• Wind and Structures
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• v.34 no.2
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• pp.231-257
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• 2022

Transmission lines systems are important components of the electrical power infrastructure. However, these systems are vulnerable to damage from high wind events such as hurricanes. This study presents the results from a 1:50 scale aeroelastic model of a multi-span transmission lines system subjected to simulated hurricane winds. The transmission lines system considered in this study consists of three lattice towers, four spans of conductors and two end-frames. The aeroelastic tests were conducted at the NSF NHERI Wall of Wind Experimental Facility (WOW EF) at the Florida International University (FIU). A horizontal distortion scaling technique was used in order to fit the entire model on the WOW turntable. The system was tested at various wind speeds ranging from 35 m/s to 78 m/s (equivalent full-scale speeds) for varying wind directions. A system identification (SID) technique was used to evaluate experimental-based along-wind aerodynamic damping coefficients and compare with their theoretical counterparts. Comparisons were done for two aeroelastic models: (i) a self-supported lattice tower, and (ii) a multi-span transmission lines system. A buffeting analysis was conducted to estimate the response of the conductors and compare it to measured experimental values. The responses of the single lattice tower and the multi-span transmission lines system were compared. The coupling effects seem to drastically change the aerodynamic damping of the system, compared to the single lattice tower case. The estimation of the drag forces on the conductors are in good agreement with their experimental counterparts. The incorporation of the change in turbulence intensity along the height of the towers appears to better estimate the response of the transmission tower, in comparison with previous methods which assumed constant turbulence intensity. Dynamic amplification factors and gust effect factors were computed, and comparisons were made with code specific values. The resonance contribution is shown to reach a maximum of 18% and 30% of the peak response of the stand-alone tower and entire system, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.373-383
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• 2015

Spatial information has been widely used for efficient land use and management, disaster management, environment management, infrastructure management, corporate marketing, and cultural assets management, and the need for spatial information is expected to be increased. For this reason, central government, local government and public institutions must establish a National Spatial Information System (Fifteen systems related to spatial information managed by National Spatial Data Infrastructure Policy office, NSIS) framework that guarantees high accuracy and quality. The NSIS will provide convenience usage of spatial information in the field of decision-making or civil support. However the current National Spatial Information System is mainly established with separate processes, which causes data redundancy, deterioration of information, passive opening, and sharing of the spatial data. This study suggests 4 standards, which has been derived by applying value-chain model to NSIS data flow, and they are ‘Production and Establishment’, ‘Integration and Sharing’, ‘Application and Fusion’ and ‘Release and Opening’. Based on these standards, the 15 NSIS were analyzed to draw out implications and reforming directions were suggested. By following these suggestions we expect more recent, consist, accurate, and connected National Spatial Information Service which will be more open to public and then satisfy the demands.

• Ecology and Resilient Infrastructure
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• v.2 no.2
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• pp.128-136
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• 2015

River areas include channels, floodplains and all the areas affected by physical and ecological processes in river systems. It is noticeably different from present riparian zone which is bounded by dykes. In this study, two methods for delineation of a floodplain are proposed, which are used for evaluation of the function of a river. One of them is a geomorphology-based technique and the other is hydrology-based inundation analysis. For the Mankyung River, these two methods are applied to delineate the floodplain area. Areas delineated with both methods are mutually compared. The results show that the geomorphology-based method is suitable for the delineation of a valley bottom, including the floodplain in a broader sense, which is unlike an inundated area reflecting contemporary hydrologic conditions. Compared with other flood frequency areas, a 100-year flood inundation area was found reasonable to represent the spatial extent of a floodplain without regard to the longitudinal location along a river. However, it is necessary in certain rivers reach where the division of a channel exists to compare a geomorphological analysis on a valley bottom with an inundation area of different frequencies.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Smart Structures and Systems
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• v.22 no.6
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• pp.727-741
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• 2018

To mitigate vibrations, tuned mass dampers(TMD) are widely used for long span bridges or high-rise buildings. Due to some durability concerns, such as fluid degradation, oil leakage, etc., the alternative solutions, such as the non-contacted eddy current damping (ECD), are proposed for mechanical devices in small scales. In the present study, a new eddy current damping TMD (ECD-TMD) is proposed and developed for large scale civil infrastructure applications. Starting from parametric study on finite element analysis of the ECD-TMD, the new design is enhanced via using the permanent magnets to eliminate the power need and a combination of a copper plate and a steel plate to improve the energy dissipation efficiency. Additional special design includes installation of two permanent magnets at the same side above the copper plate to easily adjust the gap as well as the damping. In a case study, the proposed ECD-TMD is demonstrated in the application of a steel arch bridge to mitigate the wind-induced vibrations of the flexible hangers. After a brief introduction of the configuration and the installation process for the damper, the mitigation effects are measured for the ambient vibration and forced vibration scenarios. The results show that the damping ratios increase to 3% for the weak axis after the installation of the ECD-TMDs and the maximum vibration amplitudes can be reduced by 60%.

• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• Journal of Environmental Health Sciences
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• v.39 no.5
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• pp.474-481
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• 2013

Objectives: This study was conducted to investigate the application of microbial fuel cells (MFCs) to the wastewater treatment systems employed in the Living Building Challenge. Methods: I reviewed a range of information on decentralized wastewater treatment technologies such as composting toilets, constructed wetlands, recirculating biofilters, membrane bioreactors, and MFCs. Results: The Living Building Challenge is a set of standards to make buildings more eco-friendly using renewable resources and self-treating water systems. Although there are various decentralized wastewater treatment technologies available, MFCs have been considered an attractive future option for a decentralized system as used in the Living Building Challenge. MFCs can directly convert substrate energy to electricity with high conversion efficiency at ambient and even at low temperatures. MFCs do not require energy input for aeration if using open-air cathodes. Moreover, MFCs have the potential for widespread application in locations lacking water and electrical infrastructure Conclusions: This paper demonstrated the feasibility of MFCs as a novel decentralized wastewater treatment system employed in the Living Building Challenge.

• Smart Structures and Systems
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• v.4 no.6
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• pp.741-757
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• 2008

The research field of structural control has evolved from the development of passive devices since 1970s, through the intensive investigation on active systems in 1980s, to the recent studies of semi-active control systems in 1990s. Currently semi-active control is considered most promising in civil engineering applications. However, actual implementation of semi-active devices is still limited due mainly to their system maintenance and associated long-term reliability as a result of power requirement. In this paper, the concept of functionally upgraded passive devices is introduced to streamline some of the state-of-the-art researches and guide the development of new passive devices that can mimic the function of their corresponding semi-active control devices for various applications. The general characteristics of this special group of passive devices are discussed and representative examples are summarized. Their superior performances are illustrated with cyclic and shake table tests of two example devices: mass-variable tuned liquid damper and friction-pendulum bearing with a variable sliding surface curvature.

• Smart Structures and Systems
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• v.21 no.3
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• pp.287-303
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• 2018

Applications of energy harvesting from mechanical vibrations is becoming popular but the full potential of such applications is yet to be explored. This paper addresses this issue by considering an application of energy harvesting for the dual objective of serving as an indicator of structural health monitoring (SHM) and extent of control. Variation of harvested energy from an undamaged baseline is employed for this purpose and the concept is illustrated by implementing it for active vibrations of a pipe structure. Theoretical and experimental analyses are carried out to determine the energy harvesting potential from undamaged and damaged conditions. The use of energy harvesting as indicator for control is subsequently investigated, considering the effect of the introduction of a tuned mass damper (TMD). It is found that energy harvesting can be used for the detection and monitoring of the location and magnitude of damage occurring within a pipe structure. Additionally, the harvested energy acts as an indicator of the extent of reduction of vibration of pipes when a TMD is attached. This paper extends the range of applications of energy harvesting devices for the monitoring of built infrastructure and illustrates the vast potential of energy harvesters as smart sensors.