• Journal of the Society of Naval Architects of Korea
• /
• v.55 no.6
• /
• pp.497-504
• /
• 2018

Platform Support Vessels operated in the Arctic Ocean support diverse operations of offshore plant in the sea, and the PSV is also needed to support works to exploit the oil and gas in the Arctic Ocean. Both of the ice breaking and the open sea performance have been considered together to secure the enhanced operational performance at the harsh environment in the Arctic Ocean and the open sea as well. In this study, One of the design requirements of a PSV is to guarantee continuous icebreaking performance with 3 knots at 1 m thickness of level ice, where the design draft is 7.5m and the engine power is 13 MW. Three hull forms were designed, and the ice resistance based on empirical formulas was estimated to select the initial hull form having an outstanding performance. The full scale performance of the designed hull forms was predicted by the ice model test conducted in the ice model basin of Korea Research Institute of Ships & Ocean Engineering(KRISO). The analysed results show that the selected hull form satisfies the above design requirement.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.1
• /
• pp.68-75
• /
• 2019

A low-crested structure (LCS) is an excellent feature not only because it provides shore protection but also because it is fully submerged. However, in order to properly control waves, it is necessary to maintain a certain range of crest height and width in consideration of the wave dimensions at the installation area. According to previous studies, an LCS has some wave breaking effect when the crest width is more than a fourth of the incident wavelength and the crest depth is less than a third of the incident wave height. In other words, if the crest width of the LCS is small or the crest depth is large, it cannot control the wave. Therefore, when an LCS is installed in a large sea area with a great tidal range in consideration of the landscape, waves cannot be blocked at high tide. In this study, the hydraulic performances of a typical trapezoidal LCS with a constant crest height and a low-crested structure with an adjustable crest height, which was called a tide-adapting low-crested structure (TA-LCS) in this study, were compared and evaluated under various wave conditions through hydraulic experiments. It was found that the wave transmission coefficients of the TA-LCS at high tide were lower than the values for the typical LCS based on empirical formulas. In addition, the hydraulic performances of the TA-LCS for wave reflection control were 12.9?30.4% lower than that of the typical LCS. Therefore, the TA-LCS is expected to be highly effective in controlling the energy of incoming waves during high tide even in a macro-tidal area.

• Journal of Korea Water Resources Association
• /
• v.52 no.9
• /
• pp.603-613
• /
• 2019

This study proposes a method to generate runoff ensemble members using a rainfall-runoff model based on the shot noise process (hereafter the rainfall-runoff model). The proposed method was applied to generate runoff ensemble members for three drainage basins of Daerim 2, Guro 1 and the Jungdong, whose results were then compared with the observed. The parameters of the rainfall-runoff model were estimated using the empirical formulas like the Kerby, Kraven II and Russel, also the concept of modified rational formula. Gamma and exponential distributions were used to generate random numbers of the parameters of the rainfall-runoff model. Especially, the gamma distribution is found to be useful to generate various random numbers depending on the pre-assigned relationship between mean and standard deviation. Comparison between the generated runoff ensemble members and the observed shows that those runoff ensemble members generated using the gamma distribution with its standard deviation twice of the mean properly cover the observed runoff.

• Journal of the Korean GEO-environmental Society
• /
• v.12 no.1
• /
• pp.5-12
• /
• 2011

In this study, correlation between measured deformation modulus using pressuremeter and RMR value conducted in 10 sites is analyzed, and applicability of the conventional empirical formulas to the rock masses in Korea are analyzed, It is found that if RMR is below 40, the correlation between deformation modulus and RMR accords Kim Gyo-won's formula and Aydan, Serafim and Pereira's one well, but if the RMR exceeds 40, the correlation was lower than those from the formula. Such results may be attribute to the fact that during classification of RMR, scores are weighed relatively more in joint conditions and apertures than such highly correlational items as uniaxial compression strength or RQD, and RMR would not be evaluated qualitatively due to different weathering degrees and rock mass types as well as engineers' personal errors. Sandstone among sedimentary rocks are quite well accord with suggested equation, but correlation of other rocks are due to large variance. In this study, correlation expressions of various rocks are proposed as the function of exponential based on the field test data.

• Structural Engineering and Mechanics
• /
• v.77 no.4
• /
• pp.441-461
• /
• 2021

Reinforced concrete (RC) columns are crucial in building structures and they are of higher vulnerability to terrorist threat than any other structural elements. Thus it is of great interest and necessity to achieve a comprehensive understanding of the possible responses of RC columns when exposed to high intensive blast loads. The primary objective of this study is to derive analytical formulas to assess vulnerability of RC columns using an advanced numerical modelling approach. This investigation is necessary as the effect of blast loads would be minimal to the RC structure if the explosive charge is located at the safe standoff distance from the main columns in the building and therefore minimizes the chance of disastrous collapse of the RC columns. In the current research, finite element model is developed for RC columns using LS-DYNA program that includes a comprehensive discussion of the material models, element formulation, boundary condition and loading methods. Numerical model is validated to aid in the study of RC column testing against the explosion field test results. Residual capacity of RC column is selected as damage criteria. Intensive investigations using Arbitrary Lagrangian Eulerian (ALE) methodology are then implemented to evaluate the influence of scaled distance, column dimension, concrete and steel reinforcement properties and axial load index on the vulnerability of RC columns. The generated empirical formulae can be used by the designers to predict a damage degree of new column design when consider explosive loads. With an extensive knowledge on the vulnerability assessment of RC structures under blast explosion, advancement to the convention design of structural elements can be achieved to improve the column survivability, while reducing the lethality of explosive attack and in turn providing a safer environment for the public.

• Steel and Composite Structures
• /
• v.43 no.6
• /
• pp.735-757
• /
• 2022

The behavior of shear deficient under-balanced reinforced concrete beams with rectangular cross-sections, which were externally strengthened with CFRP composite along shear spans, was experimentally investigated under vertical load. One of the specimens represents a reference beam without CFRP strengthening and the other specimens have different width/strip spacing ratios (w_f/s_f). The optimum strip in terms of w_f/s_f, which will bring the beam behavior to the ideal level in terms of strength and ductility, was determined according to the regulations. When the w_f/s_f ratio exceeds 0.55, the behavior of the beam shifted from shear failure to bending failure. However, it has been observed that the w_f/s_f ratio should be increased up to 0.82 in order for the beam to reach sufficient shear reserve value according to the codes. It is also observed that the direction and weight of the CFRP composite are one of the most critical factors and 240 gr/m² CFRP strips experienced sudden ruptures in the shear span after the cracking of the concrete. It is considered as a deficiency that the empirical shear capacity formulas given for the beams reinforced with CFRP in the regulations do not take into account both direction and weight of CFRP composites.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.136-136
• /
• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.1B
• /
• pp.21-32
• /
• 2008

Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

• Steel and Composite Structures
• /
• v.45 no.2
• /
• pp.159-173
• /
• 2022

This paper proposes a hybrid machine-learning model, which is called DANN-IP, that combines a deep artificial neural network (DANN) and an interior-point (IP) algorithm in order to improve the prediction capacity on the patch loading resistance of steel plate girders. For this purpose, 394 steel plate girders that were subjected to patch loading were tested in order to construct the DANN-IP model. Firstly, several DANN models were developed in order to establish the relationship between the patch loading resistance and the web panel length, the web height, the web thickness, the flange width, the flange thickness, the applied load length, the web yield strength, and the flange yield strength of steel plate girders. Accordingly, the best DANN model was chosen based on three performance indices, which included the R^2, RMSE, and a20-index. The IP algorithm was then adopted to optimize the weights and biases of the DANN model in order to establish the hybrid DANN-IP model. The results obtained from the proposed DANN-IP model were compared with of the results from the DANN model and the existing empirical formulas. The comparison showed that the proposed DANN-IP model achieved the best accuracy with an R^2 of 0.996, an RMSE of 23.260 kN, and an a20-index of 0.891. Finally, a Graphical User Interface (GUI) tool was developed in order to effectively use the proposed DANN-IP model for practical applications.

• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.61-74
• /
• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.