• International Journal of Highway Engineering
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• v.11 no.1
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• pp.13-24
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• 2009

This study developed a high strength and performance concrete pavement material with low shrinkage and reflection of sunlight. Based on the literature review, a new mix-design of applying flash ash to improve the strength and performance of the concrete as well as to reduce the dry shrinkage is suggested. In addition, adding black pigment to reduce the reflection and technique of applying OAG (Optimized Aggregate Gradation) is also included. The result of the laboratory experiment indicates that the brightness and the reflection, which depends on the ratio of black pigment addition, did not deviate from the normal range. When OAG is considered for the mix-design, the strength and performance of the concrete improved greatly. In addition, the mix-design using fly ash reduced the dry shrinkage of concrete and improved the resistance to the permeation of chloride ion. Furthermore, the mix-design, which uses fly ash (25% replacement) and black pigment (3% addition) with the application of OAG, is found to be the most effective mix to reduce the shrinkage and reflection as well as improving the strength and performance of the concrete. The result of an economic analysis indicates that the initial construction cost of this proposed mix is more expensive than that of normal concrete pavement material. However, it can be more economic in the long run because the normal concrete pavement material is likely to cost more due to higher probability of maintenance and repair and higher social cost due to traffic accident, etc.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Advances in Computational Design
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• v.4 no.1
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• pp.53-72
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• 2019

Safety measures for tower cranes are extremely important among the seismic countermeasures at high-rise building construction sites. In particular, the collapse of a tower crane from a high position is a very serious catastrophe. An example of such an accident due to an earthquake is the case of the Taipei 101 Building (the author was the project director), which occurred on March 31, 2002. Failure of the bolted joints of the tower-crane mast was the direct cause of the collapse. Therefore, it is necessary to design for this eventuality and to take the necessary measures on construction sites. This can only be done by understanding the precise dynamic behavior of mast joints during an earthquake. Consequently, we created a new hybrid-element model (using beam, shell, and solid elements) that not only expressed the detailed behavior of the site joints of a tower-crane mast during an earthquake but also suppressed any increase in the total calculation time and revealed its behavior through computer simulations. Using the proposed structural model and simulation method, effective information for designing safe joints during earthquakes can be provided by considering workability (control of the bolt pretension axial force and other factors) and less construction cost. Notably, this analysis showed that the joint behavior of the initial pretension axial force of a bolt is considerably reduced after the axial force of the bolt exceeds the yield strength. A maximum decrease of 50% in the initial pretension axial force under the El Centro N-S Wave ($v_{max}=100cm/s$) was observed. Furthermore, this method can be applied to analyze the seismic responses of general temporary structures in construction sites.

• Fashion & Textile Research Journal
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• v.16 no.6
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• pp.945-953
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• 2014

This study aims to develop protective pants to relieve impact from falls and to present basic data for the development. The survey results are as follows; First, 45% of the respondents were in their 60s and 55% of them were in their over 70s and older. Also, 64% of them have fallen once for the past year and 36% of them have fallen twice or more. The older they were, the more there were those who have fallen twice or more. This indicated the older people has experienced more fall accidents again after a initial fall accident. Second, as per accident situations, the survey showed that fall accidents happened the most in the winter and in the afternoon (12-18 pm). Also, it happened on a street mostly and they were wearing sneakers or hiking boots when they got a hurt slipped in a front or side by missing their step in a walk. The injury areas are mostly knee and ankle. They had the bruises or a sprain in their knee and ankle mostly. The rate of bone fracture was 19.5%. Therefore, the protection area to falls in lower body is the knee. But hip and hip joint should be protected with knee as well because those are usually be broken when it is damaged. Third, approximately 80% of those who were hospitalized for treatment had surgery. Patients who had surgery were rather in their over 70s than in their 60s. The older they were, the more serious their fracture was. The period of hospital or outpatient treatment is more than three weeks in many cases. They responded their health got worse after falls. Aftereffects of accidents were physical discomfort, anxiety and medical costs. Falls to the old makes physical damage, psychological damage, which cause reduced physical activity and the increased cost of health care with economic losses. So it results on a negative impact on the life of the old. Fourth, elderly females were rarely aware of impact protective clothing and they have never purchased such clothing. For impact protective pants, the major consideration was suitable design for their body types. They liked casual style with front or side pockets and simple designs without any patterns or decorations. As per pants materials, they responded that they need functionality, activity and elasticity. Among the functional points, insulation of cloths are considered importantly, so the heat reservance of material in the impact protective pants should be considered carefully.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of Radiation Protection and Research
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• v.33 no.4
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• pp.127-134
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• 2008

Potential economic impact of a hypothetical severe accident at a nuclear power plant(Uljin units 3/4) was estimated by applying the Delphi method, which is based on the expert judgements and opinions, in the process of quantifying uncertain factors. For the purpose of this study, it is assumed that the radioactive plume directs the inland direction. Since the economic risk can be divided into direct costs and indirect effects and more uncertainties are involved in the latter, the direct costs were estimated first and the indirect effects were then estimated by applying a weighting factor to the direct cost. The Delphi method however subjects to risk of distortion or discrimination of variables because of the human behavior pattern. A mathematical approach based on the Bayesian inferences was employed for data processing to improve the Delphi results. For this task, a model for data processing was developed. One-dimensional Monte Carlo Analysis was applied to get a distribution of values of the weighting factor. The mean and median values of the weighting factor for the indirect effects appeared to be 2.59 and 2.08, respectively. These values are higher than the value suggested by OECD/NEA, 1.25. Some factors such as small territory and public attitude sensitive to radiation could affect the judgement of panel. Then the parameters of the model for estimating the direct costs were classified as U- and V-types, and two-dimensional Monte Carlo analysis was applied to quantify the overall economic risk. The resulting median of the overall economic risk was about 3.9% of the gross domestic products(GDP) of Korea in 2006. When the cost of electricity loss, the highest direct cost, was not taken into account, the overall economic risk was reduced to 2.2% of GDP. This assessment can be used as a reference for justifying the radiological emergency planning and preparedness.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.173-182
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• 2020

Since 2000, Korea has seen a big trend in the market, as the EU tightened regulations on environment due to global warming, high oil prices and aging rural population distribution, strengthening the need for multi-purpose electric moto vehicles for small farmers based on eco-friendly energy. Multi-purpose electric motor vehicles for rural small businesses will be a very innovative means of transportation, not only maintained at a low cost and to reduce greenhouse gases through the activation of eco-friendly energy, but also be a very innovative means of transportation for reducing the labor intensity of the aging farming industry and transporting night work and logistics. In this paper, with the implementation of eco-friendly energy policies, small and medium-sized rural small business owners can easily operate on unpaved roads and well-drawn farming environments, while the intensity of labor can be reduced when transporting crops also can simply replace parts at a low cost in the event of an accident. To propose rural multi-purpose modular electric vehicles, the existing literature is reviewed and 12 modular parts are presented by benchmarking electric vehicles at home and abroad. This paper is thought to be helpful for the research of the industry as well as the design industry of modular electric vehicles.