• Computers and Concrete
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• v.23 no.2
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• pp.145-153
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• 2019

Adaptive schemes are constructed in this paper for modeling the effective chloride diffusion coefficient of cement-based materials (paste and concrete). Based on the polarization approximations for the effective conductivity of isotropic multicomponent materials, we develop some fitting procedures to include more information about the materials, to improve the accuracy of the scheme. The variable reference parameter of the approximation involves a few free scalars, which are determined through the available numerical or experimental values of the macroscopic chloride diffusion coefficient of cement paste or concrete at some volume proportions of the component materials. The various factors that affect the chloride diffusivity of cement-based material (porous material structure, uncertainty of value of the chloride diffusion coefficient in water-saturated pore spaces, etc.) may be accounted to make the predictions more accurate. Illustrations of applications are provided in a number of examples to show the usefulness of the approach.

• Journal of Drive and Control
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• v.16 no.2
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• pp.80-90
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• 2019

Fuel cell hybrid electric vehicle is an attractive solution to reduce pollutants, such as noise and carbon dioxide emission. This study presents an approach for energy management and control algorithm based on energetic macroscopic representation for a fuel cell hybrid electric vehicle that is powered by proton exchange membrane fuel cell, battery and supercapacitor. First, the detailed model of the fuel cell hybrid electric vehicle, including fuel cell, battery, supercapacitor, DC-DC converters and powertrain system, are built on the energetic macroscopic representation. Next, the power management strategy was applied to manage the energy among the three power sources. Moreover, the control scheme that was based on back-stepping sliding mode control and inversed-model control techniques were deduced. Simulation tests that used a worldwide harmonized light vehicle test procedure standard driving cycle showed the effectiveness of the proposed control method.

• Architectural research
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• v.22 no.4
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• pp.155-162
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• 2020

Numerous scholars have explored the modeling, control, and optimization of energy systems in buildings, offering new insights about technology and environments that can advance industry innovation. Eye trackers deliver objective eye-gaze data about visual and attentional processes. Due to its flexibility, accuracy, and efficiency in research, eye tracking has a control scheme that makes measuring rapid eye movement in three-dimensional space possible (e.g., virtual reality, augmented reality). Because eye movement is an effective modality for digital interaction with a virtual environment, tracking how users scan a visual field and fix on various digital objects can help designers optimize building environments and materials. Although several scholars have conducted Virtual Reality studies in three-dimensional space, scholars have not agreed on a consistent way to analyze eye tracking data. We conducted eye tracking experiments using objects in three-dimensional space to find an objective way to process quantitative visual data. By applying a 12 × 12 grid framework for eye tracking analysis, we investigated how people gazed at objects in a virtual space wearing a headmounted display. The findings provide an empirical base for a standardized protocol for analyzing eye tracking data in the context of virtual environments.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1570-1578
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• 2022

During a severe accident, steam generator (SG) tubes undergo rapid changes in the pressure and temperature. Therefore, an appropriate creep model to predict a short term creep damage is essential. In this paper, a novel creep model for Alloy 690 SG tube material was proposed. It is based on the theta (θ) projection method that can represent all three stages of the creep process. The original θ projection method poses a limitation owing to its inability to represent experimental creep curves for SG tube materials for a large strain rate in the tertiary creep region. Therefore, a new modified θ projection method is proposed; subsequently, a master curve for Alloy 690 SG material is also proposed to optimize the creep model parameters, θ_i (i = 1-5). To adapt the implicit creep scheme to the finite element code, a partial derivative of incremental creep with respect to the stress is necessary. Accordingly, creep model parameters with a strictly linear relationship with the stress and temperature were proposed. The effectiveness of the model was validated using a commercial finite element analysis software. The creep model can be applied to evaluate the creep rupture behavior of SG tubes in nuclear power plants.

• Journal of Korean Association for Spatial Structures
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• v.23 no.2
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• pp.79-90
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• 2023

Existing reinforced concrete (RC) frame buildings have seismic vulnerabilities because of seismically deficient details. In particular, since cumulative damage caused by successive earthquakes causes serious damage, repair/retrofit rehabilitation studies for successive earthquakes are needed. This study investigates the repair effect of fiber-reinforced polymer jacketing system for the seismically-vulnerable building structures under successive earthquakes. The repair modeling method developed and validated from the previous study was implemented to the building models. Additionally, the main parameters of the FRP jacketing system were selected as the number of FRP layers associated with the confinement effects and the installation location. To define the repair effects of the FRP jacketing system with the main parameters, this study conducted nonlinear time-history analyses for the building structural models with the various repairing scenarios. Based on this investigation, the repair effects of the damaged building structures were significantly affected by the damage levels induced from the mainshocks regardless of the retrofit scenarios.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1083-1091
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• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.2
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• pp.95-102
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• 2002

Spatial interpolation has become a common procedure in converting temperature forecasts and observations at irregular points for use in regional scale ecosystem modeling and the model based decision support systems for resource management. Neglection of terrain effects in most spatial interpolations for short term temperatures may cause erroneous results in mountainous regions, where the observation network hardly covers full features of the complicated terrain. A spatial interpolation model for daytime hourly temperature was formulated based on error analysis of unsampled site with respect to the site topography. The model has a solar irradiance correction scheme in addition to the common backbone of the lapse rate - corrected inverse distance weighting. The solar irradiance scheme calculates the direct, diffuse and reflected components of shortwave radiation over any surfaces based on the sun-slope geometry and compares the sum with that over a reference surface. The deviation from the reference radiation is used to calculate the temperature correction term by an empirical conversion formula between the solar energy and the air temperature on any sloped surfaces at an hourly time scale, which can be prepared seasonally for each land cover type. When this model was applied to a 14 km by 22 km mountainous region at a 10 m horizontal resolution, the estimated hourly temperature surfaces showed a better agreement with the observed distribution than those by a conventional method.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.40-51
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• 2014

This study aims to investigate urban inundation considering building footprints based on dual-drainage scheme. For this purpose, LiDAR data is cultivated to generate two original data set in terms of DEM with $1{\times}1$ meter and building layer of the study drainage area in Seoul and then the building layer is overlapped as vector polygon with the mesh data with the same size as DEM. Then, terrain data for modeling were re-sampled to reduce resolution as $10{\times}10$ meters. As results, the simulated depth without considering building footprints has a tendency to underestimate the inundation depth compared to observed data analized by CCTV imagery. Otherwise, the simulation result considering building footprints revealed definitely higher fitness. The difference of inundation depth came from the variation of inundation volume which was relevant to inundation extent. If the building footprints are enlarged, the possible inundation depth is increased, which results in being inundation depth higher because hydrological conditions such as rainfall depth are conservational. Otherwise, according to comparison of inundation extents, there were no significant difference but the case of considering building footprint was revealed slightly higher fitness. Thus, it is concluded that the considering building footprint for inundation analysis of urban watershed should be required to improve simulation accuracy synthetically.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.761-772
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• 2008

The object of this study is to develop the model that solves the numerically difficult problems in hydraulic engineering and to demonstrate the applicability of this model by means of various test examples, such as, verification in the gradually varied unsteady condition, three steady flow problems with the change of bottom slope with exact solution, and frictional bed with analytical solution. The governing equation of this model is the integral form of the Saint-Venant equation satisfying the conservation laws, and finite volume method with the Riemann solver is used. The evaluation of the mass and momentum flux with the HLL Riemann approximate solver is executed. MUSCL-Hancock scheme is used to achieve the second order accuracy in space and time. This study introduce the new and simple technique to discretize the source terms of gravity and hydrostatic pressure force due to longitudinal width variation for the balance of quantity between nonlinear flux and source terms. The results show that the developed model's implementation is accurate, robust and highly stable in various flow conditions with source terms, and this model is reliable for one-dimensional applications in hydraulic engineering.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.