• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.6
• /
• pp.10-16
• /
• 2020

Deterioration of reinforced concrete structure caused by chloride ingress is the main issue and regrading this, many studies have been investigated with both experiments and computational modelling. In addition to chloride diffusion, chloride sorption should be considered as a chloride transport mechanism in concrete structure and cracks formed in concrete structures are the main variable to evaluate the performance of the structures. In this study, after making two types of cracks width (0.1 and 0.3 mm) in reinforced concretes, chloride absorption tests were performed. Weight change and colour change using 0.1 AgNO3 solution from the samples were performed to measure chloride ingress. Image processing was also carried out to quantify range of colour change in carck face. From the result, it were confirmed that the amount of chloride absorption increases with exposure time and increasing crack width, and chlorides reached at steel depth within 1 hour. It would be possible that chloride can move through interface bewteen steel and concrete, thereby further study regarding this is required.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.25 no.1
• /
• pp.7-15
• /
• 2021

In this study, we developed Void Plywood Slab (VPS) that improved the shape of existing hollow materials. Its performance was evaluated through one-way flexural and one-way shear tests using the developed VPS. As a result of the one-way flexural performance tests of VPS, the yield load value for FPS series(longitudinal direction specimens with hollow materials) was approximately 97.5% compared to FPS-00(without hollow materials) specimen. The tests showed that the yield load was not much different. In addition, FNS series(transverse direction specimens with hollow materials) also represented about 97% of FPS-00 specimen. The one-way flexural performance was shown to have little impact from void materials. Therefore, it is confirmed that the presented system is applicable to the VPS to the slab design. The results of the one-way shear performance tests of VPS showed that it was about 92% compared to the SS-00(without hollow materials) specimen. These results were somewhat insufficient for the SS-00 specimen. Shear strength equation is expressed as the sum of shear force by concrete and shear force by reinforcement. However, in the case of void slab, it is believed that the concrete section has been deleted by the void material. However, the strength of the structure applied to the shear design, as with the flexural design, is also applied to the design based on the yield load value.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.23 no.1
• /
• pp.13-24
• /
• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.6
• /
• pp.206-216
• /
• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.23 no.1
• /
• pp.25-36
• /
• 2021

Hydrogen in hydrogen-electric vehicles has a wide range of combustion and explosion ranges, and is a combustible gas with a very fast flame propagation speed, so it has the risk of leakage, diffusion, ignition, and explosion. The fuel tank has a Thermally active Pressure Relief Device (TPRD) to reduce the risk of explosion and other explosions, and in the event of an accident, hydrogen inside the tank is released outside before an explosion or fire occurs. However, if an accident occurs in a semi-closed space such as an underground parking lot, the flow of air flow is smaller than the open space, which can cause the concentration of hydrogen gas emitted from the TPRD to accumulate above the explosion limit. Therefore, in this study, the leakage rate and concentration of hydrogen over time were analyzed according to the diameter of the nozzle of the TPRD. The diameter of the nozzle was considered to be 1 mm, 2.5 mm and 5 mm, and ccording to the diameter of the nozzle, the concentration of hydrogen in the underground parking lot increases in a faster time with the diameter of the nozzle, and the maximum value is also analyzed to be larger with the diameter of the nozzle. In underground parking lots where air currents are stagnant, hydrogen concentrations above LFL (Lowe Flammability Limit) were analyzed to be distributed around the nozzle, and it was analyzed that they did not exceed UFL (Upper Flammability Limit).

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.5
• /
• pp.9-16
• /
• 2020

A CFRP sheet has been applied as a structural reinforcement in the field, and various studies are conducted to evaluate the effect of CFRP sheets on reinforced concrete. Although many experiments were performed from previous studies, there are still limitations to analyze structural behaviors with various parameters in experiments directly. This study shows the FEA on structural behaviors of RC beams reinforced with CFRP sheets using ABAQUS software. To simulate debonding failure of CFRP sheets which is a major failure mode of RC beam with CFRP sheets, a cohesive element was applied between the bottom surface of RC beam and CFRP sheets. Both quasi-static method and 2-D symmetric FE model technique were performed to solve nonlinear problems. Results obtained from the FE models show good agreements with experimental results. It was found that reinforcement level of CFRP sheets is closely related to structural behavior of reinforced concrete including maximum strength, initial stiffness and deflection at failure. Also, as over-reinforcement of CFRP sheets could give rise to the brittle failure of RCstructure using CFRP sheets, an appropriate measure should be required when installing CFRP sheets in the structure.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.5
• /
• pp.103-110
• /
• 2020

In the recent seismic design code KDS 41 17 00, selection and modification procedures of ground motions which are used for nonlinear dynamic analyses were adopted. However, its practical applications are still limited due to the lack of literatures. This paper introduces case studies which used site-response analyses to select and modify ground motions for nonlinear dynamic analyses. Based on the case studies, design criterion for site-response analyses were reviewed thoroughly in the viewpoint of practical applications. It was found that design requirements related with bedrock motions are too conservative that ground motions are selected and modified in the excessive manner. It is especially true for low-rise building structures with period ranges including acceleration-sensitive regions. Even though surface motions have shown appropriate responses, such building structures have to re-select and re-modify ground motions based on pre-analysis procedures rather than post-ones according to the current seismic design code. Also, it was observed that building structures with soft soils under strong ground motions need more comprehensive investigations on soil properties and efficient analysis methods in order to perform site-response analyses. This is due to the fact that lack of reliabilities on soil properties and analysis methods could result in unstable site-responses.

• Journal of The Korean Association For Science Education
• /
• v.42 no.2
• /
• pp.201-214
• /
• 2022

The purpose of this study is to examine the characteristics of model of the experiment in students' open inquiry. The research is a reinterpretation of the data collected from the performance of a three-year research project under the theme of 'school science inquiry' the perspective of model of the experiment. The inquiry activities of a focus group made up of four students have been recorded seven times. The recorded files and transcribed copies were analyzed according to interpretive methods. Students' activities were divided into three modeling of the experiment units, considering the modeling unit that includes the process of starting from the problem until it gets solved. The results of the study include illuminating the dynamic process and characteristics of modeling of the experiment and discussing its educational meaning as a distributed cognitive system at each modeling unit. First, students, instruments, and the primitive form of calculation represented by the interaction between them turned out to be important factors in the distributed cognitive system that constitutes model of the experiment. Second, in the early stages, non-verbal activities were carried out in which students became familiar with instruments, and verbal quantitative signs were created when the activities were sufficiently carried out. The generated quantitative signs became a source of data and confidence that can be referenced in subsequent activities. Third, the specialization of instrumentalization occurred, and factors that were important in inquiry, such as variable control, appeared. The results of the study provide new implications for science education research and education, which have been centered on explanatory models, by unfolding the characteristics of model of the experiment that have not been noticed in science education through students' inquiry.

• Journal of the Society of Disaster Information
• /
• v.18 no.1
• /
• pp.146-153
• /
• 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 Korean Tunnelling and Underground Space Association
• /
• v.24 no.4
• /
• pp.341-353
• /
• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.