• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.105-116
• /
• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• Advances in concrete construction
• /
• v.1 no.4
• /
• pp.289-304
• /
• 2013

A reliable concrete constitutive material model is critical for an accurate numerical analysis simulation of reinforced concrete structures under extreme dynamic loadings including impact or blast. However, the formulation of concrete material model is challenging and entails numerous input parameters that must be obtained through experimentation. This paper presents a damage scale analytical model to characterize concrete material for its pre- and post-peak behavior. To formulate the damage scale model, statistical regression and finite element analysis models were developed leveraging twenty existing experimental data sets on concrete compressive strength. Subsequently, the proposed damage scale analytical model was implemented in the finite element analysis simulation of a reinforced concrete pier subjected to vehicle impact loading and the response were compared to available field test data to validate its accuracy. Field test and FEA results were in good agreement. The proposed analytical model was able to reliably predict the concrete behavior including its post-peak softening in the descending branch of the stress-strain curve. The proposed model also resulted in drastic reduction of number of input parameters required for LS-DYNA concrete material models.

• Journal of Environmental Science International
• /
• v.25 no.1
• /
• pp.41-56
• /
• 2016

In recent localized heavy rainfalls have been arising from abnormal climate change. People are concerning about damages with increasing the frequency of flooding. Therefore, we need to understand river hydraulic characteristics and management to reduce damage from flooding. To study hydraulic characterization of Sincheon experimental catchment HEC-RAS (Hydrologic Engineering Center River Analysis System) model which provided by U.S Army Corps of Engineers (USACE) was applied. This study analyzed and compared water level the frequency flood for 100 years and 200 years by clark unit Hydrography. The change of the water level of Daejeon bridge, Sincheon bridge and Singi bridge showed increased for all conditions. The flow rate for the Daejeon bridge and the Sincheon bridge showed an increase, but the Sinki bridge showed a decreasing flow rate overally, except for 1hour-100 years. The verification result showed that the model was able to simulate the water level with 0.4709 coefficient of determination and error ration ranging from 1 to 3%.

• Steel and Composite Structures
• /
• v.26 no.1
• /
• pp.115-123
• /
• 2018

Steel-concrete composite structure is widely applied to bridge engineering due to their outstanding mechanical properties and economic benefit. This paper studied a new type of steel-concrete composite anchorage system for a self-anchored suspension bridge and focused on the mechanical behavior and force transferring mechanism. A model with a scale of 1/2.5 was prepared and tested in ten loading cases in the laboratory, and their detailed stress distributions were measured. Meanwhile, a three-dimensional finite element model was established to understand the stress distributions and validated against the experimental measurement data. From the results of this study, a complicated stress distribution of the steel anchorage box with low stress level was observed. In addition, no damage and cracking was observed at the concrete surrounding this steel box. It can be concluded that the composite effect between the concrete surrounding the steel anchorage box and this steel box can be successfully developed. Consequently, the steel-concrete composite anchorage system illustrated an excellent mechanical response and high reliability.

• Structural Engineering and Mechanics
• /
• v.24 no.3
• /
• pp.355-374
• /
• 2006

Thin walled steel bridge-piers/columns are vulnerable to damage, when subjected to earthquake excitations. Local buckling, global buckling or interaction between local and global buckling usually is the cause of this damage, which results in significant strength reduction of the member. In this study new innovative design concepts, "thin-walled corrugated steel columns" and "thin-walled cellular steel columns" are presented, which allow the column to undergo large plastic deformations without significant strength reduction; hence dissipate energy under cyclic loading. It is shown that, compared with the conventional designs, circular and stiffened box sections, these new innovative concepts might results in cost-effective designs, with improved buckling and ductility properties. Using a finite element model, that takes the non-linear material properties into consideration, it is shown that the corrugations will act like longitudinal stiffeners that are supporting each other, thus improving the buckling behavior and allowing for reduction of the overall wall thickness of the column.

• Journal of the Society of Disaster Information
• /
• v.17 no.3
• /
• pp.556-567
• /
• 2021

Purpose: In this study, various methods of deep learning-based automatic damage analysis technology were reviewed based on images taken through Unmanned Aerial Vehicle to more efficiently and reliably inspect the exterior inspection and inspection of railway bridges using Unmanned Aerial Vehicle. Method: A deep learning analysis model was created by defining damage items based on the acquired images and extracting deep learning data. In addition, the model that learned the damage images for cracks, concrete and paint scaling·spalling, leakage, and Reinforcement exposure among damage of railway bridges was applied and tested with the results of automatic damage analysis. Result: As a result of the analysis, a method with an average detection recall of 95% or more was confirmed. This analysis technology enables more objective and accurate damage detection compared to the existing visual inspection results. Conclusion: through the developed technology in this study, it is expected that it will be possible to analysis more accurate results, shorter time and reduce costs by using the automatic damage analysis technology using Unmanned Aerial Vehicle in railway maintenance.

• 한국지형공간정보학회:학술대회논문집
• /
• 1994.11a
• /
• pp.32-42
• /
• 1994

A GIS-based regional risk analysis program to interactively study the vulnerability of bridges in a regional highway network is described. The analysis utilizes three major components. The use of a GIS system as the integrating environment to display geographic data, to handle inquiries and to display the results of a query. A risk model for bridges which can predict the level of damage due to a particular intensity of ground motion at a bridge site. A ground motion attenuation model to predict the intensity of ground motion at a particular bridge. The interactive components are supported by data files which encode characteristics such as potential earthquake sources and magnitudes, and characteristics of the bridges which are important for damage and failure analysis.

• Journal of Ocean Engineering and Technology
• /
• v.22 no.1
• /
• pp.75-82
• /
• 2008

A vibration-based damage-monitoring scheme is proposed that would generate an alarm showing the occurrence and location of damage under temperature-induced uncertainty conditions. Experiments on a model plate-girder bridge are described, for which a set of modal parameters was measured under uncertain temperature conditions. A damage-alarming model is formulated to statistically identify the occurrence of damage by recognizing the patterns of damage-driven changes in the natural frequencies of the test structure and by distinguishing temperature-induced off-limits. A damage index method based on the concept of modal strain energy is implemented in the test structure to predict the location of damage. In order to adjust for the temperature-induced changes in the natural frequencies that are used for damage detection, a set of empirical frequency correction formulas is analyzed from the relationship between the temperature and frequency ratio.

• Earthquakes and Structures
• /
• v.26 no.2
• /
• pp.87-96
• /
• 2024

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

• Structural Engineering and Mechanics
• /
• v.53 no.3
• /
• pp.481-495
• /
• 2015

Many hydropower stations in southwest China are located in regions of brittle rock mass with high geo-stresses. Under these conditions deep fractured zones often occur in the sidewalls of the underground caverns of a power station. The theory and methods of fracture and damage mechanics are therefore adopted to study the phenomena. First a flexibility matrix is developed to describe initial geometric imperfections of a jointed rock mass. This model takes into account the area and orientation of the fractured surfaces of multiple joint sets, as well as spacing and density of joints. Using the assumption of the equivalent strain principle, a damage constitutive model is established based on the brittle fracture criterion. In addition the theory of fracture mechanics is applied to analyze the occurrence of secondary cracks during a cavern excavation. The failure criterion, for rock bridge coalescence and the damage evolution equation, has been derived and a new sub-program integrated into the FLAC-3D software. The model has then been applied to the stability analysis of an underground cavern group of a hydropower station in Sichuan province, China. The results of this method are compared with those obtained by using a conventional elasto-plastic model and splitting depth calculated by the splitting failure criterion proposed in a previous study. The results are also compared with the depth of the relaxation and fracture zone in the surrounding rock measured by field monitoring. The distribution of the splitting zone obtained both by the proposed model and by the field monitoring measurements are consistent to the validity of the theory developed herein.