• Journal of Radiation Industry
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• v.17 no.4
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• Food Engineering Progress
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• v.14 no.3
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• pp.208-216
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• 2010

Lab scale experiments were conducted in order to assess the applicability of $CaCO_{3}$-alginate beads as neutralizer for the high cell density cultivation and prepare the direct vat inoculation cultures of isolated sourdough lactic acid bacteria. With increasing the amount of bead and decreasing the diameter of bead in acidic solution, the neutralizing effect of $CaCO_{3}$-alginate bead became higher. In batch process with $CaCO_{3}$-alginate beads, Lactobacillus amylovorus DU-21 isolated from sourdough showed the highest viable cell counts and optical density in MRS broth. The values of viable cell counts and optical density were 9.996 log CFU/mL and 3.97, respectively. Experiments on the conditions which increase viability during lyophilization were carried out and the following results were obtained; 15% glycerol revealed the high cryoprotective effect on the concentrated cultures during lyophilization among the two cryoprotective agents. Consequently, $CaCO_{3}$-alginate beads and 15% glycerol were found to be useful not only to cultivate Lactobacillus amylovorus DU-21 but also to preserve strain.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.