• 플랜트 저널
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• 제12권4호
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• pp.44-50
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• 2016

실증적인 압축시스템 구현을 위해 관로 유동 모델을 기존의 압축 시스템 모델에 적용하였다. 두 모델의 결합을 위해 압축시스템을 구성하는 압축기, 플래넘, 쓰로틀 벨브 와 각 구성 품을 연결하는 배관의 접점에 적절한 경계 조건을 사용하였다. 본 연구를 통해 관로 유동 모델이 압축 시스템의 안정성에 미치는 영향을 살펴보았다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.668-673
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• 2008

In this paper, we developed a physically-based micromechanical model for inelastic deformation of ceramic powders. The aggregate response of ceramic particles was modeled using the two-surface yield function which considered the shear-induced dilatancy caused by friction, rolling resistance and cohesion between powder particles and consolidation caused by plastic deformation of powder themselves under high compression. The constitutive equations were implemented into the user-subroutine VUMAT of finite element program ABAQUS/Explicit. The material parameters in the constitutive model were identified by calibrating the model to reproduce data from triaxial compression tests and simple compression tests. The density distribution obtained by using the proposed model was in good quantitative agreement with the experimental results of the triaxial compression and cold isostaic compression as well.

• 한국농공학회논문집
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• 제66권2호
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• pp.1-12
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• 2024

In order to integrate two consolidation theories of Terzaghi's consolidation theory and Mesri's secondary compression theory and to identify a model suitable for analyzing stress-strain behavior over time, numerical analysis on consolidation tests were conducted using a modified cam-clay model and a soft soil creep model and the following conclusions were obtained. The results of numerical analysis applying the theory that a linear proportional relationship is established between the void ratio at logarithmic scale and the permeability coefficient at logarithmic scale is better agreement with the result of oedometer test than the results of applying constant hydraulic conductivity. The modified cam-clay model is a model that does not include secondary compression, but the slope of the normal consolidation line corresponding to the compression index of the standard consolidation test includes secondary compression, so the actual settlement curve over time is lower than the predicted value through numerical analysis. It always gets smaller. Other previous studies that applied Terzaghi's consolidation theory to consolidation test analysis showed the same results and were cross-confirmed. The soft soil creep model, which includes secondary compression in the theory, showed good agreement in all sections including secondary compression in the consolidation test results. It was judged appropriate to use a soft soil creep model when performing numerical analysis of soft clay ground.

• 에너지공학
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• 제24권3호
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• pp.61-66
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• 2015

Homogeneous charge compression ignition (HCCI) engine combines the combustion characteristics of a compression ignition engine and a spark ignition engine. HCCI engines take advantage of the high compression ratio and heat release rate and thus exhibit high efficiency found in compression ignition engines. In modern research, simulation has be come a powerful tool as it saves time and also economical when compared to experimental study. Engine simulation has been developed to predict the performance of a homogeneous charge compression ignition engine. The effects of compression ratio, cylinder pressure, rate of pressure rise, flame temperature, rate of heat release, and mass fraction burned were simulated. The simulation and analysis show several meaningful results. The objective of the present study is to develop a combustion characteristics model for a homogeneous charge compression ignition engine running with isooctane as a fuel and effect of compression ratio.

• 전자공학회논문지C
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• 제34C권3호
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• pp.23-36
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• 1997

In tis paper, sthe new data model for the hardware implementation of lempel-ziv compression algorithm was proposed. Traditional model generates the codeword which consists of 3 bytes, the last symbol, the position and the matched length. MSB (most significant bit) of the last symbol is the comparession flag and the remaining seven bits represent the character. We confined the value of the matched length to 128 instead of 256, which can be coded with seven bits only. In the proposed model, the codeword consists of 2 bytes, the merged symbol and the position. MSB of the merged symbol is the comression flag. The remaining seven bits represent the character or the matched length according to the value of the compression flag. The proposed model reduces the compression ratio by 5% compared with the traditional model. The proposed model can be adopted to the existing hardware architectures. The incremental factors of the compression ratio are also analyzed in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1389-1408
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• 2021

Proof-of-Work (PoW) is the first and still most common consensus protocol in blockchain. But it is costly and energy intensive, aiming at addressing these problems, we propose a consensus algorithm named Proof-of-Work-and-Block-Compression (PoW-BC). PoW-BC is an improvement of PoW to compress blocks and adjust consensus parameters. The algorithm is designed to encourage the reduction of block size, which improves transmission efficiency and reduces disk space for storing blocks. The transaction optimization model and block compression model are proposed to compress block data with a smaller compression ratio and less compression/ decompression duration. Block compression ratio is used to adjust mining difficulty and transaction count of PoW-BC consensus protocol according to the consensus parameters adjustment model. Through experiment and analysis, it shows that PoW-BC improves transaction throughput, and reduces block interval and energy consumption.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.1159-1164
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• 2006

In this paper an artificial neural network model is developed to estimate the unconfined compression strength of Deep Cement Mixing(DCM) treated soil. A database which consists of a number of unconfined compression test result compiled from 9 clay sites is used to train and test of the artificial neural network model. Developed neural network model requires water content of soil, unit weight of soil, passing percent of #200 sieve, weight of cement, w-c ratio as input variables. It is found that the developed artificial neural network model can predict more precise and reliable unconfined compression strength than the conventional empirical models.

• Geomechanics and Engineering
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• 제25권4호
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• pp.341-345
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• 2021

1D sand compression response to ko-loading experiences volume contraction from low to high effective stress regimes. Previous study suggested compressibility model with physically correct asymptotic void ratios at low and high stress levels and examined only for both remolded clays and natural clays. This study extends the validity of Enhanced Terzaghi model for different sand types complied from 1D compression data. The model involved with four parameters can adequately fit 1D sand compression data for a wide stress range. The low stress obtained from fitting parameters helps to identify the initial fabric conditions. In addition, strong correlation between compressibility and the void ratio at low stress facilitates determination of self-consistent fitting parameters. The computed tangent constrained modulus can capture monotonic stiffening effect induced by an increase in effective stress. The magnitude of tangent stiffness during large strain test should not be associated with small strain stiffness values. The use of a single continuous function to capture 1D stress-strain sand response to ko-loading can improve numerical efficiency and systematically quantify the yield stress instead of ad hoc methods.

• Steel and Composite Structures
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• 제39권3호
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• pp.319-335
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• 2021

This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP, which combines an interior-point (IP) algorithm and artificial neural network (ANN), to improve the axial compression capacity prediction of elliptical concrete-filled steel tubular (CFST) columns. For this purpose, 145 tests of elliptical CFST columns extracted from the literature are used to develop the ANN-IP model. In this regard, axial compression capacity is considered as a function of the column length, the major axis diameter, the minor axis diameter, the thickness of the steel tube, the yield strength of the steel tube, and the compressive strength of concrete. The performance of the ANN-IP model is compared with the ANN-LM model, which uses the robust Levenberg-Marquardt (LM) algorithm to train the ANN model. The comparative results show that the ANN-IP model obtains more magnificent precision (R² = 0.983, RMSE = 59.963 kN, a20 - index = 0.979) than the ANN-LM model (R² = 0.938, RMSE = 116.634 kN, a20 - index = 0.890). Finally, a new Graphical User Interface (GUI) tool is developed to use the ANN-IP model for the practical design. In conclusion, this study reveals that the proposed ANN-IP model can properly predict the axial compression capacity of elliptical CFST columns and eliminate the need for conducting costly experiments to some extent.

• 방송공학회논문지
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• 제27권1호
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• pp.31-43
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• 2022

전통적인 비디오 압축은 움직임 예측, 잔차 신호 변환 및 양자화를 통한 하이브리드 압축 방식을 기반으로 지금까지 발전해왔다. 최근 인공 신경망을 통한 기술이 빠르게 발전함에 따라, 인공 신경망 기반의 이미지 압축, 비디오 압축 연구 또한 빠르게 진행되고 있으며, 전통적인 비디오 압축 코덱의 성능과 비교해 높은 경쟁력을 보여주고 있다. 본 논문에서는 이러한 인공 신경망 기반 비디오 압축 모델의 성능을 향상시킬 수 있는 새로운 방법을 제시한다. 기본적으로는 기존 인공 신경망 기반 비디오 압축 모델들이 채택하고 있는 변환 및 복원 신경망과 엔트로피 모델(Entropy model)을 이용한 율-왜곡 최적화(Rate-distortion optimization) 방법을 사용하며, 인코더 측에서 디코더 측으로 압축된 레이턴트 정보(Latent information)를 전송할 때 엔트로피 모델이 추정하기 어려운 정보의 값을 이동시켜 전송할 비트량을 감소시키고, 손실된 정보를 추가로 전송함으로써 손실된 정보에 대한 왜곡을 보정한다. 이러한 방법을 통해 기존의 인공 신경망 기반 비디오 압축 기술인 MFVC(Motion Free Video Compression) 방법을 개선하였으며, 실험 결과를 통해 H.264를 기준으로 계산한 BDBR (Bjøntegaard Delta-Bitrate) 수치(%)로 MFVC(-14%) 보다 두 배 가까운 비트량 감축(-27%)이 가능함을 입증하였다. 제안된 방법은 MFVC 뿐 아니라, 레이턴트 정보와 엔트로피 모델을 사용하는 신경망 기반 이미지 또는 비디오 압축 기술에 광범위하게 적용할 수 있다는 장점이 있다.