• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.70-73
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• 1992

This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathematically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTNI Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Nuclear Engineering and Technology
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• v.45 no.7
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• pp.827-838
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• 2013

Interaction layer growth between U-Mo alloy fuel particles and Al in a dispersion fuel is a concern due to the volume expansion and other unfavorable irradiation behavior of the interaction product. To reduce interaction layer (IL) growth, a small amount of Si is added to the Al. As a result, IL growth is affected by the Si content in the Al matrix. In order to predict IL growth during fabrication and irradiation, empirical models were developed. For IL growth prediction during fabrication and any follow-on heating process before irradiation, out-of-pile heating test data were used to develop kinetic correlations. Two out-of-pile correlations, one for the pure Al matrix and the other for the Al matrix with Si addition, respectively, were developed, which are Arrhenius equations that include temperature and time. For IL growth predictions during irradiation, the out-of-pile correlations were modified to include a fission-rate term to consider fission enhanced diffusion, and multiplication factors to incorporate the Si addition effect and the effect of the Mo content. The in-pile correlation is applicable for a pure Al matrix and an Al matrix with the Si content up to 8 wt%, for fuel temperatures up to $200^{\circ}C$, and for Mo content in the range of 6 - 10wt%. In order to cover these ranges, in-pile data were included in modeling from various tests, such as the US RERTR-4, -5, -6, -7 and -9 tests and Korea's KOMO-4 test, that were designed to systematically examine the effects of the fission rate, temperature, Si content in Al matrix, and Mo content in U-Mo particles. A model converting the IL thickness to the IL volume fraction in the meat was also developed.

• Wind and Structures
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• v.19 no.6
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• pp.687-708
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• 2014

The performance of the $k-{\varepsilon}$ and $k-{\omega}$ two-equation turbulence models was investigated in computational simulations of the neutrally stratified atmospheric boundary layer developing above various terrain types. This was achieved by using a proposed methodology that mimics the experimental setup in the boundary layer wind tunnel and accounts for a decrease in turbulence parameters with height, as observed in the atmosphere. An important feature of this approach is pressure regulation along the computational domain that is additionally supported by the nearly constant turbulent kinetic energy to Reynolds shear stress ratio at all heights. In addition to the mean velocity and turbulent kinetic energy commonly simulated in previous relevant studies, this approach focuses on the appropriate prediction of Reynolds shear stress as well. The computational results agree very well with experimental results. In particular, the difference between the calculated and measured mean velocity, turbulent kinetic energy and Reynolds shear stress profiles is less than ${\pm}10%$ in most parts of the computational domain.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.139-145
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• 2018

In this paper, we propose the methodology and system to show weather information to spatial system. When using the spatial information system, it is easy and convenient to show information such as target location, mission contents, enemy threats and so on. However, drawing 1-dimensional weather information on 3-dimensional space in spatial information system is hard task. To fuse data, we need to add a spatial layer including weather information to spatial layers and perform space modeling for showing weather information as spatial data in a virtual space. The virtual space is shown by receiving meteorological data and then changing in real time through weather database linkage.

• Journal of the Microelectronics and Packaging Society
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• v.25 no.4
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• pp.59-66
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• 2018

In this paper, we analyzed the usefulness of single-structured printed circuit board (PCB) modeling by using numerical analysis to model the PCB structure applied to a package for semiconductor purposes and applying modeling assuming a single structure. PCBs with circuit layer of 3rd and 4th were used for analysis. In addition, measurements were made on actual products to obtain material characteristics of a single structure PCB. The analysis results showed that if the PCB was modeled in a single structure compared to a multi-layered structure, the warpage analysis results resulting from modeling the PCB structure would increase and there would be a significant difference. In addition, as the circuit layer of the PCB increased, the mechanical properties of the PCB, the elastic coefficient and inertia moment of the PCB increased, decreasing the package's warpage.

• Wind and Structures
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• v.6 no.2
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• pp.91-106
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• 2003

The paper presents the results of 1:50 geometrical scale laboratory modeling of wind-induced point pressure on the roof of the Texas Tech University (TTU) test building. The nominal (prevalent at the TTU site) wind and two bounding (low and high turbulence) flows were simulated in a boundary-layer wind tunnel at Colorado State University. The results showed significant increase in the pressure peak and standard deviation with an increase in the flow turbulence. It was concluded that the roof mid-plane pressure sensitivity to the turbulence intensity was the cause of the previously reported field-laboratory mismatch of the fluctuating pressure, for wind normal and $30^{\circ}$-off normal to the building ridge. In addition, it was concluded that the cornering wind mismatch in the roof corner/edge regions could not be solely attributed to the wind-azimuth-independent discrepancy between the turbulence intensity of the approach field and laboratory flows.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.

• Steel and Composite Structures
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• v.30 no.5
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• pp.417-432
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• 2019

This paper presents the results of axial compression testing and numerical modeling on reinforced concrete columns (RCC) with normal concrete (NC) and high-strength concrete (HSC), RCC confined by glass-fiber reinforced plastic pipes (GRP) casing as well as carbon fiber reinforced polymer (CFRP), The major parameters evaluated in the experiments were the effects of concrete type, GRP casing and CFRP wrapping, as well as the number of CFRP layers. 12 cylindrical RCC ($150{\times}600mm$) were prepared and divided into two groups, NC and HSC. Each group was divided into two parts; with and without GRP casing. In each part, one column was without CFRP strengthening layer, a column was wrapped with one CFRP layer and another column with two CFRP layers. All columns were tested under concentrated compression load. Numerical modeling was performed using ABAQUS software and the results of which were compared with experimental findings. A good agreement was found between the results. Results indicated that the utilization of CFRP wrapping and GRP casing improved compression capacity and ductility of RCC. The addition of one and two layer-FRP wrapping increased capacity in the NC group to an average of 18.5% and 26.5% and in the HSC group to an average of 10.2% and 24.8%. Meanwhile, the utilization of GRP casing increased the capacity of the columns by 3 times in the NC group and 2.38 times in the HSC group. The results indicated that although both CFRP wrapping and GRP casing increased confinement, the GRP casing gave more increase capacity and ductility of the RCC due to higher confinement. Furthermore, the confinement effect was higher on NC group.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.