• Journal of Ocean Engineering and Technology
• /
• 제33권6호
• /
• pp.564-572
• /
• 2019

Numerical simulation of the sediment by the Delft3d model was conducted to examine the changes in the sediment budget transport caused by long-term wave changes at the Maengbang beach. Representative waves were generated with input reduction tools using NOAA NCEP wave data for about 40 years, i.e., from January 1979 to May 2019. To determine the adequacy of the model, wave and depth changes were compared and verified using wave and depth data observed for about 23 months beginning in March 2017. As a result of the error analysis, the bias was 0.05 and the root mean square error was 0.23, which indicated that the numerical wave results were satisfactory. Also, the observed change in depth and numerical result were similar. In addition, to examine the effect due to long-term changes in the waves, the NOAA wave data classified into each of the representative wave grades, and then the annual trend of the representative wave was analyzed. After deciding the weight of each wave class considering the changed wave environment in 2100, the amounts of sedimentation, deposition, and the sediment transport budget were reviewed for the same period. The results indicated that the sedimentation pattern did not change significantly compared to the current state, and the amount of the local sediment budget shown in the present state was slightly less. And there has been a local increase in the number of sediment budget transport, but there is no significant difference in the net and amount of sediment movements.

• Smart Structures and Systems
• /
• 제20권4호
• /
• pp.483-498
• /
• 2017

Real-Time Hybrid Simulation (RTHS) is a powerful and cost-effective dynamic experimental technique. To implement a stable and accurate RTHS, time delay present in the experiment loop needs to be compensated. This delay is mostly introduced by servo-hydraulic actuator dynamics and can be reduced by applying appropriate compensators. Existing compensators have demonstrated effective performance in achieving good tracking performance. Most of them have been focused on their application in cases where the structure under investigation is subjected to inputs with relatively low frequency bandwidth such as earthquake excitations. To advance RTHS as an attractive technique for other engineering applications with broader excitation frequency, a discrete-time feedforward compensator is developed herein via various optimization techniques to enhance the performance of RTHS. The proposed compensator is unique as a discrete-time, model-based feedforward compensator. The feedforward control is chosen because it can substantially improve the reference tracking performance and speed when the plant dynamics is well-understood and modeled. The discrete-time formulation enables the use of inherently stable digital filters for compensator development, and avoids the error induced by continuous-time to discrete-time conversion during the compensator implementation in digital computer. This paper discusses the technical challenges in designing a discrete-time compensator, and proposes several optimal solutions to resolve these challenges. The effectiveness of compensators obtained via these optimal solutions is demonstrated through both numerical and experimental studies. Then, the proposed compensators have been successfully applied to RTHS tests. By comparing these results to results obtained using several existing feedforward compensators, the proposed compensator demonstrates superior performance in both time delay and Root-Mean-Square (RMS) error.

• Bulletin of the Korean Chemical Society
• /
• 제26권12호
• /
• pp.2007-2016
• /
• 2005

An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 한국의학물리학회 2003년도 제27회 추계학술대회
• /
• pp.49-49
• /
• 2003

목적 : 심초음파는 비침습적이므로 반복적으로 정확히 심질환의 경과를 관찰하여 치료효과 및 수술시기를 정할 수 있는 검사로서 임상적으로 매우 유용하다. 실시간 심근조영심초음파에 의한 time intensity 평가는 부위별로 수행됨으로 연속적으로 위치하는 관심영역이 intensity에 있어 심장의 움직임 변화에 영향을 받는다. Time intensity 곡선의 최적의 곡선맞춤을 위해 주기적인 심장 운동 매개변수를 조합해 기존의 모델을 보정한 안정적인 측정방법을 제시한다. 방법 : 심장의 운동에 의한 특징적인 정보를 설명하기 위해 기존의 문헌에 제시된 지수 함수에 주어진 심박수로 만들어진 시간에 관한 일반적인 정형파 함수를 추가한다. C(t) = A[1 - exp($\beta$t)] + Dsine(2$\pi$ft + $\theta$) C(t): videointensity A: plateau videointensity (blood volume) $\beta$: capillary blood velocity (rate constant of rise in videointensity) t: pulsing interval (ms) D: displacement from the periodic variance of the curve (estimated motion field from the ejection point for the ratio between systole and diastole) f: heart rate $\theta$: transit time issue A $\times$ $\beta$ : myocardial blood flow 관상동맥의 관류 데이터에 대한 실험이 펄스간격에 대한 비디오 세기로 수행되었다. 그리고 이러한 결과들이 the sum of squares due to error, R square, root mean squared error로 평가되었다. 결과 : 실험결과, 주기적인 심장의 움직임과 심박출 시점으로부터의 변위를 잘 기술하고 곡선에서의 측정 점들이 예측된 심장 움직임에 따라 성공적으로 표시되었다. 뿐만 아니라 보정된 모델이 현저한 적합도의 향상을 보여주었다. 결론 : 제시된 접근방법은 각각의 측정에서 심장 운동 영역의 변화에 독립적이며 측정 시점에 의해 영향받지 않고 심근 관류의 안정적인 측정이 가능하다. 심장의 움직임에 관한 매개변수를 조합한 모델로 곡선접합을 수행함으로써 관류의 정량적 정보를 좀더 정확하게 얻을 수 있으며 임상적 이용을 가능하게 할 것으로 기대된다.

• The Journal of the Korea institute of electronic communication sciences
• /
• 제14권6호
• /
• pp.1235-1240
• /
• 2019

It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

• Journal of KIISE:Software and Applications
• /
• 제31권9호
• /
• pp.1171-1179
• /
• 2004

We describe word boundary detection that extracts the boundary between speech and non-speech. The proposed method uses two features. One is the normalized root mean square of speech signal, which is insensitive to white noises and represents temporal information. The other is the normalized met-frequency band energy of voice signal, which is frequency information of the signal. Our method detects word boundaries using a recurrent fuzzy associative memory(RFAM) that extends FAM by adding recurrent nodes. Hebbian learning method is employed to establish the degree of association between an input and output. An error back-propagation algorithm is used for teaming the weights between the consequent layer and the recurrent layer. To confirm the effectiveness, we applied the suggested system to voice data obtained from KAIST.

• Magazine of the Korean Society of Agricultural Engineers
• /
• 제45권5호
• /
• pp.97-109
• /
• 2003

This study is mainly conducted to derive the design drought rainfall by the consecutive duration using probability weighted moments with rainfall in the regional drought frequency analysis. It is anticipated to suggest optimal design drought rainfall of hydraulic structures for the water requirement and drought frequency of occurrence for the safety of water utilization through this study. Preferentially, this study was conducted to derive the optimal regionalization of the precipitation data that can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. Five homogeneous regions in view of topographical and climatological aspects were accomplished by K-means clustering method. Using the L-moment ratio diagram and Kolmogorov-Smirnov test, generalized extreme value distribution was confirmed as the best fitting one among applied distributions. At-site and regional parameters of the generalized extreme value distribution were estimated by the method of L-moments. Design drought rainfalls using L-moments following the consecutive duration were derived by the at-site and regional analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design drought rainfall derived by at-site and regional analysis in the observed an simulated data were computed and compared. In has shown that the regional frequency analysis procedure can substantially more reduce the RRMSE. RBIAS and RR in RRMSE than those of at-site analysis in the prediction of design drought rainfall. Consequently, optimal design drought rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

• Journal of The Korean Society of Agricultural Engineers
• /
• 제60권6호
• /
• pp.83-96
• /
• 2018

The objective of this study was to estimate the climate change impact on water quantity and quality to Saemanguem watershed using SWAT (Soil and water assessment tool) model. The SWAT model was calibrated and validated using observed data from 2008 to 2017 for the study watershed. The $R^2$ (Determination coefficient), RMSE (Root mean square error), and NSE (Nash-sutcliffe efficiency coefficient) were used to evaluate the model performance. RCP scenario data were produced from 10 GCM (General circulation model) and all relevant grid data including the major observation points (Gusan, Jeonju, Buan, Jeongeup) were extracted. The systematic error evaluation of the GCM model outputs was performed as well. They showed various variations based on analysis of future climate change effects. In future periods, the MIROC5 model showed the maximum values and the CMCC-CM model presented the minimum values in the climate data. Increasing rainfall amount was from 180mm to 250mm and increasing temperature value ranged from 1.7 to $5.9^{\circ}C$, respectively, compared with the baseline (2006~2017) in 10 GCM model outputs. The future 2030s and 2070s runoff showed increasing rate of 16~29% under future climate data. The future rate of change for T-N (Total nitrogen) and T-P (Total phosphorus) loads presented from -26 to +0.13% and from +5 to 47%, respectively. The hydrologic cycle and water quality from the Saemanguem headwater were very sensitive to projected climate change scenarios so that GCM model should be carefully selected for the purpose of use and the tendency analysis of GCM model are needed if necessary.

• Journal of Biosystems Engineering
• /
• 제39권4호
• /
• pp.310-317
• /
• 2014

Purpose: This study was conducted to analyze the air flow characteristics in a plant factory with different inlet and outlet locations using computational fluid dynamics (CFD). Methods: In this study, the flow was assumed to be a steady-state, incompressible, and three-dimensional turbulent flow. A realizable k-${\varepsilon}$ turbulent model was applied to show more reasonable results than the standard model. A CFD software was used to perform the numerical simulation. For validation of the simulation model, a prototype plant factory ($5,900mm{\times}2,800mm{\times}2,400mm$) was constructed with two inlets (${\Phi}250mm$) and one outlet ($710mm{\times}290mm$), located on the top side wall. For the simulation model, the average air current speed at the inlet was $5.11m{\cdot}s^{-1}$. Five cases were simulated to predict the airflow pattern in the plant factory with different inlet and outlet locations. Results: The root mean square error of measured and simulated air current speeds was 13%. The error was attributed to the assumptions applied to mathematical modelling and to the magnitude of the air current speed measured at the inlet. However, the measured and predicted airflow distributions of the plant factory exhibited similar patterns. When the inlets were located at the center of the side wall, the average air current speed in the plant factory was increased but the spatial uniformity was lowered. In contrast, if the inlets were located on the ceiling, the average air current speed was lowered but the uniformity was improved. Conclusions: Based on the results of this study, it was concluded that the airflow pattern in the plant factory with multilayer cultivation shelves was greatly affected by the locations of the inlet and the outlet.

• Advances in biomechanics and applications
• /
• 제1권3호
• /
• pp.169-185
• /
• 2014

Computational multibody models of the elbow can provide a versatile tool to study joint mechanics, cartilage loading, ligament function and the effects of joint trauma and orthopaedic repair. An efficiently developed computational model can assist surgeons and other investigators in the design and evaluation of treatments for elbow injuries, and contribute to improvements in patient care. The purpose of this study was to develop an anatomically correct elbow joint model and validate the model against experimental data. The elbow model was constrained by multiple bundles of non-linear ligaments, three-dimensional deformable contacts between articulating geometries, and applied external loads. The developed anatomical computational models of the joint can then be incorporated into neuro-musculoskeletal models within a multibody framework. In the approach presented here, volume images of two cadaver elbows were generated by computed tomography (CT) and one elbow by magnetic resonance imaging (MRI) to construct the three-dimensional bone geometries for the model. The ligaments and triceps tendon were represented with non-linear spring-damper elements as a function of stiffness, ligament length and ligament zero-load length. Articular cartilage was represented as uniform thickness solids that allowed prediction of compliant contact forces. As a final step, the subject specific model was validated by comparing predicted kinematics and triceps tendon forces to experimentally obtained data of the identically loaded cadaver elbow. The maximum root mean square (RMS) error between the predicted and measured kinematics during the complete testing cycle was 4.9 mm medial-lateral translational of the radius relative to the humerus (for Specimen 2 in this study) and 5.30 internal-external rotation of the radius relative to the humerus (for Specimen 3 in this study). The maximum RMS error for triceps tendon force was 7.6 N (for Specimen 3).