• 한국구조물진단유지관리공학회 논문집
• /
• 제22권2호
• /
• pp.98-104
• /
• 2018

콘크리트 비파괴강도 추정식은 일반적으로 콘크리트 강도를 결정하는데 사용된다. 그러나 기존의 추정식들은 대부분 제한된 실험 변수를 토대로 제안되어 배합조건, 강도특성 등이 다양한 실제 공용중 교량의콘크리트 압축강도 추정시 많은 오류를 포함한다. 본 연구에서는 297개 공용 교량의 정밀안전진단 결과 중 콘크리트 비파괴시험 및 현장 코어강도 시험결과를 토대로 콘크리트 부재의 코어강도와 비파괴 추정강도 평가결과를 비교분석하였다. 분석결과 분석이 이루어진 기존 추정식들 중 일본건축학회 CNDT소위원회 강도계산식이 다른 추정식에 비하여 실제파괴강도와의 오차가 가장적고 상관분석의 신뢰도도 가장높은 것으로 검토되었다. 그러나 이 추정식은 코어강도가 30 MPa이상일때 추정강도는 과소평가되는 것으로 나타났다. 이에 본 논문에서는 추정식에 의한 강도와 현장 코어강도사이의 관계를 활용하여 회귀분석을 통한 개선된 비파괴강도 추정식을 제안하였다.

• 대한조선학회논문집
• /
• 제47권5호
• /
• pp.647-655
• /
• 2010

In this paper, a numerical study is carried out for super-pipe, flat plate and axisymmetric body flows to investigate a validity of using wall function and high $y_1^+$ in calculation of high Reynolds number flow. The velocity profiles in boundary layer agree well with the law of the wall. And it is found that the range of $y^+$��which validated the logarithmic law of the wall grows with increasing Reynolds number. From the result, an equation is suggested that can be used to estimate a maximum $y^+$ value of validity of the log law. And the slope(1/$\kappa$) of the log region of the numerical result is larger than that of experimental data. On the other hand, as $y_1^+$ is increasing, both the friction and the pressure resistances tend to increase finely. When using $y_1^+$ value beyond the range of log law, the surface shear stress shows a significant error and the pressure resistance increases rapidly. However, when using $y_1^+$ value in the range, the computational result is reasonable. From this study, the use of the wall function with high value of $y_1^+$ can be justified for a full scale Reynolds number ship flow.

• 한국물환경학회지
• /
• 제35권5호
• /
• pp.432-438
• /
• 2019

The purpose of this study is to predict Trophic Diatom Index (TDI) in tributaries of the Han River watershed using the random forest algorithm. The one year (2017) and supplied aquatic ecology health data were used. The data includes water quality(BOD, T-N, $NH_3-N$, T-P, $PO_4-P$, water temperature, DO, pH, conductivity, turbidity), hydraulic factors(water width, average water depth, average velocity of water), and TDI score. Seven factors including water temperature, BOD, T-N, $NH_3-N$, T-P, $PO_4-P$, and average water depth are selected by the Correlation Feature Selection. A TDI prediction model was generated by random forest using the seven factors. To evaluate this model, 2017 data set was used first. As a result of the evaluation, $R^2$, % Difference, NSE(Nash-Sutcliffe Efficiency), RMSE(Root Mean Square Error) and accuracy rate show that this model is compatible with predicting TDI. To be more concrete, $R^2$ is 0.93, % Difference is -0.37, NSE is 0.89, RMSE is 8.22 and accuracy rate is 70.4%. Also, additional evaluation using data set more than 17 times the measured point was performed. The results were similar when the 2017 data set were used. The Wilcoxon Signed Ranks Test shows there was no statistically significant difference between actual and predicted data for the 2017 data set. These results can specify the elements which probably affect aquatic ecology health. Also, these will provide direction relative to water quality management for a watershed that must be continuously preserved.

• 전기전자학회논문지
• /
• 제24권4호
• /
• pp.1176-1179
• /
• 2020

선박의 이동 경로를 예측하는 기존의 방법들은 일반적으로 위도와 경도를 직접 예측한다. 하지만, 위도와 경도를 직접 예측할 경우, 예측 모델이 출력 가능한 범위가 상당히 넓어서 예측 오차가 매우 크게 발생할 수 있다. 또한, 순환 신경망 모델 기반의 예측에서는 이전 예측 위치도 다음 위치를 예측하기 위해 사용되기 때문에 오차가 누적되는 현상도 쉽게 발생할 수 있다. 이에 따라, 제안하는 방법에서는 위도와 경도를 직접 예측하지 않고, 선박의 가속도를 예측하여, 향후 속도와 방향을 결정하고, 그 결과로 위도와 경도가 예측되는 방법을 제안한다. 실험 결과에서는 같은 순환 신경망 모델을 사용했을 때, 제안하는 방법이 기존의 직접적으로 위도와 경도를 예측하는 방법에 비해 더 적은 오차를 발생시킴을 보인다.

• 대한의용생체공학회:의공학회지
• /
• 제41권6호
• /
• pp.247-255
• /
• 2020

Accurate diagnosis of movement disorders is important for providing right patient care at right time. In general, assessment of motor impairment relies on clinical ratings conducted by experienced clinicians. However, this may introduce subjective opinions into scoring the severity of motor impairment. Digital devices such as table PC and smart band with accelerometer can be used for more accurate and objective assessment and possibly helpful for clinicians to make right decision of patient's states. In this study, we introduce quantification algorithms of motor impairment which uses the digital data acquired during four clinical motor tests (Line drawing, Spiral drawing, Nose to finger and Hand flip tests). The step by step procedure of quantifying metrics (Tremor Frequency, Tremor Magnitude, Error Distance, Time, Velocity, Count and Period) are provided with flowchart. The effectiveness of the proposed algorithm is presented with the result from simulated data (normal, normal with tremor and slowness, poor with tremor, poor with tremor and slowness).

• 대기
• /
• 제32권2호
• /
• pp.163-178
• /
• 2022

This study aims to evaluate the accuracy of retrieved horizontal winds with different quality control methods from three Doppler lidars deployed over the complex terrain during the PyeongChang 2018 Olympic and Paralympic games. To retrieve the accurate wind profile, this study also proposes two quality control methods to distinguish between meteorological signals and noises in the Doppler velocity field, which can be broadly applied to different Doppler lidars. We evaluated the accuracy of retrieved winds with the wind measurements from the nearby or collocated rawinsondes. The retrieved wind speed and direction show a good agreement with rawinsonde with a correlation coefficient larger than 0.9. This study minimized the sampling error in the wind evaluation and estimation, and found that the accuracy of retrieved winds can reach ~0.6 m s^-1 and 3° in the quasi-homogeneous wind condition. We expect that the retrieved horizontal winds can be used in the high-resolution analysis of the horizontal winds and provide an accurate wind profile for model evaluation or data assimilation purposes.

• 대한조선학회논문집
• /
• 제59권3호
• /
• pp.141-148
• /
• 2022

A hybrid turbulence model has developed by combining a sub-grid scale model using dynamic k equation in LES with k-𝜔 SST model of RANS equation. To ascertain potential applicability of the hybrid turbulence model, fully developed turbulent channel flows at Re_𝜏=180 have been simulated of which computational domain has a top wall with coarse cells and a bottom wall with fine cells. The streamwise mean velocity and turbulent intensity profiles showed a good agreement with DNS data when using the hybrid model rather than using a single model in k-𝜔 SST or dynamic k equation models. Computational simulations of turbulent flows around KVLCC2 with a pre-swirl duct have been mainly performed using the hybrid turbulence model. Compared to the results obtained from RANS simulation with k-𝜔 SST model as well as LES with dynamic k equation SGS model, turbulent wakes of the duct in the present simulation using the hybrid turbulence model were very similar to that of LES. Also, the resistances acting on hull, rudder and duct in hybrid turbulence model were similar to those in RANS simulation whereas the viscous forces acting on the hull in LES had a significant error due to coarse cells inappropriate to the sub-grid scale model.

• 한국군사과학기술학회지
• /
• 제26권1호
• /
• pp.10-21
• /
• 2023

For various target tracking applications, it is well known that the Kalman filter is the optimal estimator(in the minimum mean-square sense) to predict and estimate the state(position and/or velocity) of linear dynamical systems driven by Gaussian stochastic noise. In the case of nonlinear systems, Extended Kalman filter(EKF) and/or Unscented Kalman filter(UKF) are widely used, which can be viewed as approximations of the(linear) Kalman filter in the sense of the conditional expectation. However, to implement EKF and UKF, the exact dynamical model information and the statistical information of noise are still required. In this paper, we propose the recurrent neural-network based Kalman filter, where its Kalman gain is obtained via the proposed GRU-LSTM based neural-network framework that does not need the precise model information as well as the noise covariance information. By the proposed neural-network based Kalman filter, the state estimation performance is enhanced in terms of the tracking error, which is verified through various linear and nonlinear tracking problems with incomplete model and statistical covariance information.

• 대한조선학회논문집
• /
• 제60권3호
• /
• pp.155-164
• /
• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• 멤브레인
• /
• 제33권1호
• /
• pp.34-45
• /
• 2023

본 연구에서는 투과 유량 모델을 개발하기 위하여, 시간, 막 전후의 압력 차, 회전 속도, 막의 기공 크기, 동점도, 농도 및 공급 유체의 밀도 등 7개의 입력 변수에 기반한 두 종류(ANN 및 SVM) 인공지능 기법을 이용하였다. 시행착오법과 실험데이터와 예측 데이터 간의 결정 계수(R²) 와 평균절대상대편차(AARD)를 포함한 두 가지 통계 변수를 통해 최적의 모델을 선정하였다. 최종적으로 얻어진 결과에서 최적화된 ANN 모델이 R² = 0.999 및 AARD% = 2.245인 투과 플럭스 예측 정확도를 보여서, R² = 0.996 및 AARD% = 4.09의 정확도를 보인 SVM 모델에 비해 더 정확함을 알 수 있었다. 또한, ANN 모델은 SVM 방식에 비해 투과 유속을 예측하는 능력도 더 높은 것으로 나타났다.