• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.269-277
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• 2019

Using the non-local elasticity theory, Timoshenko beam model is developed to study the non- local buckling of Triple-walled carbon nanotubes (TWCNTs) embedded in an elastic medium under axial compression. The chirality and small scale effects are considered. The effects of the surrounding elastic medium based on a Winkler model and van der Waals' (vdW) forces between the inner and middle, also between the middle and outer nanotubes are taken into account. Considering the small-scale effects, the governing equilibrium equations are derived and the critical buckling loads under axial compression are obtained. The results show that the critical buckling load can be overestimated by the local beam model if the small-scale effect is overlooked for long nanotubes. In addition, significant dependence of the critical buckling loads on the chirality of zigzag carbon nanotube is confirmed. Furthermore, in order to estimate the impact of elastic medium on the non-local critical buckling load of TWCNTs under axial compression, the use of these findings are important in mechanical design considerations, improve and reinforcement of devices that use carbon nanotubes.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.778-789
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• 2021

Recently, various lightweight methods for using Convolutional Neural Network(CNN) models in mobile devices have emerged. Weight quantization, which lowers bit precision of weights, is a lightweight method that enables a model to be used through integer calculation in a mobile environment where GPU acceleration is unable. Weight quantization has already been used in various models as a lightweight method to reduce computational complexity and model size with a small loss of accuracy. Considering the size of memory and computing speed as well as the storage size of the device and the limited network environment, this paper proposes a method of compressing integer weights after quantization using a video codec as a method. To verify the performance of the proposed method, experiments were conducted on VGG16, Resnet50, and Resnet18 models trained with ImageNet and Places365 datasets. As a result, loss of accuracy less than 2% and high compression efficiency were achieved in various models. In addition, as a result of comparison with similar compression methods, it was verified that the compression efficiency was more than doubled.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.9
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• pp.1139-1148
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• 1997

Compression waves propagating in a high-speed railway tunnel develops large pressure fluctuations on the train body or tunnel structures. The pressure fluctuations would cause an ear discomfort for the passengers and increase the aerodynamic resistance of trains. As a fundamental research to resolve the pressure wave phenomenon in the tunnel, experiments were carried out by using a shock tube with an open end. A blockage to model trains inside the tunnel was installed on the lower wall of shock tube, thus forming a sudden cross-sectional area reduction. The compression waves were obtained by the fast opening gate valve instead of a conventional diaphragm of shock tube and measured by the flush mounted pressure transducers with a high sensitivity. The experimental results were compared with the previous theoretical analyses. The results show that the ratio of the reflected to the incident compression wave at the sudden cross-sectional area reduction increases but the ratio of the passing to the incident compression wave decreases, as the incident compression wave becomes stronger. This experimental results are in good agreements with the previous theoretical ones. The maximum pressure gradient of the compression wave abruptly increases but the width of the wave front does not vary, as it passes over the sudden cross-sectional area reduction.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.987-997
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• 2008

Successful design, construction and maintenance of geotechnical structure in soft ground and marine clay demands prediction, control, stability estimation and monitoring of settlement with high accuracy. It is important to predict and to estimate the compression index of soil for predicting of ground settlement. Lab. and field tests have been and are indispensable tools to achieve this goal. In this paper, Artificial Neural Networks (ANNs) model with Levenberg-Marquardt Algorithm and field database were used to predict compression index of soil in Korea. Based on soil property database obtained from more than 1800 consolidation tests from soils samples, the ANNs model were proposed in this study to estimate the compression index, using multiple soil properties. The compression index from the proposed ANN models including multiple soil parameters were then compared with those from the existing empirical equations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.147-161
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• 2003

Video object segmentation is one of the core technologies for content-based real-time MPEG-4 encoding system. For real-time requirement, the segmentation algorithm should be fast and accurate but almost all existing algorithms are computationally intensive and not suitable for real-time applications. The MPEG-4 VM(Verification Model) has provided basic algorithms for MPEG-4 encoding but it has many limitations in practical software development, real-time camera input system and compression efficiency. In this paper, we implemented the preprocessing system for real-time camera input and VOP extraction for content-based video coding and also implemented motion detection to achieve the 180 : 1 compression rate for real-time and high compression MPEG-4 encoding.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.165-170
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• 1998

This paper presents a new prediction method RBP region-based prediction model where the context used for prediction contains regions instead of individual pixels. There is a meaningful property that RBP can partition a cartoon image into two distinctive types of regions, one containing full-color backgrounds and the other containing boundaries, edges and home-chromatic areas. With the development of computer techniques, synthetic images created with CG (computer graphics) becomes attactive. Like the demand on data compression, it is imperative to efficiently compress synthetic images such as cartoon animation generated with CG for storage of finite capacity and transmission of narrow bandwidth. This paper a lossy compression method to full-color regions and a lossless compression method to homo-chromatic and boundaries regions. Two criteria for partitioning are described, constant criterion and variable criterion. The latter criterion, in form of a linear function, gives the different threshold for classification in terms of contents of the image of interest. We carry out experiments by applying our method to a sequence of cartoon animation. We carry out experiments by applying our method to a sequence of cartoon animation. Compared with the available image compression standard MPEG-1, our method gives the superior results in both compression ratio and complexity.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.711-718
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• 1999

Current turbulence models including modified $K-{\varepsilon}-{\tau}$ turbulence model do not predict compression effect on turbulence accurately in an internal combustion engine. The $K-{\varepsilon}-{\tau}$ turbulence model was suggested to improve the predictability of compression effect by We et al. In this paper a numeri-cal study was performed to clarify the applicability of the $K-{\varepsilon}-{\tau}$ turbulenc model to the calculation of the in-cylinder flow of an axisymmetric engine. THe results using $K-{\varepsilon}-{\tau}$ turbulence model are compared to those from the modified $K-{\varepsilon}-{\tau}$ turbulence model and experimental data. The mean veloc-ity and rms velocity profiles using $K-{\varepsilon}-{\tau}$ turbulence model showed a better agreement with an experimental data than those of modifid $K-{\varepsilon}-e$ turbulence model.

• Steel and Composite Structures
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• v.42 no.2
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• pp.265-275
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• 2022

A new type of precast steel reinforced concrete (PSRC) column was put forward in this paper. In order to study the static performance of PSRC column and hollow precast steel reinforced concrete (HPSRC) column subjected to combined compression and shear loading, a parametric test was carried out and effects of axial compression ratio, concrete strength and shear ratio on the mechanical behavior of composite PSRC column and HPSRC column were explored. In addition, the cracks development, load-span displacement relationship, strain distribution and shear bearing strength of column specimens were emphatically focused. Test results implied that shear failure of all specimens occurred during the test, and higher strength of cast-in-place concrete, smaller shear ratio and larger axial compression ratio could lead to greater shear resistance, but when the axial compression ratio was larger than 0.36, the shear capacity began to decrease gradually. Furthermore, truss-arch model for determining the shear strength of PSRC column and HPSRC column was proposed and the calculated results obtained from proposed method were verified to be valid.

• Tunnel and Underground Space
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• v.28 no.3
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• pp.277-291
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• 2018

LSTM (Long Short-Term Memory) algorithm which is a kind of recurrent neural network was used to establish a model to predict the stress-strain curve of an material under uniaxial compression. The model was established from the stress-strain data from uniaxial compression tests of silica-gypsum specimens. After training the model, it can predict the behavior of the material up to the failure state by using an early stage of stress-strain curve whose stress is very low. Because the LSTM neural network predict a value by using the previous state of data and proceed forward step by step, a higher error was found at the prediction of higher stress state due to the accumulation of error. However, this model generally predict the stress-strain curve with high accuracy. The accuracy of both LSTM and tangential prediction models increased with increased length of input data, while a difference in performance between them decreased as the amount of input data increased. LSTM model showed relatively superior performance to the tangential prediction when only few input data was given, which enhanced the necessity for application of the model.

• Computers and Concrete
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• v.28 no.6
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• pp.585-603
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• 2021

The validation based on the experimental data demonstrates that the concrete strength under triaxial compression (TC) is overestimated by Lubliner-Oller strength criterion (SC) but underestimated by Lubliner-Lee SC in ABAQUS. Moreover, the discontinuous derivatives of failure criterion exists near the unexpected breakpoints. Both resulted from the piecewise linear meridians of the original Lubliner SC with constants γ. Following the screen for the available failure criteria to determine the model parameter γ of Lubliner SC, Menétrey-Willam SC (MWSC) is considered the most promising option with a reasonable aspect ratio Kc but no other strength values required and only two new model parameters introduced. The failure surface of the new Lubliner SC based on MWSC (Lubliner-MWSC) is smooth and has no breakpoints along the hydrostatic pressure (HP) axis. Finally, predicted results of Lubliner-MWSC are compared with other concrete failure criteria and experimental data. It turns out that the Lubliner-MWSC can represent the concrete failure behavior, and MWSC is the optimal choice to improve the applicability of the concrete damaged plasticity model (CDPM) under TC in ABAQUS.