• Nuclear Engineering and Technology
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• v.33 no.4
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• pp.441-456
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• 2001

ABB-CE＇s regionalization methodology for the core inlet flow distribution map is reviewed. This methodology merges the test data of fuel assembly locations which are either in symmetry or strongly correlated with others. It increases the number of available test data for each regional flow factor It makes up effectively for the deficiency due to limited number of test data. It also contributes to making the core inlet flow distribution smoother not only locally but also over the entire core, and to relieving the impacts of test errors that may happen due to some do- calibrated local pressure measurement taps. As a result, the core inlet How distribution data becomes more statistically useful and thus the conservatism involved in handling the core inlet flow factors for the thermal margin analysis is expected to be reduced. Meanwhile, the regionalized map may lose the unique local characteristics in core inlet flow distribution too much. By an alternative approach introduced in the present work, it is shown that such a disadvantage can be mitigated somewhat if the engineering judgement is made more

• The Journal of Engineering Geology
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• v.28 no.1
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• pp.35-45
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• 2018

Imaging technologies are applied at various geological scales including pore scale, core scale and intermediate scale in order to characterize pore space of rocks as well as to map the fluid distribution in porous media. This technical report presents experimental results using core-flooding apparatus suited with imaging technology. Three different core samples, that are homogeneous, fractured and heterogeneous cores, were used to assess the two-phase fluid migration behavior as $CO_2$ displaces resident brine. We show that imaging technology can be effective in characterizing salt-precipitation, capillary pressure and spatio-temporal variation of trapping mechanisms.

• Journal of Korean Society of Forest Science
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• v.96 no.5
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• pp.591-601
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• 2007

Spatial information on forest biomass is an important factor to evaluate the capability of forest as a carbon sequestrator and is a core independent variable required to drive models which describe ecological processes such as carbon budget, hydrological budget, and energy flow. The objective of this study is to understand the relationship between satellite image and field data, and to quantitatively estimate and map the spatial distribution of forest biomass. Landsat Enhanced Thematic Mapper (ETM+) derived vegetation indices and field survey data were applied to estimate the biomass distribution of mountainous forest located in Gwangneung Experimental Forest (230 ha). Field survey data collected from the ground plots were used as the dependent variable, forest biomass, while satellite image reflectance data (Band 1~5 and Band 7), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and RVI (Ratio Vegetation Index) were used as the independent variables. The mean and total biomass of Gwangneung catchment area were estimated to be about 229.5 ton/ha and $52.8{\times}10^3$ tons respectively. Regression analysis revealed significant relationships between the measured biomass and Landsat derived variables in both of deciduous forest ($R^2=0.76$, P < 0.05) and coniferous forest ($R^2=0.75$, P < 0.05). However, there still exist many uncertainties in the estimation of forest ecosystem parameters based on vegetation remote sensing. Developing remote sensing techniques with adequate filed survey data over a long period are expected to increase the estimation accuracy of spatial information of the forest ecosystem.