• 한국지반공학회논문집
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• 제22권2호
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• pp.29-39
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• 2006

동반 논문(백규호, 2006)에서 사석과 모래로 뒷채움된 케이슨에 대하여 모래와 사석의 내부마찰각과 단위중량의 차이는 물론 사석의 뒷채움 경사각 변화와 뒷채움재에서 발생하는 아칭효과까지 고려해서 비선형의 주동토압을 산정 할 수 있는 토압산정식이 제안되었다. 본 연구에서는 새로 제안된 토압산정식에 대한 정확도를 검증하기 위하여 뒷채움재가 균질하고 벽체가 거친 경우에 대한 제안식의 결과는 백규호(2003a)의 제안식과 비교하였고, 뒷채움재가 균질하고 벽체가 매끄러운 경우에 대한 제안식의 결과는 Rankine의 토압이론과 비교되었다. 그리고 매개변수 분석을 통해서 사석과 모래의 내부마찰각과 단위중량, 케이슨의 벽면마찰각, 사석의 뒷채움 경사각 변화가 케이슨에 작용하는 주동토압에 미치는 영향을 조사하였으며, 매개변수 분석 결과에 근거해서 케이슨에 작용하는 주동토압을 최소화할 수 있는 뒷채움 시공법이 제안되었다.

• 한국지반공학회논문집
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• 제25권11호
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• pp.17-26
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• 2009

마이크로파일이 직접기초시스템으로 활용되는 경우 말뚝 캡이 설치되어 말뚝지지 전면기초의 래프트와 같은 역할을 수행하지만 마이크로파일 기초시스템의 하중분담 거동에 관한 연구는 미미한 실정이다 이에 본 연구에서는 말뚝캡이 씌워진 실물 크기의 마이크로파일 재하시험 자료를 바탕으로 3차원 비선형 유한요소해석을 실시하여 마이크로 파일과 래프트의 하중분담 거동을 분석하고 각각의 변수들이 하중분담 거동에 미치는 영향을 파악하였다. 해석 결과 $2{\times}1$ 마이크로파일 기초시스템의 경우 최종하중단계에서 약 50%의 하중을, 그리고 $2{\times}2$ 마이크로파일 기초시스템의 경우 약 30%의 하중을 캡이 분담하고 있는 것으로 나타났다. 또한 마이크로파일의 간격 및 경사각이 증가할수록 캡의 하중분담이 커지는 것을 알 수 있다.

• Advances in nano research
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• 제14권4호
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• pp.363-373
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• 2023

A novel type of steel fiber with a rounded-end shape is presented to improve the bonding behavior of fibers with Carbon Nanotubes (CNT)-reinforced Ultra-High Performance Concrete (UHPC) matrix. For this purpose, by performing a parametric study and using the nonlinear finite element method, the impact of geometric characteristics of the fiber end on its bonding behavior with UHPC has been studied. The cohesive zone model investigates the interface between the fibers and the cement matrix. The mechanical properties of the cohesive zone model are determined by calibrating the finite element results and the experimental fiber pull-out test. Also, the results are evaluated with the straight steel fibers outcomes. Using the novel presented fibers, the bond strength has significantly improved compared to the straight steel fibers. The new proposed fibers increase bond strength by 1.1 times for the same diameter of fibers. By creating fillet at the contact area between the rounded end and the fiber, bond strength is significantly improved, the maximum fiber capacity is reachable, and the pull-out occurs in the form of fracture and tearing of the fibers, which is the most desirable bonding mode for fibers. This also improves the energy absorbed by the fibers and is 4.4 times more than the corresponding straight fibers.

• Geomechanics and Engineering
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• 제28권2호
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• pp.197-207
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• 2022

The seismic holding behaviors of plate anchor embedded into submerged coarse-grained soils were investigated considering different anchor inclinations. The limit equilibrium method and the Pseudo-Dynamic Approach (PDA) were employed to calculate the inertia force of the soils within the failure rupture. In addition, assuming the permeability of coarse-grained soils was sufficiently large, the coefficient of hydrodynamic force applied on the inclined plate anchor is obtained through adopting the exact potential flow theory. Therefore, the seismic holding resistance was calculated as the combination of the inertia force and the hydrodynamic force within the failure rupture. The failure rupture can be developed due to the uplift loads, which was assumed to be an arc of a circle perpendicular to the anchor and inclines at (π/4 - φ/2). Then, the derived analytical solutions were evaluated by comparing the static breakout factor N_γ to the published experimental and analytical results. The influences of soil and wave properties on the plate anchor holding behavior are reported. Finally, the dynamic anchor holding coefficients N_γd, were reported to illustrate the anchor holding behaviors. Results show that the soil accelerations in x and z directions were both nonlinear. The amplifications of soil accelerations were more severe at lower normalized frequencies (ωH/V) compared to higher normalized frequencies. The coefficient of hydrodynamic force, C, of the plate anchor was found to be almost constant with anchor inclinations. Finally, the seismic anchor holding coefficient oscillated with the oscillation of the inertia force on the plate anchor.

• 한국음향학회지
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• 제42권3호
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• pp.169-180
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• 2023

수중음향통신의 성능은 다중경로 전달과 도플러 확산에 크게 영향을 받는다. 본 논문은 다중경로 전달 환경에서 강인한 기존의 Sweep Spread Carrier(SSC) 기법을 변형하여, 새로운 통신기법인 Triangle Spread Carrier(TSC) 기법을 제안한다. 제안한 TSC 기법은 상승-처프와 하강-처프 신호가 반복되는 반송파를 갖는 형태이며, 각각의 상관함수 특성을 활용하여 수신 신호의 도플러 천이 주파수를 추정하고 보정한다. 제안된 TSC 기법의 성능을 입증하기 위하여 수중 채널 시뮬레이터를 이용한 모의실험과 동해에서 수행된 해상실험을 결과를 제시한다. 해상실험 결과 추정된 도플러 천이 주파수만을 이용하여 복조하였을 때 비부호화 된 비트 오류율은 최대 0.194였지만, 제안한 방법을 적용하였을 때 비부화화된 비트 오류율이 0.001로 감소하였다.

• Geomechanics and Engineering
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• 제33권3호
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• pp.279-289
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• 2023

Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σ_c) and tensile strength (σ_t) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R²), adjusted R² (Adj R²), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R² and Adj R² values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

• 천문학회보
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• 제46권2호
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• pp.47.3-48
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• 2021

We studied the large scale dynamo process in a system forced by helical magnetic field. The dynamo process is basically nonlinear, but can be linearized with 𝛼&𝛽 coefficients and large scale magnetic field $\bar{B}$. This is very useful to the investigation of solar (stellar) dynamo. A coupled semi-analytic equations based on statistical mechanics are used to investigate the exact evolution of 𝛼&𝛽. This equation set needs only magnetic helicity ${\bar{H}}_M({\equiv}{\langle}{\bar{A}}{\cdot}{\bar{B}}{\rangle},\;{\bar{B}}={\nabla}{\times}{\bar{A}})$ and magnetic energy ${\bar{E}}_M({\equiv}{\langle}{\bar{B}}^2{\rangle}/2)$. They are fundamental physics quantities that can be obtained from the dynamo simulation or observation without any artificial modification or assumption. 𝛼 effect is thought to be related to magnetic field amplification. However, in reality the averaged 𝛼 effect decreases very quickly without a significant contribution to ${\bar{B}}$ field amplification. Conversely, 𝛽 effect contributing to the magnetic diffusion maintains a negative value, which plays a key role in the amplification with Laplacian ∇²(= - k²) for the large scale regime. In addition, negative magnetic diffusion accounts for the attenuation of plasma kinetic energy E_V(= 〈 U² 〉/2) (U: plasma velocity) when the system is saturated. The negative magnetic diffusion is from the interaction of advective term - U • ∇ B from magnetic induction equation and the helical velocity field. In more detail, when 'U' is divided into the poloidal component U_pol and toroidal one U_tor in the absence of reflection symmetry, they interact with - B • ∇ U and - U • ∇ B from ∇ × 〈 U × B 〉 leading to 𝛼 effect and (negative) 𝛽 effect, respectively. We discussed this process using the theoretical method and intuitive field structure model supported by the simulation result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.942-943
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• 2021

The present work proposes a classification system for the HEp-2 cell images using an unsupervised deep feature learning method. Unlike most of the state-of-the-art methods in the literature that utilize deep learning in a strictly supervised way, we propose here the use of the deep convolutional autoencoder (DCAE) as the principal feature extractor for classifying the different types of the HEp-2 cell images. The network takes the original cell images as the inputs and learns to reconstruct them in order to capture the features related to the global shape of the cells. A final feature vector is constructed by using the latent representations extracted from the DCAE, giving a highly discriminative feature representation. The created features will be fed to a nonlinear classifier whose output will represent the final type of the cell image. We have tested the discriminability of the proposed features on one of the most popular HEp-2 cell classification datasets, the SNPHEp-2 dataset and the results show that the proposed features manage to capture the distinctive characteristics of the different cell types while performing at least as well as the actual deep learning based state-of-the-art methods.

• 대한토목학회논문집
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• 제28권4A호
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• pp.457-463
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• 2008

종방향 보강재는 압축플랜지를 단순지지함으로써 국부좌굴강도를 증가시키는 역할을 수행한다. 최근 연구에 의하면, 종방향으로 적절한 간격을 두고 점지지 되었을 경우 그 선을 따라서 단순 지지된 경우와 동일한 좌굴강도를 보이는 것으로 밝혀졌다. 이 같은 연구결과로부터, 하부콘크리트에 부착된 전단연결재가 압축플랜지의 좌굴시 점지지 조건을 만족할 수 있다면 전단연결재가 단순지지의 역할도 수행할 수 있을 것이라는 예측이 가능하다. 이와 같은 사실이 입증이 된다면, 강박스거더 제작비에서 매우 큰 부분을 차지하는 종방향보강재를 생략할 수 있기 때문에 보다 경제적인 설계가 가능해 질 것이다. 본 연구에서는 하부압축플랜지에 종방향보강재를 대체할 전단연결재의 종방향 배치 시 최소간격 결정과 동시에 하부 콘크리트와 합성거동을 하기 위해 소요되는 전단연결재 소요 개수와 간격을 결정하기 위한 연구를 수행하였다.