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RISS 인기검색어
- 검색키워드
- 저자 : S.A.H. FEGHHI (검색결과 4 건)
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S. Jafarikia,S.A.H. FEGHHI 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.1
The purpose of this paper is to study the source term behavior after severe accidents by using a semikineticmodel for simulation and calculation of in-containment activity. The reactor containment specificationand the safety features of the containment under different accident conditions play a great rolein evaluating the in-containment activity. Assuming in-vessel and instantaneous release of radioactivity into the containment, the behavior of incontainmentisotopic activity is studied for noble gasses (Kr and Xe) and the more volatile elements ofiodine, cesium, and aerosols such as Te, Rb and Sr as illustrative examples of source term release underLOCA conditions. The results of the activity removal mechanisms indicates that the impact of volumetricleakage rate for noble gasses is important during the accident, while the influence of deposition on thecontainment surfaces for cesium, mainly iodine isotopes and aerosol has the largest contribution inremoval of activity during evolution of the accident.
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E. Nazemi,S.A.H. FEGHHI,G.H. Roshani,R. Gholipour Peyvandi,S. Setayeshi 한국원자력학회 2016 Nuclear Engineering and Technology Vol.48 No.1
Void fraction is an important parameter in the oil industry. This quantity is necessary forvolume rate measurement in multiphase flows. In this study, the void fraction percentagewas estimated precisely, independent of the flow regime in gaseliquid two-phase flows byusing g-ray attenuation and a multilayer perceptron neural network. In all previous studiesthat implemented a multibeam g-ray attenuation technique to determine void fractionindependent of the flow regime in two-phase flows, three or more detectors were usedwhile in this study just two NaI detectors were used. Using fewer detectors is of advantagein industrial nuclear gauges because of reduced expense and improved simplicity. In thiswork, an artificial neural network is also implemented to predict the void fraction percentageindependent of the flow regime. To do this, a multilayer perceptron neuralnetwork is used for developing the artificial neural network model in MATLAB. Therequired data for training and testing the network in three different regimes (annular,stratified, and bubbly) were obtained using an experimental setup. Using the techniquedeveloped in this work, void fraction percentages were predicted with mean relative errorof <1.4%.
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Nazemi, E.,Feghhi, S.A.H.,Roshani, G.H.,Gholipour Peyvandi, R.,Setayeshi, S. Korean Nuclear Society 2016 Nuclear Engineering and Technology Vol.48 No.1
Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.
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Z. GHOLAMZADEH,S.A.H. FEGHHI,S.M. MIRVAKILI,A. JOZE-VAZIRI,M. ALIZADEH 한국원자력학회 2015 Nuclear Engineering and Technology Vol.47 No.7
The use of subcritical aqueous homogenous reactors driven by accelerators presents anattractive alternative for producing 99Mo. In this method, the medical isotope productionsystem itself is used to extract 99Mo or other radioisotopes so that there is no need toirradiate common targets. In addition, it can operate at much lower power compared to atraditional reactor to produce the same amount of 99Mo by irradiating targets. In this study,the neutronic performance and 99Mo, 89Sr, and 131I production capacity of a subcriticalaqueous homogenous reactor fueled with low-enriched uranyl nitrate was evaluated usingthe MCNPX code. A proton accelerator with a maximum 30-MeV accelerating power wasused to run the subcritical core. The computational results indicate a good potential for themodeled system to produce the radioisotopes under completely safe conditions because ofthe high negative reactivity coefficients of the modeled core. The results show thatapplication of an optimized beam window material can increase the fission power of theaqueous nitrate fuel up to 80%. This accelerator-based procedure using low enricheduranium nitrate fuel to produce radioisotopes presents a potentially competitive alternativein comparison with the reactor-based or other accelerator-based methods. This systemproduces ~1,500 Ci/wk (~325 6-day Ci) of 99Mo at the end of a cycle.
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