• The Journal of Engineering Geology
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• v.29 no.4
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• pp.383-391
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• 2019

Bio-grouting based on microbial-induced calcite precipitation (MICP) is recently emerging as a novel and environmentally friendly technique for improvement of coarse-grained ground. To date, the mechanical behaviour of bio-grouted coarse-grained soil with different calcite contents and grain sizes still remains poorly understood. The primary objective of this study is to investigate the influence of calcite content on the mechanical properties of bio-grouted coarse-grained soil with different grain sizes. This is achieved through an integrated study of uniaxial loading experiments of bio-grouted coarse-grained soil, 3D digitization of the grains in conjunction with discrete element modelling (DEM). In the DEM model, aggregates were represented by clump logic based on the 3D morphology digitization of the typical coarse-grained aggregates while the CaCO₃ was represented by small-sized bonded particle model. The computed stress-strain relations and failure patterns of the bio-grouted coarse-grained soil were validated against the measured results. Both experimental and numerical investigation suggest that aggregate sizes and calcite content significantly influence the mechanical behaviour of bio-cemented aggregates. The strength of the bio-grouted coarse-grained soil increases linearly with calcite content, but decreases non-linearly with the increasing particle size for all calcite contents. The experimental-based DEM approach developed in this study also offers an optional avenue for the exploring of micro-mechanisms contributing to the mechanical response of bio-grouted coarse-grained soils.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.315-327
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• 2002

The main objective of this study is to develop an discrete optimization algorithm of plane steel frames with rigid using second-order-elastic-plastic hinge analysis which is considering panel zone. Conventional analyses of steel frame are usually tarried out without considering the effect of panel zone deformation on frame behavior The validity of this model is established by comparison without panel zone on joint models is analyzed numerically to demonstrate the importance of using realistic models in steel frame analysis. The objective function is taken as Weight of steel frames and the constraints we formulated based on AISC-LRFD(1994). The validity of the developed algorithm we demonstrate by comparing the result with those of SAP2000. The result of the study indicates that the optimal design algorithm considering of panel zone behavior more economic design than simple steel frame design methods.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.6
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• pp.59-68
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• 2002

In this paper, we design the two-dimensional Discrete Wavelet Transform (2D DWT) filter that is widely used in various applications such as image compression because it has no blocking effects and relatively high compression rate. The filter that we used here is two-channel four-taps QMF(Quadrature Mirror Filter) Lattice filter with PR (Perfect Reconstruction) property. The proposed DWT architecture, with two consecutive inputs shows an efficient performance with a minimum of such hardware resources as multipliers, adders, and registers due to a simple scheduling. The proposed architecture was verified by the RTL simulation, and utilizes the hardware 100%. Our architecture shows a relatively high performance with a minimum hardware when compared with other approaches. An efficient memory mapping and address generation techniques are introduced and the fixed-point arithmetic analysis for minimizing the PSNR degradation due to quantization is discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.603-611
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• 2013

In this paper, we propose a new method which estimates and encrypts significant component of digital image such as digital cinema using discrete wavelet packet transform (DWPT). After analyzing the characteristics of images in spatial and frequency domain, the required information for ciphering an image was extracted. Based on this information an ciphering method was proposed with wavelet transform and packetization of subbands. The proposed algorithm can encrypt images in various robust from selecting transform-level and energy threshold. From analyzing the encryption effect numerically and visually, the optimized parameter for encryption is presented. Without additional analyzing process, one can encrypt efficiently digital image using the proposed parameter. Although only 0.18% among total data is encrypted, the reconstructed image dose not identified. The paketization information of subbands and the cipher key can be used for the entire secret key.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.23-33
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• 1996

In this paper we point out that if the classical principal domain for bispectra is utilized to determine a second-order Volterra model's output, such and output will be incomplete. This deficiency is associated with the periodic nature of the DFT. For this reason, the objective of this paper is to present an "extended" principal domain for Volterra kernels which leads to an improved estimate of the nonlinear system's response. In order to define the extended principal domain, we derive a new discrete frequency-domain Volterra model from a discrete time-domain Volterra model utilizing 2-dimensional DFT and the relationship between the quadratic component of the Volterra model and a square filter. The effect of the extended domain on the model output is interpreted in terms of the periodicity of DFT. Through computer simulations, we demonstrate the effects of the extended principal domain on the Volterra modeling. The simulation results indicate that the extended principal domain plays and important role in computing Volterra model outputs and estimating Volterra model coefficients.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.15-28
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• 2020

In this study, a procedure was introduced to estimate strength and deformation modulus of the 3-D discrete fracture network(DFN) systems using the distinct element method(DEM). Fracture entities were treated as non-persistent square planes in the DFN systems. Systematically generated fictitious fractures having similar mechanical characteristics of intact rock were combined with non-persistent real fractures to create polyhedral blocks in the analysis domain. Strength and deformation modulus for 10 m cube domain of various deterministic and stochastic 3-D DFN systems were estimated using the DEM to explore the applicability of suggested method and to examine the effect of fracture geometry on strength and deformability of DFN systems. The suggested procedures were found to effective in estimating anisotropic strength and deformability of the 3-D DFN systems.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.6
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• pp.84-93
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• 2018

Three-dimensional (3D) numerical simulations have been carried out to study how coolant injection conditions influence the cooling efficiency and projectile ejection performance in a mixture-gas ejection system (or gas-steam launch system). The 3D single-phase computational model was verified using a 1D model constructed with reference to the previous research and then a two-phase flow computation simulating coolant injection on to hot gas was performed using a DPM (Discrete Phase Model). As a result of varying the coolant flow rate and number of injection holes, cooling efficiency was improved when the number of injection holes were increased. In addition, the change of the coalescence frequency and spatial distribution of coolant droplets caused by the injection condition variation resulted in a change of the droplet diameter, affecting the evaporation rate of coolant. The evaporation was found to be a critical factor in the design optimization of the ejection system by suppressing the pressure drop while the temperature decreases inside the breech.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.607-612
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• 2020

In this paper, we deal with the stability of linear discrete systems with time-varying delays and unstructured uncertainty. Stability conditions are derived based on Lyapunov stability theory, and can include the effect of uncertainty. The unstructured uncertainty in the papaer which can not be figured out its exact characteristics and only can be expreesed by its magnitude is considered. Compared with the previous results on the stability, the new results can expand the applicable systems and alleviate the stability conditions which are more effective and powerful. The proposed stability condition is expressed in the form of an simple inequality, and includes the both effects of the uncertainties and time-varying delay. We present the results comparing the new stability condition with the existing results, and verify the effectiveness and the superiority of the proposed results through numerical example.

• Resources Recycling
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• v.31 no.6
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• pp.36-43
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• 2022

The general screen used to separate the particle size of recycled aggregate has restrictions when dealing with moisturized materials because of the blockage phenomenon. Therefore, in this study, to improve the separation efficiency of the conventional screen, the excellence of additional vibrating device based on spring was decided by a simulation experiment based on the discrete element method (DEM). The motion characteristic was investigated by analyzing the displacement, amplitude, and strain angle based on the spring design. Further, the particle motion was simulated by applying spring motion. The material flow and separation efficiency of the screen applied spring were confirmed as 9.2 kg/s and 97 %, respectively. Consequently, the improvement in the screen applied with blockage prevention spring was confirmed by comparing with the conventional screen.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1103-1108
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• 2023

In this paper, we propose a new algorithm for attenuating the background noises in acoustic signal. This algorithm improves the noise attenuation performance by using the FNN(: Full-connected Neural Network) deep learning algorithm instead of the existing adaptive filter after wavelet transform. After wavelet transforming the input signal for each short-time period, noise is removed from a single input audio signal containing noise by using a 1024-1024-512-neuron FNN deep learning model. This transforms the time-domain voice signal into the time-frequency domain so that the noise characteristics are well expressed, and effectively predicts voice in a noisy environment through supervised learning using the conversion parameter of the pure voice signal for the conversion parameter. In order to verify the performance of the noise reduction system proposed in this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed. As a result of the experiment, the proposed deep learning algorithm improved Mean Square Error (MSE) by 30% compared to the case of using the existing adaptive filter and by 20% compared to the case of using the STFT(: Short-Time Fourier Transform) transform effect was obtained.