• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.5D
• /
• pp.831-838
• /
• 2006

An experimental/analytic study has been conducted to understand the adverse effects of low vehicle speed, high axle load and high tire pressure on the performance of asphalt pavements. Of 33 asphalt sections at KHC test road, two sections having different base layer thickness (180 mm versus 280 mm) are adopted for rollover tests. During the test, a standard three-axle dump truck maintains a steady state condition as moving along the wheel path of a passing lane, and lateral offsets and real travel speed are measured with a laser-based wandering system. Test results suggest that vehicle speed affects both longitudinal and transverse strains at the bottom of asphalt layer (290 mm and 390 mm below the surface), and even slightly influences the measured vertical stresses at the top of subbase and subgrade due to the dynamic effect of rolling vehicle. Since the anisotropic nature of asphalt-aggregate mixtures, the difference between longitudinal and transverse strains appears prominent throughout the measurements. As the thickness of asphalt pavement increases, the measured lateral strains become larger than its corresponding longitudinal strains. Over the limited testing conditions, it is concluded that higher axle weight and higher tire pressures induce more strains and vertical stresses, leading to a premature deterioration of pavements. Finally, a layered elastic analysis overestimates the maximum strains measured under the 1st axle load, while underestimating the maximum vertical stress in both pavement sections.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4D
• /
• pp.635-647
• /
• 2006

Korean construction companies first advanced to the international markets in 1960's and so far have brought more than 4,900 projects which account for 193 billion dollars approximately. With the large increase of national employment and income being followed by the achievement, Korea's construction industry has made an enormous contribution to the improvement of domestic economy for the last 40 years. However, recently the increased risk in international markets as well as the sharpening competition with foreign companies promising in terms of advanced technologies and low labor cost have been driving Korean construction away from the market shares. According to ENR (Engineering News Record, 1994~2003), it is revealed that 15.1% of top 225 global contractors are suffering from loss in international construction markets. This phenomenon is largely due to the highly uncertain characteristics of international projects, which are inherently exposed to various and complicated risky situations. Furthermore, especially for Korean construction companies, it is often the case that the failure in an international construction project cannot be offset by even a sufficient number of successful domestic achievements. Therefore, not only the selective screening among the nominated projects which have strong possibility of collapse but the systematic strategies for controlling potential risk factors are also considered indispensable in international construction portfolio management. The purpose of this study is to first analyze the causal relationships of the profit-influencing variables and the project success, and develop the profitability forecasting model in international construction projects.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.2D
• /
• pp.235-244
• /
• 2009

Design Value Engineering (VE) has become an import part of the daily design process since it has been introduced in the construction industry. Design VE is usually conducted in the general and execution design stages respectively. In order to increase the effectiveness of the VE process, the outcome from the general design VE activities should be integrated into execution design. The outcome from the execution design should be used again for construction. In this study, a consecutive VE process model has been presented as a way to improve the current practice of design VE activities in the construction industry. In the presented model, follow-up activities are emphasized to increase values from the life-cycle perspective of a construction project. The model was tested in a case study of an actual design VE process. The result of the study demonstrates that the model can: 1) effectively incorporate owners requirements; 2) assist decision making in selecting better construction; 3) increase the interface between general and execution design stages; and 4) trace the value flow more efficiently. Overall, the study results indicates that a the consecutive VE process model can be effectively applied when construction project are contracted for the life-cycle management of construction projects.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3D
• /
• pp.453-459
• /
• 2006

This paper presents an experimental evaluation of wandering effect on asphalt concrete pavement responses. A laser-based wandering system has been developed and its performance is verified under various field conditions. The portable wandering system composed of two laser sensors with Position Sensitive Devices can allow one to measure the distance between laser sensors and tire edges of moving vehicle. Therefore, lateral position of each wheel on the pavement can be determined in a real time manner. Pavement responses due to different loading paths are investigated using a roll over test which is carried out on one of asphalt surfaced pavements in the Korea Highway Corporation test road. The pavement section (A5) consists of 5 cm thick surface course; 7 cm intermediate course; and 18 mm base course, and is heavily instrumented with strain gauges, vertical soil pressure cells and thermo-couples. From the center of wheel paths, seven equally-spaced lateral loading paths are carefully selected over an 140 cm wandering zone. Test results show that lateral horizontal strains in both surface and intermediate courses are mostly compressive right under the loading path and tensile strains start to develop as the loading offset becomes 40 cm from the wheel path. The development of the vertical stresses in the top layers of subbase and anti-frost is found to be minimal once the loading offset becomes 50 cm.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.6B
• /
• pp.641-649
• /
• 2006

The behavior of a three-dimensional pure rectangular water jet with aspect ratio of 10 was experimentally investigated based on the results of the mean velocity field obtained by PIV. The saddle back distribution was observed in the lateral distribution along the major axis. The theoretical centerline velocity equation derived from the point source concept using the spreading rate for the axisymmetric jet was in good agreement with the measured centerline velocity and gave the division of the potential core region, two-dimensional region, and axisymmetric region. The range of the two-dimensional region divided by the criterion of the theoretical centerline velocity decay for the aspect ratio of 10 was observed to be smaller than that of the transition region. The applicability of the two-dimensional model to the behavior of the rectangular jet with low aspect ratio or the wastewater discharged from a multiport diffuser in the deep water of real ocean may result in significant error in the transition and axisymmetric regions after the two-dimensional region. In the two-dimensional region, the Gaussian constant tended to be conserved, and the spreading rate slightly decreased at the end of the two-dimensional region. The normalized turbulent intensity along the centerline of the jet initially abruptly increased and showed relatively higher intensity for higher Reynolds number.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.1A
• /
• pp.9-18
• /
• 2009

This paper introduces the application of DE (Differential Evolutionary) method for the estimation of tensile force of the externally prestressed tendon. The proposed technique, a SI (System Identification) method using the DE algorithm, can make global solution search possible as opposed to classical gradient-based optimization techniques. The numerical tests show that the proposed technique employing DE algorithm is a useful method which can detect the effective nominal diameters as well as estimate the exact tensile forces of the externally prestressed tendon with an estimation error less than 1% although there is no a priori information about the identification variables. In addition, the validity of the proposed technique is experimentally proved using a scale-down model test considering the serviceability state condition without and with the loss of the prestressed force. The test results prove that the technique is a feasible and effective method that can not only estimate the exact tensile forces and detect the effective nominal diameters but also inspect the damping properties of test model irrespective of the loss of the prestressed force. The 2% error of the estimated effective nominal diameter is due to the difference between the real tendon diameter with a wired section and the FE model diameter with a full-section. Finally, The accuracy and superiority of the proposed technique using the DE algorithm are verified through the comparative study with the existing theories.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.3D
• /
• pp.381-389
• /
• 2009

Korean government is investing 1.8 billion won on infrastructure and investment on PPP projects constitutes 16.3%. This phenomenon is to promote private investment as well as lessening government burdens of public budgeting. However, the only criterion to be considered is government financial status in selecting public or private highway investment projects. So systematic decision support model is required in choosing public or private highway investment projects. So, this paper suggests a systematic decision support model for deciding public or private highway investment at the early stage of project planning. Furthermore, this paper identifies key decision variables with respect to economic, politic, project management criterions based on the related literatures and feedbacks from experts. This paper analyzed 30 cases of government investment and PPP projects and got the survey result from highway specialists. As a result, this paper presents an interval with respect to economic criteria using mean and standard deviation and a logistic regression equation which can predict the possibility of PPP project. Through this study, decision maker of central or local government can decide public or PPP highway project more systematically and reasonably.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.383-384
• /
• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Journal of the Korean earth science society
• /
• v.44 no.6
• /
• pp.557-577
• /
• 2023

This study defines non-precipitation information as areas with weak precipitation or cloud particles that radar cannot detect due to weak returned signals, and suggests methods for its utilization in data assimilation. Previous studies have demonstrated that assimilating radar data from precipitation echoes can produce precipitation in model analysis and improve subsequent precipitation forecast. However, this study also recognizes the non-precipitation information as valuable observation and seeks to assimilate it to suppress spurious precipitation in the model analysis and forecast. To incorporate non-precipitation information into data assimilation, we propose observation operators that convert radar non-precipitation information into hydrometeor mixing ratios and relative humidity for the Weather Research and Forecasting Data Assimilation system (WRFDA). We also suggest a preprocessing method for radar non-precipitation information. A single-observation experiment indicates that assimilating non-precipitation information fosters an environment conducive to inhibiting convection by lowering temperature and humidity. Subsequently, we investigate the impact of assimilating non-precipitation information to a real case on July 23, 2013, by performing a subsequent 9-hour forecast. The experiment that assimilates radar non-precipitation information improves the model's precipitation forecasts by showing an increase in the Fractional Skill Score (FSS) and a decrease in the False Alarm Ratio (FAR) compared to experiments in which do not assimilate non-precipitation information.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.10
• /
• pp.27-35
• /
• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.