• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.738-740
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• 2003

A method for identifying the released region and time of Asian dust using the long-range inverse transport model that traces the wind field in the backward direction from positions where Asian dust was observed is described. Initial conditions for the inverse transport simulation were obtained from the time variation of the density distribution of the suspended particulate matter (SPM) in the air measured at various places in Japan. Based on a concentration of trajectories of the air mass computed by the inverse transport model, the source region of Asian dust clouds observed at meteorological stations in Japan on March 17 to 18, 2002 was estimated. As a result, it was found that dust particles were released at about 6h on March 15 in the neighborhood of Inner Mongolian Autonomous Region.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1358-1367
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• 2017

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector responses (using the adjoint transport solution) with measured responses. DIMP performs well with forward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search volume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

• Ocean and Polar Research
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• v.21 no.2
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• pp.87-97
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• 1999

To estimate absolute transports by advection in the southwestern East Sea (Japan Sea), an inverse method was applied to CTD data obtained in July 1993. The relative velocities are calculated using the thermal wind equation. The inverse model was formulated to obtain a reference velocity based on the mass conservation in each of four vertical layers within a region enclosed by hydrographic sections and the coastal boundary. The flow patterns in the surface layer are clockwise and anti-clockwise in the regions south and northwest of Ulleung Island, respectively, and a strong northward flow appears in between them. In the second layer, the flow fields are generally weak. The inverse calculation yields the southward flow along the coast, and this suggests that the subsurface low salinity water in the Ulleung Basin is supplied by the southward transport along the east coast of Korea.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.414-422
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• 2021

The aim of this work considers a second order point reactor kinetics model based on the P1 approximation of transport theory, called in this work as P1 point reactor model. The P1 point reactor model implicitly considers the time derivative of the neutron source which has not been thus considered previously. The inverse method to calculate the reactivity in nuclear reactors -chosen because its high accuracy- Matrix Formulation. The numerical results shown that the Matrix Formulation for the reactivity estimation constitutes a method with insignificant calculation errors.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1465-1474
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• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• Journal of Soil and Groundwater Environment
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• v.10 no.3
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• pp.24-31
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• 2005

This study presents a contaminant transport model suitable for a 2-dimensional heterogeneous aquifer with multiple contaminant sources. It uses a streamline simulation, which transforms a multi-dimensional problem into multiple 1dimensional problems. It runs flow simulation, streamline tracking, and calculation of contaminant concentrations by turns. The model is verificated with a Visual MODFLOW by comparing contaminant concentration distributions and breakthrough curves at an observation well. Due to its fast simulation, it can be applied to time consuming simulations such as in a fine-grided aquifer, an inverse modeling and other applications.

• Geomechanics and Engineering
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• v.29 no.1
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• pp.53-63
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• 2022

Simplified analytical solutions are developed for the dynamic analyses of an axially loaded pile foundation embedded in a transverse-isotropic, fluid-filled, poro-visco-elastic soil with rigid substratum. The pile is modeled as a viscoelastic Rayleigh-Love rod, while the surrounding soil is regarded as a transversely isotropic, liquid-saturated, viscoelastic, porous medium of which the mechanical behavior is represented by the Boer's poroelastic media model and the fractional derivative model. Upon the separation of variables, the frequency-domain responses for the impedance function of the pile top, and the vertical displacement and the axial force along the pile shaft are gained. Then by virtue of the convolution theorem and the inverse Fourier transform, the time-domain velocity response of the pile head is derived. The presented solutions are validated, compared to the existing solution, the finite element model (FEM) results, and the field test data. Parametric analyses are made to show the effect of the soil anisotropy and the excitation frequency on the pile-soil dynamic responses.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.684-689
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• 2003

One field identified by an inverse method is one of multiple candidate solutions those are independently obtained through a specific estimation technique. While averaging of optimized fields can provide a better description of the spatial feature of an unknown field, it deteriorates the flow and transport characteristics of the optimized fields. As a result, the averaged field is not suited for modeling aquifer performances. Based on genetic algorithm, an optimal field synthesis technique is developed, which combines diversely optimized fields into a refined group of fields. Each field in the population is paired, and a sub-region of each field is exchanged by crossover operation to create a group of synthesized fields of enhanced modeling capability. The population of the fields is evolved till the synthesized fields become sufficiently similar. Applications of the optimal field synthesis to synthetic cases indicate that the objective functions of the fields assessing the modeling capabilities are further reduced after the optimal field synthesis. The identified fields from various inverse techniques may yield a range of modeling results under varied flow situations. The uncertainty is narrowed down through the optimal field synthesis and the associated modeling results converge on that of the reference field. The developed inverse modeling facilitates the construction of a reliable simulation model and hence trustworthy predictions of the future performances.

• Korean Chemical Engineering Research
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• v.55 no.5
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• pp.638-645
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• 2017

A model for predicting the transport velocity was proposed using the correlation of the particle entrainment rate in the gas fluidized bed. The emptying time method was simulated using correlations of Choi et al. and Li and Kato. In order to exclude the influence of the unit of the gas velocity, the dimensionless velocity obtained by dividing the gas velocity by the terminal velocity was used as the value of the x-axis. The inverse of the particle entrainment rate was used as the value of the y-axis. When increasing the gas velocity, the non-dimensional velocity, at which the decreasing slope of the y-value is 0.398 [$m^2s/kg$] in absolute value, was considered as the transport velocity. The transport velocity predicted by the model was in good agreement even at high temperature and high pressure.

• Journal of Radiation Protection and Research
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• v.42 no.4
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• pp.212-221
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• 2017

Background: This study aims to calculate detector positions as a design of a radioactive source localizing radiation portal monitor (RPM) system using an improved genetic algorithm. Materials and Methods: To calculate of detector positions for a source localizing RPM system optimization problem is defined. To solve the problem, a modified iterative genetic algorithm (MIGA) is developed. In general, a genetic algorithm (GA) finds a globally optimal solution with a high probability, but it is not perfect at all times. To increase the probability to find globally optimal solution rather, a MIGA is designed by supplementing the iteration, competition, and verification with GA. For an optimization problem that is defined to find detector positions that maximizes differences of detector signals, a localization method is derived by modifying the inverse radiation transport model, and realistic parameter information is suggested. Results and Discussion: To compare the MIGA and GA, both algorithms are implemented in a MATLAB environment. The performance of the GA and MIGA and that of the procedures supplemented in the MIGA are analyzed by computer simulations. The results show that the iteration, competition, and verification procedures help to search for globally optimal solutions. Further, the MIGA is more robust against falling into local minima and finds a more reliably optimal result than the GA. Conclusion: The positions of the detectors on an RPM for radioactive source localization are optimized using the MIGA. To increase the contrast of the measurements from each detector, a relationship between the source and the detectors is derived by modifying the inverse transport model. Realistic parameters are utilized for accurate simulations. Furthermore, the MIGA is developed to achieve a reliable solution. By utilizing results of this study, an RPM for radioactive source localization has been designed and will be fabricated soon.