• Journal of the Korea Concrete Institute
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• v.22 no.1
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• pp.19-27
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• 2010

Aging and severe environments are major causes of damage in reinforced concrete (RC) structures such as buildings and bridges. Deterioration such as concrete cracks, corrosion of steel, and deformation of structural members can significantly degrade the structural performance and safety. Therefore, effective and easy-to-use methods are desired for repairing and strengthening such concrete structures. Various methods for strengthening and rehabilitation of RC structures have been developed in the past several decades. Recently, FRP composite materials have emerged as a cost-effective alternative to the conventional materials for repairing, strengthening, and retrofitting deteriorating/deficient concrete structures, by externally bonding FRP laminates to concrete structural members. The main purpose of this study is to investigate the effectiveness of adaptive neuro-fuzzy inference system (ANFIS) in predicting behavior of circular type concrete column retrofitted with FRP. To construct training and testing dataset, experiment results for the specimens which have different retrofit profile are used. Retrofit ratio, strength of existing concrete, thickness, number of layer, stiffness, ultimate strength of fiber and size of specimens are selected as input parameters to predict strength, strain, and stiffness of post-yielding modulus. These proposed ANFIS models show reliable increased accuracy in predicting constitutive properties of concrete retrofitted by FRP, compared to the constitutive models suggested by other researchers.

• Journal of the Korea Concrete Institute
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• v.17 no.2 s.86
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• pp.179-189
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• 2005

Corrosion of steel due to chloride attack is a major concern in reinforced concrete structures which are located in the marine environments. In this case, Fick's 2nd law has been used for the prediction of chloride diffusion related with service life of concrete structures. However, those studies were confined mostly to the single deterioration due to chloride only, although actual environment is rather of combined type. The purpose of the present study is, therefore, to explore the influences of carbonation to chloride attack in concrete structures and to investigate the validity of Fick's law to chloride attack combined carbonation. The test results indicate that the chloride ion profiles from Fick's law using the diffusion coefficient of immersion tests is not reflected the effect of separation of chloride ions in carbonation region but valid in sound region in case of combined action. On the other hand, the chloride ion profiles from Fick's law using the diffusion coefficient of Tang and Nilsson's method coincide with test results under dry-wet condition but not under combined condition. The results of present study may Imply that the new method for the measurement of diffusion coefficient is required to predict the chloride ion profiles in case of combined action at early.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.2
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• pp.109-115
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• 2019

In case of the cracks in concrete, the penetration of deterioration ions such as chloride ions in to cracks is accelerated. According to the penetration of chloride ions, structural and durability problems to RC(Reinforced Concrete) structures are caused. In this study, the accelerated chloride diffusion coefficient which is in steady state is evaluated for 2 year aged normal and high strength FA(Fly Ash) concrete, after a range of crack depths are induced up to 1.0 mm in 56 aged day. Considering crack effect by linear regression analysis, high strength concrete has slightly less increasing ratio of diffusion coefficient by crack than normal strength concrete, and diffusion coefficient increases non-linearly as crack width is increased. Also, In two types of concrete, crack effect decrease as the curing period increase. In the case of quantifying crack and curing effect by using exponential function form, the coefficients of determination are higher than those of linear regression analysis. Under steady state, it is thought that there is not a high correlation between the crack effect and the curing effect, and considering the two independent effects, it is believed that reasonable prediction equation for diffusion of concrete with crack can be proposed.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.2
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• pp.191-199
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• 2021

In this study, the correlation between the influencing factors on corrosion and Half Cell Potential(HCP) measurement was analyzed considering the three levels of W/C ratio, cover depth, and chloride concentration. The HCP increased with enlarged cover depth, so it was confirmed that the increment of cover depth was effective for control of corrosion. Based on the criteria, the case of 60mm cover depth showed excellent corrosion control with under -200mV, indicating increase of cover depth is an effective method for reducing intrusion of external deterioration factors. When fresh water was injected to the upper part of specimens, very low level of HCP was monitored, but in the case that concentrations of chloride were 3.5% and 7.0%, HCP dropped under -200mV. In addition, the case with high volume of unit binder showed lower HCP measurement like increasing cover depth. Multiple regression analysis was performed to evaluate the correlation between the corrosive influence factors and HCP results, showing high coefficient of determination of 0.97. However, there were limitations such as limited number of samples and measuring period. Through the additional corrosion monitoring and chloride content evaluation after dismantling the specimen, more reasonable prediction can be achieved for correlation analysis with relevant data.

• Journal of the Korean GEO-environmental Society
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• v.23 no.3
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• pp.15-22
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• 2022

This study aims to observe the swelling representative rocks in Korea and to suggest improvements in the use of test methods and prior analysis in relation to the weathering of rocks. The swelling test and analysis were performed on the drilling cores obtained for the ground investigation at the domestic highway construction site. For the method of determining the absorption expansion index of rocks, the method proposed in "Standard Methods for Sample Collection and Specimen Preparation" of ISRM and Korean Rock Engineers Standard Rock Test Method was used. The specimen for the measurement of the expansion displacement was cylindrical with a height of 10 cm and a diameter of 5 cm. The existing swelling analysis method evaluates the sensitivity to weathering by using the maximum expansion displacement, but since the classification by bedrock grade is unclear, it is reasonable to use the rate of change of the expansion displacement according to the immersion time. It is necessary to conduct an experiment to distinguish between weathering and fault deterioration. In addition, long-term weathering prediction technology for each cancer type is needed through the expansion displacement analysis of the chemical weathering stage.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.33-40
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• 2021

The deterioration of underground facilities, disturbance of the ground due to underground development activities, and changes in ground water can cause ground subsidence accidents in the urban areas. The investigation on the geotechnical and hydraulic factors affecting the ground subsidence accident is very significant to predict the ground subsidence risk in advance. In this study, an analysis DB was constructed through 3D ground modeling to utilize the currently operating geotechnical survey information DB and ground water behavior information for risk prediction. Additionally, using these results, the relationship between the actual ground subsidence occurrence history and ground conditions and ground water level changes was confirmed. Furthermore, the methodology used to visualize the risk of ground subsidence was presented by reconstructing the engineering characteristics of the soil presented according to the Unified Soil Classification System (USCS) in the existing geotechnical survey information into the internal erosion sensitivity of the soil, Based on the result, it was confirmed that the ground in the area where the ground subsidence occurred consists of more than 40% of sand (SM, SC, SP, SW) vulnerable to internal erosion. In addition, the effect of the occurrence frequency of ground subsidence due to the change in ground water level is also confirmed.

• Journal of the Korean GEO-environmental Society
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• v.23 no.4
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• pp.5-10
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• 2022

Recently, ground subsidence has been continuously occurring in downtown areas, threatening the safety of citizens. Various underground facilities such as water and sewage pipelines and communication pipelines are buried under the road. It is reported that the cause of ground subsidence is the deterioration of various facilities and the reckless development of the underground. In particular, it is known that the biggest cause of ground subsidence is the aging of sewage pipelines. As an existing study related to this, several representative factors of sewage pipelines were selected and a study to predict the risk of ground subsidence through statistical analysis has been conducted. In this study, a data SET was constructed using the characteristics of OO city's sewage pipe characteristics and ground subsidence data, The data set constructed from the characteristics of the sewage pipe of OO city and the location of the ground subsidence was used. The goal of this study was to present a classification model for the occurrence of ground subsidence according to the characteristics of sewage pipes through machine learning. In addition, the importance of each sewage pipe characteristic affecting the ground subsidence was calculated.

• Tunnel and Underground Space
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• v.33 no.3
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• pp.169-188
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• 2023

Fires in tunnels are characterized by higher temperature rise and higher maximum temperatures compared to ground fires. For this reason, countries such as the Netherlands and Germany have developed separate temperature-time curves for use in tunnel fires. Fires in tunnels cause damage to the tunnel lining, such as loss of section and deterioration of the material properties. This study reviewed the design concept of fire stability of structures, section loss due to spalling, changes in physicochemical and mechanical properties of tunnel lining materials, fireproofing materials for structure safety, and fire damage prediction models. In order to secure the stability of a structure against fire, it is necessary to identify the type of structure and the possible fire load at the design stage, identify the expected section loss and damage range, and prepare for such damage through fireproofing materials. In this study, we have summarized the matters that can be referred to in performing such a series of tasks and presented our opinions on them.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.