• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.477-485
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• 2018

To control manage environmental load during construction work, it is required to ascertain an accurate quantity for materials those are using during the construction. In construction industrial nowadays, especially on design part, there are lots of mistakes occurred on quantity take-off between plan documents and actual work. That mistakes are caused by omission of design items, overcount because of interference each materials or simple calculate error. Besides, in case of a construction project, engineers are impossible to design perfectly due to a lot of invalid variable in a construction site. Thus, design errors and changes occur frequently in the process of construction work or design due to such unclear elements. And in case of LCA assessment based on 2D design, there is difficult for an engineer who is in charge to calculate the volume of materials manually using drawings and relevant specifications. This study is aimed for examining and verifying a high reliable method of evaluating environmental load which is useful in construction process through comparing LCA analysis. In addition, this study provides the method of calculating the volume of materials and LCA assessment in working on the basis of 2D design, using the specifications which is used for LCA evaluation, and possibility of utilizing the LCA assessment by introducing BIM design technic to improve the former problem through comparing and analyzing the previous method with 3D-based evaluation process.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.68-81
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• 2014

This study aims to apply and evaluate the automatic DAD analysis method, which is able to establish the depth-area relationship more efficiently and accurately for point-to-areal rainfall conversion. First, the proposed automatic DAD analysis method tracks the expansion route of area from the storm center, and it is divided into Box-tracking, Point-tracking, Advanced point-tracking according to tracking method. After applying the proposed methods to 10 events occurred in Yongdam-watershed area, we confirmed that the Advanced point-tracking method makes it possible to estimate the maximum average areal rainfal(MAAR) more accurately with consideration of the storm movement and the multi-centered storm. In addition, Advanced point-tracking could reduce the errors of the estimated MAAR induced by increasing the area because it can estimate MAAR for each storm center and compare them at the same time. Finally, the DAD curve for the study area could be derived based on the DAD analysis of the selected 10 events.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.236-237
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• 2017

In this research, experimental seakeeping results of Warped hull form 2 on the regular waves were compared with numerical results of strip method and CFD. In case of ship's speed, there are 3 cases (3.4m/s, 4.6m/s, 5.75m/s) for numerical simulation, and they are belong to semi-planing and planing condition. Consequently, in case of strip method, it is shown that the resonance phenomena occurred from around ${\lambda}/L_{OA}=2$ to 4 and RAO value were significantly higher than that of other. this is different from experimental results. In case of CFD, overall trends were similar with experimental values except there are somewhat excessive RAO values around ${\lambda}/L_{OA}=0.5$ to 2.5. these phenomena is confirmed that it became larger as the ship's speed increased, and it was considered that the error occurred because the number of mesh in vertical direction of wave height at ${\lambda}/L_{OA}=0.5$ to 2.5 were relatively less than those of wave height at ${\lambda}/L_{OA}=2.5$ to 5.2.

• Journal of the Korea Concrete Institute
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• v.19 no.2
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• pp.179-188
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• 2007

Recently, the concern on the receipt of poor ready-mixed concrete in the construction field and the durability of concrete has been increased. Based on the such background, a large number of measuring methods of water content for fresh concrete have been developed and enforced in a developed country. In this study, to investigate practicality for quality control of ready-mixed concrete among various water content measurement techniques, microwave range method, air meter method and capacitance measurement method as measuring methods of water content were selected. Then, it was evaluated estimating performance of water content according to the change of binder types, fine aggregate types, absorption ratio, water content and water-binder ratio in series I and II. Also, it was examined influence on error occurrence of water content according to change of properties of used materials in series III. Finally, based on this study, it was proposed fundamental data to utilize measurement technique of water content to quality control of ready-mixed concrete in construction field.

• Journal of the Korea Concrete Institute
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• v.24 no.2
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• pp.205-214
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• 2012

Crack widths play an important role in the serviceability limit state. When crack widths are controlled sufficiently, the reinforcement corrosion can be reduced using only existing concrete cover thickness due to low permeability in the region of finely distributed hair-cracks. Thus, the knowledge about the tensile crack opening is essential in designing more durable concrete structures. Therefore, numerous researches related to the topic have been performed. Nevertheless accurate measurement of a crack width is not a simple task due to several reasons such as unknown potential crack formation location and crack opening damaging strain gages. In order to overcome these difficulties and measure precise crack widths, a displacement measurement system was developed using digital image correlation. Accuracy calibration tests gave an average measurement error of 0.069 pixels and a standard deviation of 0.050 pixels. Direct tensile test was performed using ultra high performance concrete specimens. Crack widths at both notched and unnotched locations were measured and compared with clip-in gages at various loading steps to obtain crack opening profile. Tensile deformation characteristics of concrete were well visualized using displacement vectors and full-field displacement contour maps. The proposed technique made it possible to measure crack widths at arbitrary locations, which is difficult with conventional gages such as clip-in gages or displacement transducers.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.261-268
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• 2004

Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.545-553
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• 2009

Digital Elevation Models (DEM) is widely used in establishing the topographic profile in nation spatial information. Aerial Light Detection And Ranging (LiDAR) system is one of the well-known means to produce DEM. The system has fast data acquisition procedures and less weather-dependent restrictions compared to photogrammetric approaches. In this regards, LiDAR has been widely utilized and accepted in the process of nation spatial information generation due to its sufficient positional accuracy. However, the investigation of the accuracy of aerial LiDAR data over the area of forestation with various kinds of vegetations has been barely implemented in Korea. Hence, this research focuses on the investigation of the accuracy of aerial LiDAR data over the area of forestation and the evaluation of the acquired accuracy according to the characteristics of the vegetations. The study areas include land with shrubs and its adjacent forest area with mixed tree species. The spots for the investigation have been selected to be well-distributed over the whole study areas and their coordinates are surveyed by Global Positioning Systems (GPS). Then, the surveyed information and aerial LiDAR data have been compared with each other and the result accuracy has been evaluated. Conclusively, it is recommended that LiDAR data collection to be conducted after defoliation period, especially over the areas with broadleaf trees due to the possibility of significant outliers.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.395-405
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• 2018

Seakeeping safety module in Korean e-Navigation system is one of the ship remote monitoring services that is employed to ensure the safety of ships by monitoring the ship's real time performance and providing a warning in advance when the abnormal conditions are encountered in seakeeping performance. In general, seakeeping performance has been evaluated by simulating ship motion analysis under specific conditions for its design. However, due to restriction of computation time, it is not realistic to perform simulations to evaluate seakeeping performance under real-time operation conditions. This study aims to introduce a reasonable and faster method to predict a ship's roll motion which is one of the factors used to evaluate a ship's seakeeping performance by using a machine learning-based surrogate model. Through the application of various learning techniques and sampling conditions on training data, it was observed that the difference of roll motion between a given surrogate model and motion analysis was within 1%. Therefore, it can be concluded that this method can be useful to evaluate the seakeeping performance of a ship in real-time operation.