• Geomechanics and Engineering
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• v.37 no.4
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• pp.341-358
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• 2024

This paper reports several plane-strain trapdoor tests conducted to investigate the effects of reinforcement on soil arching development under localized surface loading with a loading plate width three times the trapdoor width. An analogical soil composed of aluminum rods with three different diameters was used as the backfill and Kraft paper with two different stiffness values was used as the reinforcement material. Four reinforcement arrangements were investigated: (1) no reinforcement, (2) one low stiffness reinforcement R1, (3) one high stiffness reinforcement R2, and (4) two low stiffness reinforcements R1 with a backfill layer in between. The stiffness of R2 was approximately twice that of R1; therefore, two R1 had approximately the same total stiffness as one R2. Test results indicate that the use of reinforcement minimized soil arching degradation under localized surface loading. Soil arching with reinforcement degraded more at unloading stages as compared to that at loading stages. The use of stiffer reinforcement had the advantages of more effectively minimizing soil arching degradation. As compared to one high stiffness reinforcement layer, two low stiffness reinforcement layers with a backfill layer of certain thickness in between promoted soil arching under localized surface loading. Due to different states of soil arching development with and without reinforcement, an analytical multi-stage soil arching model available in the literature was selected in this study to calculate the average vertical pressures acting on the trapdoor or on the deflected reinforcement section under both the backfill self-weight and localized surface loading.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.5
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• pp.537-545
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• 2005

A new dispersion model for dense gas is constructed in the Lagrangian framework. Prediction of concentration by the proposed model is compared with measure data obtained in the experiment conducted in Thorney Island in 1984. Two major effects of dense gas dispersion, gravity slumping and stratification effect, are successfully incorporated into LDM (Lagrangian dense gas model). Entrainment effect is naturally modelled by introducing stochastic dispersion model with the effect of turbulence suppression by stratification. Not only various releasing conditions but also complex terrain can be extended to, although proposed model is appropriate for flat terrain.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1749-1758
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• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.354-357
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• 2021

Infants communicate their feelings and needs to the outside world through non-verbal methods such as crying and displaying diverse facial expressions. However, inexperienced parents tend to decode these non-verbal messages incorrectly and take inappropriate actions, which might affect the bonding they build with their babies and the cognitive development of the newborns. In this paper, we propose an aural-visual two-stream based infant cry recognition system to help parents comprehend the feelings and needs of crying babies. The proposed system first extracts the features from the pre-processed audio and video data by using the VGGish model and 3D-CNN model respectively, fuses the extracted features using a fully connected layer, and finally applies a SoftMax function to classify the fused features and recognize the corresponding type of cry. The experimental results show that the proposed system classification exceeds 0.92 in F1-score, which is 0.08 and 0.10 higher than the single-stream aural model and single-stream visual model.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.69-73
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• 2016

We use the non-stationary three dimensional two-layer outer gap model to explain gamma-ray emissions from a pulsar magnetosphere. We found out that for some pulsars like the Geminga pulsar, it was hard to explain emissions above a level of around 1 GeV. We then developed the model into a non-stationary model. In this model we assigned a power-law distribution to one or more of the spectral parameters proposed in the previous model and calculated the weighted phase-averaged spectrum. Though this model is suitable for some pulsars, it still cannot explain the high energy emission of the Geminga pulsar. An Inverse-Compton Scattering component between the primary particles and the radio photons in the outer magnetosphere was introduced into the model, and this component produced a sufficient number of GeV photons in the spectrum of the Geminga pulsar.

• Journal of computational fluids engineering
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• v.2 no.2
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• pp.1-8
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• 1997

Two versions of anisotropic k-ε turbulence model are incorporated in the modified k-ε model of Sohn et al. to avoid the need for the experimental normal stress value in the model and applied to convergent and divergent flows with strong and adverse pressure gradients in the plane of symmetry of a body of revolution. The models are the nonlinear k-ε model of Speziale and the anisotropic model of Nisizima & Yoshizawa. All of the models yield satisfactory results for relatively complex flow on a plane-of-symmetry boundary layer. The results of the models are compared with those results of experimental normal stress value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.459-466
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• 2006

Numerical values of thermodynamic properties such as temperature, pressure, dryness, volume, enthalpy and entropy are required in numerical analysis on evaluating the thermal performance. But the steam table itself cannot be used without modelling. From this point of view the neural network with function approximation characteristics can be an alternative. the multi-layer neural networks were made for saturated vapor region and superheated vapor region separately. For saturated vapor region the neural network consists of one input layer with 1 node, two hidden layers with 10 and 20 nodes each and one output layer with 7 nodes. For superheated vapor region it consists of one input layer with 2 nodes, two hidden layers with 15 and 25 nodes each and one output layer with 3 nodes. The proposed model gives very successful results with ${\pm}0.005%$ of percentage error for temperature, enthalpy and entropy and ${\pm}0.025%$ for pressure and specific volume. From these successful results, it is confirmed that the neural networks could be powerful method in function approximation of the steam table.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.343-356
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• 2007

This paper explored the characteristics of the interannual sea surface temperature (SST) variability in the equatorial Pacific by analyzing the simulated data from a newly coupled general circulation model (CGCM). The CGCM simulates well the realistic ENSO variability as well as the mean climatologies including SST, seasonal cycle, precipitation, and subsurface structures. It is argued that the zonal gradient of SST in the equatorial Pacific is responsible for the over-energetic SST variability near the equatorial western boundary in the model. This variability could also be related to the strong westward propagation of SST anomalies which resulted from the enhanced the zonal advection feedback. The simple two-strip model supports this by sensitivity tests. Analysis of the relationship between zonal mean thermocline depth and NINO3 SST index suggested that the ENSO variability is controlled by the recharge-discharge oscillator of the model. The lead-lag regression result reveals that heat buildup process in the western equatorial Pacific associated with the increase of the barrier layer thickness (BLT) is a precedent condition for El $Ni\widetilde{n}o$ to develop.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.4
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• pp.361-372
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• 2019

The flow pattern of air layers and skin-friction drag reduction by air injection are investigated to find the suitable multiphase flow model using unstructured finite-volume CFD solver for the Reynolds-averaged Navier-Stokes equations. In the present computations, two different multiphase flow modeling approaches, such as the Volume of Fluid (VOF) and the Eulerian Multi-Phase (EMP), are adopted to investigate their performances in resolving the two-phase flow pattern and in estimating the frictional drag reduction. First of all, the formation pattern of air layers generated by air injection through a circular opening on the bottom of a flat plate are investigated. These results are then compared with those of MMkiharju's experimental results. Subsequently, the quantitative ratios of skin-friction drag reduction including the behavior of air layers, within turbulent boundary layers in large scale and at high Reynolds number conditions, are investigated under the same conditions as the model test that has been conducted in the US Navy's William B. Morgan Large Cavitation Channel (LCC). From these results, it is found that both VOF and EMP models have similar capability and accuracy in capturing the topology of ventilated air cavities so called'air pockets and branches'. However, EMP model is more favorable in predicting quantitatively the percentage of frictional drag reduction by air injection.

• Atmosphere
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• v.26 no.3
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• pp.435-444
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• 2016

In spite of considerable progress in the recent decades, there still remain large uncertainties in numerical cloud models. In this study, effects of uncertainty in terminal velocity of graupel on cloud simulation are investigated. For this, a two-dimensional bin microphysics cloud model is employed, and deep convective clouds are simulated under idealized environmental conditions. In the sensitivity experiments, the terminal velocity of graupel is changed to twice and half the velocity in the control experiment. In the experiment with fast graupel terminal velocity, a large amount of graupel mass is present in the lower layer. On the other hand, in the experiment with slow graupel terminal velocity, almost all graupel mass remains in the upper layer. The graupel size distribution exhibits that as graupel terminal velocity increases, in the lower layer, the number of graupel particles increases and the peak radius in the graupel mass size distribution decreases. In the experiment with fast graupel terminal velocity, the vertical velocity is decreased mainly due to a decrease in riming that leads to a decrease in latent heat release and an increase in evaporative cooling via evaporation, sublimation, and melting that leads to more stable atmosphere. This decrease in vertical velocity causes graupel particles to fall toward the ground easier. By the changes in graupel terminal velocity, the accumulated surface precipitation amount differs up to about two times. This study reveals that the terminal velocity of graupel should be estimated more accurately than it is now.