• Journal of Environmental Impact Assessment
• /
• v.33 no.2
• /
• pp.84-98
• /
• 2024

This study proposed a prediction equation for the estimation of blasting vibaration and blasting noise, utilizing 320 datasets for the blasting vibration and blasting noise acquired during urban blasting works in the Incheon, Suwon, Wonju, and Yangsan regions. The proposed blasting vibration prediction equation, derived from regression analysis, indicated correlation coefficients of 0.879 and 0.890 for SRSD and CRSD, respectively, with an R² value exceeding 0.7. In the case of the blasting noise prediction equation, stepwise regression analysis yielded a correlation coefficient of 0.911 between the prediction values and real measurements for the blasting nosie, and further analysis to determine the constant value revealed a correlation coefficient of 0.881, with an R² value also exceeding 0.7. These results suggest the feasibility of applying the proposed prediction equations when environmental impact assessments or education environment evaluation according to urban development or apartment construction projects is performed.

• Journal of Korea Water Resources Association
• /
• v.54 no.5
• /
• pp.301-309
• /
• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Water for future
• /
• v.28 no.1
• /
• pp.133-144
• /
• 1995

The subject of the paper is the selection of the number and location of rainguage stations among existing ones, which will be part of real-time data collection system, for the computation of mean areal precipitation and for use as input of real-time flow forecasting models. The weighted average method developed by National Weather Service was used to compute MAP. Two different searching methods were used to find local optimal solutions as a function of the number of rainguages. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Journal of Power Electronics
• /
• v.18 no.5
• /
• pp.1608-1617
• /
• 2018

The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.

• Tribology and Lubricants
• /
• v.5 no.2
• /
• pp.60-67
• /
• 1989

For the life prediction and fatigue failure prevention of the constant velocity joint, the maximum equivalent stress and its location in depth from the contact area are essential. These values give the fundamental information to determine the depth of the surface hardening treatment at the contact area. Contact stresses are evaluated at the surface and subsurface of the ball groove of the Weiss type constant velocity joint. The maximum contact pressure and the maximum equivalent stress are obtained. The effects of various parameters such as the radius of ball groove, friction coefficient, and residual stress are studied. The maximum equivalent stress and the maximum contact pressure increase as the radius of the ball grove increases. The location of the maximum equivalent stress moves toward surface as the friction coefficient increases. It was also found that the maximum equivalent stress becomes minimum when the compressire residual stress is about 0.16 times of the maximum contact pressure.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.27 no.10
• /
• pp.101-106
• /
• 2013

This paper proposes the new high precision monitoring sensor for the Marine Installation. Among variety of sensor network systems, wireless information transmission through the marine is one of the enabling technologies for the development of future marine-observation systems and sensor networks. Applications of marine monitoring range from oil industry to aquaculture, and include instrument monitoring, pollution control, climate recording, prediction of natural disturbances. For these marine applications to be available, however, the provision of precise location information using monitoring sensor is essential. In this paper, the dynamic characteristics for obtaining the location information of monitoring sensor is analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the Monitoring for the Marine Installation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.5
• /
• pp.1109-1122
• /
• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• Structural Engineering and Mechanics
• /
• v.51 no.2
• /
• pp.299-313
• /
• 2014

In the first part of this paper, the influences of some of crack parameters on natural frequencies of a cracked cantilever Functionally Graded Beam (FGB) are studied. A cantilever beam is modeled using Finite Element Method (FEM) and its natural frequencies are obtained for different conditions of cracks. Then effect of variation of depth and location of cracks on natural frequencies of FGB with single and multiple cracks are investigated. In the second part, two Multi-Layer Feed Forward (MLFF) Artificial Neural Networks (ANNs) are designed for prediction of FGB's Cracks' location and depth. Particle Swarm Optimization (PSO) and Back-Error Propagation (BEP) algorithms are applied for training ANNs. The accuracy of two training methods' results are investigated.

• Journal of Welding and Joining
• /
• v.25 no.5
• /
• pp.72-77
• /
• 2007

Prediction and control of the thermal distortion is particularly important for the design and manufacture of welded thin metal structure. In this study, numerical computations are performed to analyze effect of structure section shape and weld line location on distortion. In addition, this study aims to develop a thermal elasto-plastic simulation using finite element method to predict distortion, with particular emphasis on bending deformation generated in outline welding of a thin box structure. From the numerical analysis, it was revealed that the section shape and weld line location play an important role on the welding distortion. Among 3 types of section shape design proposed in this study, the least deformation remained in the two path welded structure.

• Korean Journal of Computational Design and Engineering
• /
• v.3 no.3
• /
• pp.161-167
• /
• 1998

Cutting forces in ball-end milling of slanted surfaces are calculated. The cutting area is determined from the Z-map of the surface geometry and current cutter location. The obtained cutting area is projected onto the cutter plane normal to the Z-axis and compared with cutting edge element location. Cutting force is calculated by integration of elemental cutting forces of engaged cutting edge elements. Experiments with various slanted angles were performed to verify the proposed cutting force estimation model. It is shown that the proposed method predicts cutting force effectively for any geometry including sculptured surfaces with cusp marks and surfaces with pockets and holes.