP systems/components. As the first and key step towards developing an integrated NPP dynamic probabilistic risk assessment platform that can account for such feedback mechanisms, the current study adopts a system dynamics simulation approach to model the thermal dynamic processes in: the reactor core; the secondary coolant system; and the pressurized water reactor. The reactor core and secondary coolant system parameters used to develop system dynamics models are based on those of the Palo Verde Nuclear Generating Station. These three system dynamics models are subsequently validated, using results from published work, under different system perturbations including the change in reactivity, the steam valve coefficient, the primary coolant flow, and others. Moving forward, the developed system dynamics models can be integrated with other interacting processes within a NPP to form the basis of a dynamic system-level (systemic) risk assessment tool.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1616-1622
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• 2022

Selenium has been identified as an element of interest for the safety assessment of a deep geological repository (DGR) for used nuclear fuel. In Canada, groundwaters at DGR depths in sedimentary rocks have been observed to have a high ionic strength. This paper examines the sorption behavior of Se(-II) onto illite, MX-80 bentonite, Queenston shale, and argillaceous limestone in Na-Ca-Cl solutions of varying ionic strength (0.1-6 mol/kgw (m)) and across a pH range of 4-9. Little ionic strength dependence for Se(-II) sorption onto all solids was observed except that sorption at high ionic strength (6 m) was generally slightly lower than sorption at low ionic strength (0.1 m). Illite and MX-80 exhibited the expected results for anion sorption, while shale and limestone exhibited more constant sorption across the pH range tested. A non-electrostatic surface complexation model successfully predicted sorption of Se(-II) onto illite and MX-80 using the formation of an inner-sphere surface complex and an outer-sphere surface complex. Optimized values for the formation reactions of these surface species were proposed.

• Structural Engineering and Mechanics
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• 제7권4호
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• pp.413-432
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• 1999

A macro-element model is developed to account for shear deformation and bond slip of reinforcement bars in the beam-column joint region of reinforced concrete structures. The joint region is idealized by two springs in series, one representing shear deformation and the other representing bond slip. The softened truss model theory is adopted to establish the shear force-shear deformation relationship and to determine the shear capacity of the joint. A detailed model for the bond slip of the reinforcing bars at the beam-column interface is presented. The proposed macro-element model of the joint is validated using available experimental data on beam-column connections representing exterior joints in ductile and nonductile frames.