• Geomechanics and Engineering
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• v.18 no.5
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• pp.535-543
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• 2019

Building on/with expansive soils with no treatment brings complications. Compacted expansive soils specifically fall short in satisfying the minimum requirements for transport embankment infrastructures, requiring the adoption of hauled virgin mineral aggregates or a sustainable alternative. Use of hauled aggregates comes at a high carbon and economical cost. On average, every 9m high embankment built with quarried/hauled soils cost $12600MJ.m^{-2}$ Embodied Energy (EE). A prospect of using mixed cutting-arising expansive soils with industrial/domestic wastes can reduce the carbon cost and ease the pressure on landfills. The widespread use of recycled materials has been extensively limited due to concerns over their long-term performance, generally low shear strength and stiffness. In this contribution, hydromechanical properties of a waste tyre sand-sized rubber (a mixture of polybutadiene, polyisoprene, elastomers, and styrene-butadiene) and expansive silt is studied, allowing the short- and long-term behaviour of optimum compacted composites to be better established. The inclusion of tyre shred substantially decreased the swelling potential/pressure and modestly lowered the compression index. Silt-Tyre powder replacement lowered the bulk density, allowing construction of lighter reinforced earth structures. The shear strength and stiffness decreased on addition of tyre powder, yet the contribution of matric suction to the shear strength remained constant for tyre shred contents up to 20%. Reinforced soils adopted a ductile post-peak plastic behaviour with enhanced failure strain, offering the opportunity to build more flexible subgrades as recommended for expansive soils. Residual water content and tyre shred content are directly correlated; tyre-reinforced silt showed a greater capacity of water storage (than natural silts) and hence a sustainable solution to waterlogging and surficial flooding particularly in urban settings. Crushed fine tyre shred mixed with expansive silts/sands at 15 to 20 wt% appear to offer the maximum reduction in swelling-shrinking properties at minimum cracking, strength loss and enhanced compressibility expenses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.369-380
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• 2019

When a extreme loading such as blast is applied to prestressed concrete (PSC) structures and infrastructures for an instantaneous time, serious property damages and human casualties occur. However, a existing design procedure for PSC structures such as prestressed containment vessel (PCCV) and gas storage tank do not consider a protective design for extreme internal blast scenario. Particularly, an internal blast is much more dangerous than that of external blast. Therefore, verification of the internal blast loading is required. In this paper, the internal blast resistance capacity of PSC member is evaluated by performing internal blast tests on RC and bi-directional PSC scaled down specimens. The applied internal blast loads were 22.68, 27.22, and 31.75 kg (50, 60, and 70 lbs) ANFO explosive charge at 1,000 mm standoff distance. The data acquisitions include blast pressure, deflection, strain, crack patterns, and prestressing force. The test results showed that it is possible to predict the damage area to the structure when internal blast loading occurs in PCCV structures.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.599-606
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• 2021

Water Distribution Networks, one of the social infrastructures buried underground, has the function of transporting and supplying purified water to customers. In recent years, as measurement capability is improved, a number of studies related to leak recognition and detection by applying a deep learning technique based on flow rate data have been conducted. In this study, a cognitive model for leak occurrence was developed using an LSTM-based deep learning algorithm that has not been applied to the waterworks field until now. The model was verified based on the assumed data, and it was found that all cases of leaks of 2% or more can be recognized. In the future, based on the proposed model, it is believed that more precise results can be derived in the prediction of flow data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.509-517
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• 2022

The demand for underground infrastructures such as tunnels is expanding due to rapid urbanization. Tunnels in urban areas are usually constructed adjacent to structures supported by piles. Therefore, a proper understanding of pile-tunnel interaction due to tunnel excavation activities is vital. Thus, in this study, a numerical analysis is conducted to analyze pile settlements, ground surface settlements and shear deformations above an existing tunnel subject to the presence of an adjacent tunnelling, with vertical offsets, the number of piles and the pile spacing considered as variables in the analysis. The results show that the vertical offsets between the tunnel crown and the pile tip generatelarger settlement than the pile spacing. In addition, the vertical offset shows an inversely proportional relationship to the shear deformation due to new tunnelling.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.50-57
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• 2023

Autonomous driving technologies have been gradually improved for road traffic owing to the development of artificial intelligence. Since the truck platooning is beneficial in terms of the associated transporting expenses, the Connected-Automated Vehicle technology is rapidly evolving. The structural performance is, however, rarely investigated to capture the effect of truck platooning on civil infrastructures.In this study, the dynamic behavior of bridges under truck platooning was investigated, and the amplification factor of responses was estimated considering several parameters associated with the driving conditions. Artificial intelligence techniques were used to estimate the maximum response of the mid span of a bridge as the platooning vehicles passing, and the importance of the parameters was evaluated. The most suitable algorithm was selected by evaluating the consistency of the estimated displacement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5C
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• pp.313-322
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• 2006

Liquefaction of soil foundation is one of the major seismic damage types for infrastructures. In this paper, deterministic and probabilistic approaches for the evaluation of liquefaction potential are briefly summarized and the risk assessment method is newly proposed using seismic fragility and seismic hazard analyses. Currently the deterministic approach is widely used to evaluate the liquefaction potential in Korea. However, it is very difficult to handle a certain degree of uncertainties in the soil properties such as elastic modulus and resistant capacity by deterministic approach, and the probabilistic approaches are known as more promising. Two types of probabilistic approaches are introduced including (1) the reliability analysis (to obtain probability of failure) for a given design earthquake and (2) the seismic risk analysis of liquefaction for a specific soil for a given service life. The results from different methods show a similar trend, and the liquefaction potential can be more quantitatively evaluated using the new risk analysis method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.605-609
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• 2006

In this study, two kinds of smart accelerometers are investigated for the application of smart sensors to the structural health monitoring of infrastructures. Smart optical Fiber Bragg Grating (FBG) type and Micro-Electo-Mechanical System (MEMS) type accelerometers are selected for this study and the high sensitive ICP type accelerometer is used for the reference sensor. Small size shaking table tests were performed with 3-story shear building model using random input ground motions. The output only modal identification was carried out using stochastic subspace identification and the performances of sensors are compared in modal domain indirectly. The modal sensitivity method was applied to update the story stiffness of numerical model and the updated results were verified using the additional experiments for the same structure with additional mass.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.663-673
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• 2010

We are developing asset management information systems to introduce the preventive/proactive approach at operation and management (O&M) of infrastructures. The objective of this study is to explore the future direction for development and operation of asset management information systems. So, we developed the success model and selected the evaluation criteria for analyzing user satisfaction to assess the expected performance of asset management information systems and the degree of impact on asset management functions to operation and management of highway transportation facilities. We estimated the relative importance weight according to the selected evaluation criteria through AHP analysis. We verified the logical consistency of the importance weight and exclude biased outlier from importance weight group using the concept of the Compatibility.

• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.