• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.1
• /
• pp.1-8
• /
• 2017

Drinking water deficiency is prevalent in developing countries due to contamination of surface and ground water, difficulties of water treatment, and lack of water infrastructures. 'Rainwater For Drinking (RFD)' projects are emerging as one of the effective solutions globally since RFD systems provide safe drinking water from rainwater. In RFD projects, perception of local residents toward RFD project is essential as local residents must manage their RFD systems on their own after the project finishes. This research performed survey and interview to 209 local residents, who use RFD systems, and analyzed their general perception, expected effects and feared factors toward RFD projects. Through the research, it was shown that the most of the local residents have positive perception towards RFD projects' effectiveness (41.9%) and are willing to participate (58.9%). The top three expected effect factors of the RFD projects were 'supply of safe water source', 'vitalization of local community', and 'expansion of RFD system'. The top three feared factors were 'quality of rainwater', 'technical factors of RFD system', and 'maintenance of RFD system'. The research findings indicate that development of simple water quality measuring device and education of the local residents about RFD system is necessary for better maintenance of the RFD system after the project finishes.

• Journal of Korea Water Resources Association
• /
• v.48 no.2
• /
• pp.115-126
• /
• 2015

In recent years, debris flow disaster has occurred in multiple locations between high and low mountainous areas simultaneously with a flooding disaster in urban areas caused by heavy and torrential rainfall due to the changing global climate and environment. As a result, these disasters frequently lead to large-scale destruction of infrastructures or individual properties and cause psychological harm or human death. In order to mitigate these disasters more effectively, it is necessary to investigate what causes the damage with an integrated model of both disasters at once. The objectives of this study are to analyze the mechanism of debris flow for real basin, to determine the PMP and run-off discharge due to the DAD analysis, and to estimate the influence range of debris flow for fan area according to the scenario. To analyse the characteristics of debris flow at the real basin, the parameters such as the deposition pattern, deposit thickness, approaching velocity, occurrence of sediment volume and travel length are estimated from DAD analysis. As a results, the peak time precipitation is estimated by 135 mm/hr as torrential rainfall and maximum total amount of rainfall is estimated by 544 mm as typhoon related rainfall.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.31 no.6
• /
• pp.367-372
• /
• 2018

Defects in aging infrastructures such as pre-stressed concrete bridges and cable bridges can cause a collapse of the entire structure. Defects, however, are often located inside of the structures that they are not visible from the outside. For example, in PSC bridges, because reinforcement steels are encased by exterior covers, corrosion and void on the reinforcement steel cannot be detected with a visual inspection. Therefore, in this paper, a new non-destructive evaluation(NDE) method that can detect defects inside of structures is presented. The new method utilizes sending of electrical signals, a method often utilized in electrical engineering to detect any discontinuities on power cables. In order to confirm the applicability and accuracy of the method, some experiments were conducted in the laboratory. And to overcome the hardship of conducting experiments on real structures due to their enormous size, simualtions were conudcted using a commercial program, COMSOL. The results of the experiments were analyzed and compared to confirm the accuracy of the simualtions.

• Journal of the Korean GEO-environmental Society
• /
• v.20 no.2
• /
• pp.69-79
• /
• 2019

The coastal area forms various sedimentary layers according to the environmental conditions such as the topography and geological features of the upper region of the river, ocean currents, and river mouth. Therefore, identifying the characteristics of the marine clay deposited in the coastal area plays a key role in the investigation of the formation of soft ground. In general, alluvial grounds are formed by a variety of factors such as changes in topography and natural environment, they have very diverse qualities depending on the deposited region or sedimentation conditions. The most important thing for the construction of social infrastructures in soft ground areas is economical and efficient treatment of soft ground. In this study, the author collected data from diverse laboratory and field tests on five areas in western and southern offshore with relatively high reliability, and then statistically analyzed them, thereby presenting standard constants for construction design. Correlation between design parameters such as over consolidation ratio, preconsolidation pressure was analyzed using linear and non-linear regression analyses. Also, proposed distribution characteristics of design parameters in consideration of each region's uncertainty through statistical analyses such as normality verification, outlier removal.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.23 no.6
• /
• pp.549-558
• /
• 2021

In order to keep infrastructures such as tunnels and underground facilities safe, cracks of concrete lining in tunnel should be detected by regular inspections. Since regular inspections are accomplished through manual efforts using maintenance lift vehicles, it brings about traffic jam, exposes works to dangerous circumstances, and deteriorates consistency of crack inspection data. This study aims to provide methodology to automatically extract cracks from tunnel concrete lining images generated by the existing tunnel image acquisition system. Specifically, we train a deep learning based semantic segmentation model with open dataset, and evaluate its performance with the dataset from the existing tunnel image acquisition system. In particular, we compare the model performance in case of using all of a public dataset, subset of the public dataset which are related to tunnel surfaces, and the tunnel-related subset with negative examples. As a result, the model trained using the tunnel-related subset with negative examples reached the best performance. In the future, we expect that this research can be used for planning efficient model training strategy for crack detection.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.5
• /
• pp.543-553
• /
• 2023

This study was conducted to propose a simple method to evaluate the load-carrying capacity of RC slab bridges, which have been most frequently constructed in Korea. A number of RC slab bridges have been considerably deteriorated associate with the long service year. However, since these bridges are not included in the 1st and 2nd class infrastructures due to their short span length, they have been relatively neglected compared to other bridge types in terms of safety management. In the previous theoretical study, a process (draft) was proposed for evaluating the damage of RC slab bridges using the relationship between the displacement response ratio and the stiffness reduction rate derived by the measured displacement and natural frequency. In this paper, to verify the validity of the proposed damage evaluation process (draft), the results to the actual bridges were compared with the safety grade and the Matsui's deterioration index. In addition, to enhance the practical applicability of the existing process (draft), an improved method approximately evaluating the load-carrying capacity using only the measured natural frequency was presented. If an error of 10% of the load-carrying capacity is allowed, it is judged that the proposed damage evaluation process can be appropriately used not only for evaluating the safety of RC slab bridges, but also for determining priorities for their maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.6D
• /
• pp.745-752
• /
• 2009

Management of social infrastructure has been advanced from facility management (FM) to asset management (AM), which adopts the aggressive and proactive methods in predicting the deterioration of infrastructure, prevents failures, and eventually saves maintenance cost. Infrastructure asset management is not a simple engineering technique, but it is a new paradigm evolved from facility management practices. To implement the infrastructure asset management successfully, organizational reform is very important. This paper suggests critical success factors and key performance indicators to implement the infrastructure asset management for facility managers of government owned social infrastructures such as roads and bridges. Reorganizing the facility management group requires new vision, objectives, strategies for the paradigm-changing asset management. This paper uses Balanced Score Card (BSC) which is a proven method in measuring and setting new objectives for an organization. Once the performance indicators are reviewed repeatedly by facility managers through experts workshops, developed BSC can be used in practice. This paper discusses the development of robust BSC scoring method through in depth literature reviews and investigation of asset management practices of domestic and international cases.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.1A
• /
• pp.53-59
• /
• 2010

Recently, NDTs (Non-Destructive Techniques) using infrared camera are widely studied for detection of damage and void in RC (reinforced concrete) structures and they are also considered as an effective techniques for maintenance of infrastructures. The temperature on concrete surface depends on material and thermal properties such as specific heat, thermal conductivity, and thermal diffusion coefficient. Different porosity on cement mortar due to different mixture proportions can show different heat behavior in cooling stage. The porosity can affect physical and durability properties like strength and chloride diffusion coefficient as well. In this paper, active thermography which uses flash for heat induction is utilized and thermal characteristics on surface are evaluated. Samples of cement mortar with W/C (water to cement ratio) of 0.55 and 0.65 are prepared and physical properties like porosity, compressive strength, and chloride diffusion coefficient are evaluated. Then infrared thermography technique is carried out in a constant room condition (temperature $20{\sim}22^{\circ}C$ and relative humidity 55-60%). The mortar samples with higher porosity shows higher residual temperature at the cooling stage and also shows reduced critical time which shows constant temperature due to back wall effect. Furthermore, simple equation for critical time of back wall effect is suggested with porosity and experimental constants. These characteristics indicate the applicability of infrared thermography as an NDT for quality assessment of cement based composite like concrete. Physical properties and thermal behavior in cement mortar with different porosity are analyzed in discussed in this paper.

• Journal of the Korea Concrete Institute
• /
• v.25 no.5
• /
• pp.485-496
• /
• 2013

In recent years, frequent terror or military attacks by explosion or impact accidents have occurred. Examplary case of these attacks were World Trade Center collapse and US Department of Defense Pentagon attack on Sept. 11 of 2001. These attacks of the civil infrastructure have induced numerous casualties and property damage, which raised public concerns and anxiety of potential terrorist attacks. However, a existing design procedure for civil infrastructures do not consider a protective design for extreme loading scenario. Also, the extreme loading researches of prestressed concrete (PSC) member, which widely used for nuclear containment vessel, gas tank, bridges, and tunnel, are insufficient due to experimental limitations of loading characteristics. To protect concrete structures against extreme loading such as explosion and impact with high strain rate, understanding of the effect, characteristic, and propagation mechanism of extreme loadings on structures is needed. Therefore, in this paper, to evaluate the impact resistance capacity and its protective performance of bi-directional unbonded prestressed concrete member, impact tests were carried out on $1400mm{\times}1000mm{\times}300mm$ for reinforced concrete (RC), prestressed concrete without rebar (PS), prestressed concrete with rebar (PSR, general PSC) specimens. According to test site conditions, impact tests were performed with 14 kN impactor with drop height of 10 m, 5 m, 4 m for preliminary tests and 3.5 m for main tests. Also, in this study, the procedure, layout, and measurement system of impact tests were established. The impact resistance capacity was measured using crack patterns, damage rates, measuring value such as displacement, acceleration, and residual structural strength. The results can be used as basic research references for related research areas, which include protective design and impact numerical simulation under impact loading.

• Journal of Korean Society of Disaster and Security
• /
• v.12 no.2
• /
• pp.73-82
• /
• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.