• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.893-902
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• 2005

Reasonable prediction of residual capacity of fire-damaged reinforced columns is important for both the safety measurement and the rehabilitation of the reinforced concrete structures suffered from exposure to extensive fire. In order to predict the residual behavior of fire-damaged reinforced concrete columns, its predictive model must be able to take into account the amount of heat transferred into the column, the level of deterioration of constituent materials and various column geometries. The numerical model presented in this research includes all these factors. The model has been shown to reasonably predict the residual behavior of fire-damaged columns. Parametric studies were performed using this model for the effects of cover thickness, exposure time to fire and column geometries on the residual behavior of reinforced concrete columns. It was found that serious damage on the residual capacity of column resulted from a longer exposure time to fire but only marginal differences from other factors.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.3
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• pp.56-61
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• 2012

The most common deterioration cause of concrete structures over the world is chloride ions attacks. Thus, service life modeling of concrete is a crucial issue in civil engineering society. Many studies on the durability of concrete have been accomplished, however, it is not easy to review literatures about environmental analysis. Since the durability of concrete depends on the properties of the surface concrete. micro-climatic condition which influences on surface concrete realistically should be considered. This study is devoted to analysis the micro-climatic condition of concrete structures, based on the in-situ monitoring of weather in marine environment. The effect of degree of saturation on chloride diffusivity of concrete is also examined. It is expected that the result of this work should be available for the prediction of chloride profile of marine concrete.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.8
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• pp.98-103
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• 2015

Power plant is that very high reliability when industrial and economic impact on the overall electric power system is required, it is essential to improve the reliability, especially the fault prediction diagnosis. Since an accident caused by the partial discharge in the power plant is above state has a faster response characteristic than the other indications in the case of any, the partial discharge generated in the power plant immediately detect the deterioration of insulation due to the accident of the power plant and the non-drawn It should prevent or reduce. Partial Discharge Measuring Systems for UHV SF6 Gas Insulated Switchgear and power transformer on site installed has some probability of abnormal recognition in case of non-flexible deal with on site noise. Many methode to eliminate these kinds of noises, UHF Detection System is chosen as purchase description in Korea, but this system having a bandwidth between 500MHz 1.5GHz wide band. Initial install periods(about 20 years ago), this band had no strong signal source, but in these days this wide band have strong signals, such as LTE. So, module described in this paper is designed as simultaneously use with wide and narrow band for solve this noise problem, and introduce this system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.68-76
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• 2016

The present study proposes the definition of service life and the end-of-life criterion for bridge maintenance. Bridges begin to deteriorate as soon as they are put into service. Effective bridge maintenance requires sound understanding of the deterioration mechanism as well as the expected service life. In order to determine the expected service life of a bridge for effective bridge maintenance, it is necessary to have a clear definition of service life and end-of-life. However, service life can be viewed from several perspectives based on literature review. The end of a bridge's life can be also defined by more than one perspective or performance measure. This study presents definition of service life which can be used for bridge maintenance and the end-of life criterion using the performance measure such as a damage score. The regression model can predict an average service life of bridges using the proposed end-of-life criterion.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.193-198
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• 2023

The rapid aging of the veterans has reached a level that cannot handle the demand for veterans care through the existing veterans care infrastructure. Therefore, it is urgent to improve the quality of the overall service of veterans due to the deterioration of the quality of nursing services for veterans with various underlying diseases compared to general patients and the long-term waiting for admission to the veterans care center. In this situation, about 640,000 people are admitted to veterans care institutions, but only about 5% of them can enter the veterans care center smoothly. As of June 2020, the number of people waiting to enter the veterans care center exceeds 1,000, including 520 at Suwon Veterans Nursing Home, 1 at Gwangju Veterans Nursing Home, 47 at Gimhae Veterans Nursing Home, 39 at Daegu Veterans Nursing Home, 86 at Namyangju Veterans Nursing Home.. Therefore, in order to predict those who want to enter the Veterans Nursing Home and wait for admission, and to find an important basis for resolving the long-term atmosphere, the ratio of future care providers is predicted in 2022-2050 and 2022-2024 to establish a cooperative system. As a result, 6,988 people in 2022, 6,797 people in 2023, and 6,606 people in 2024 can be admitted when 'preferred linkage', and 12,057 people in 2022 when 'expanded linkage'. It was found that 11,837 people in 2023 and 11,618 people in 2024 could be admitted. This was derived by estimating the percentage of people who wish to enter the Veterans Nursing Home when linking private nursing homes, and eventually "additional acceptance" of 22.5% in 2022, 20.9% in 2023, 19.4% in 2024, and 38.8% in 2023, 36.3% in 2023, and 34.1% in 2024 are most efficiently available.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.138-151
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• 2023

Korea's port infrastructure is rapidly aging, with old port facilities with more than 30 years of public life expected to surge from about 23% in 2019 to 47% in 2029. Traditional, aging ports lose competitiveness in logistics processing, reducing development around the port and increasing human casualties due to the human resource-based maintenance of the facilities. Therefore, it is necessary to solve this problem by establishing systematic management technology based on a digital twin. This research aimed to present the specific implementation steps of a digital twin reflecting smart port technology through cases of port infrastructure disasters, aging status, and smart ports. The study analyzed the port infrastructure linkage system and created and mapped scenarios essential for digital twin implementation. Three-dimensional (3D) modeling and simulation data for disaster and aging management among existing port infrastructure systems were collected. A digital twin port was implemented with 3D modeling. It implements a port digital twin simulation that links data such as sensing data and image data acquired from the port infrastructure in real time. Implementing a digital twin port for port infrastructure disasters and aging management can secure predictive port infrastructure management and disaster safety

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.143-154
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• 2022

Corrosion of steel reinforcement is considered as the main cause of concrete structures deterioration, especially those under humid environmental conditions. Hence, fiber reinforced polymer (FRP) bars are being increasingly used as a replacement for conventional steel owing to their non-corrodible characteristics. However, predicting the shear strength of beams reinforced with FRP bars still challenging due to the lack of robust shear theory. Thus, this paper aims to develop an explicit data driven based model to predict the shear strength of FRP reinforced beams using multi-objective evolutionary polynomial regression analysis (MOGA-EPR) as data driven models learn the behavior from the input data without the need to employee a theory that aid the derivation, and thus they have an enhanced accuracy. This study also evaluates the accuracy of predictive models of shear strength of FRP reinforced concrete beams employed by different design codes by calculating and comparing the values of the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²), and percentage of prediction within error range of ±20% (a20-index). Experimental database has been developed and employed in the model learning, validation, and accuracy examination. The statistical analysis illustrated the robustness of the developed model with MAE, RMSE, 𝜇, 𝜎, R², and a20-index of 14.6, 20.8, 1.05, 0.27, 0.85, and 0.61, respectively for training data and 10.4, 14.1, 0.98, 0.25, 0.94, and 0.60, respectively for validation data. Furthermore, the developed model achieved much better predictions than the standard predictive models as it scored lower MAE, RMSE, and 𝜎, and higher R² and a20-index. The new model can be used in future with confidence in optimized designs as its accuracy is higher than standard predictive models.

• Journal of the Korea Concrete Institute
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• v.15 no.4
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• pp.606-614
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• 2003

The major cause of deterioration for the concrete bridge decks exposed to de-icing chemicals would be chloride-induced reinforcement corrosion. Thus, in this paper, in order to predict time to corrosion for concrete bridge decks in the urban area, chloride concentration was measured with depth from the surface. A frequency analysis on surface chloride concentration and chloride diffusion coefficient of concrete bridge deck equals 0.192, 29.828 in the scale parameter and 7.899, 1.983 in the shape parameter of gamma distribution. The average value of surface chloride concentration equals 1.5 kg/㎥ and condenses from 1 to 2 kg/㎥ in the level of probability 70%. From the probabilistic results, it is confirmed that 26mm of minimum cover depth in order to target 20 years over is calculated. The countermeasure strategy to extend the service life of concrete bridge deck exposed to de-icing chemicals would be an effective method to increase cover depth and to place high performance concrete, which could lead to reduce the chloride diffusion coefficient and distribution range.