• Smart Structures and Systems
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• v.12 no.3_4
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• pp.291-308
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• 2013

A novel concept of transmissibility based on a wavelet transform for structural damage detection is presented in this paper. The main objective of the research was the development of a method for detecting slight damage at the incipient stage. As a vibration-based approach, the concept of transmissibility has attracted considerable interest because of its advantages and effectiveness in damage detection. However, like other vibration-based methods, transmissibility-based approaches suffer from insensitivity to slight local damage because of the regularity of the traditional Fourier transform. Therefore, the powerful signal processing techniques must be found to solve this problem. Wavelet transform that is able to capture subtle information in measured signals has received extensive attention in the field of damage detection in recent decades. In this paper, we first propose a novel transmissibility concept based on the wavelet transform. Outlier analysis was adopted to construct a damage detection algorithm with wavelet-based transmissibility. The feasibility of the proposed method was numerically investigated with a typical six-degrees-of-freedom spring-mass system, and comparative investigations were performed with a conventional transmissibility approach. The results demonstrate that the proposed transmissibility is more sensitive than conventional transmissibility, and the former is a promising tool for structural damage detection at the incipient stage.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.4
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• pp.291-302
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• 2004

Blast-induced anisotropic rock damage around a blast-hole was analyzed by a using numerical method with user-defined subroutine based on continuum damage mechanics. Anisotropic blasting pressure was evaluated by applying anisotropic ruck characteristics to analytical solution which is a function of explosive and rock properties. Anisotropic rock damage was evaluated by applying the proposed anisotropic blasting pressure. Blast-induced isotropic rock damage was also analyzed. User-defined subroutines to solve anisotropic and isotropic damage model were coded. Initial rock damages in natural ruck were considered in anisotropic and isotropic damage models. Blasting pressure and elastic modulus of rock were major influential parameters from parametric analysis results of isotropic rock damage. From the results of anisotropic rock damage analysis, blasting pressure was the most influential parameter. Anisotropic rock damage area in horizontal direction was approximately 34% larger and about 12% smaller in vertical direction comparing with isotropic rock damage area. Isotropic rock damage area under fully coupled charge condition was around 30 times larger than that under decoupled charge condition. Blasting pressure under fully coupled charge condition was estimated to be more than 10 times larger than that of decoupled charge condition.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.2
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• pp.119-128
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• 2016

In a performance-based design, the structural safety is estimated from pre-defined damage states and corresponding damage indices. Both damage states and damage indices are well defined for above-ground structures, but very limited studies have been performed on underground structures. In this study, we define the damage states and damage indices of a cut-and-cover box tunnel which is one of typical structures used in metro systems, under a seismic excitation from a series of inelastic frame analyses. Three damage states are defined in terms of the number of plastic hinges that develop within the structure. The damage index is defined as the ratio of the elastic moment to the yield moment. Through use of the proposed index, the inelastic behavior and failure mechanism of box tunnels can be simulated and predicted through elastic analysis. In addition, the damage indices are linked to free-field shear strains. Because the free-field shear strain can be easily calculated from a 1D site response analysis, the proposed method can be readily used in practice. Further studies are needed to determine the range of shear strains and associated uncertainties for various types of tunnels and site profiles. However, the inter-linked platform of damage state - damage index - shear wave velocity - shear strain provides a novel approach for estimating the inelastic response of tunnels, and can be widely used in practice for seismic designs.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.594-601
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• 2020

Purpose: The purpose of the present study was to identify factors affecting anxiety about disaster damage potential in Gyonggi-do and evacuation behavior that influences evacuation behavior. Method: Multiple regression analysis was performed to test the hypothesis and to analyze the influence of anxiety about disaster damage potential and perceived stress, and analyzed similarity in correspondence between age and anxiety about disaster damage potential. Results: The anxiety about disaster damage potential of a group vulnerable to safety and anxiety about disaster damage potential of disaster system collapse were perceived in close proximity. Disaster system collapse, evacuation life, and natural disasters were found to be factors affecting perceived stress. Stress and natural disasters were found to be influencing factors on evacuation behavior. Conclusion: The necessity of managing stress was confirmed since anxiety about natural disaster damage potential and stress affect evacuation behavior. The recent experiences of heavy rain disasters indicate that the anxiety about disaster damage potential is expected to increase. The findings also indicate the importance of preventive planning and psychological management to manage the anxiety about disaster damage potential.

• Smart Structures and Systems
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• v.25 no.5
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.513-520
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• 2017

In order to analyze flood damage mitigation effects, it is necessary not only to analyze inundation areas and depth through hydraulic and hydrological analysis but also to estimate flood damages. Flood damages of structure and contents of buildings are generally analyzed according to the flood depth. In this study, we developed and applied flood depth-damage functions for the school buildings based on actual damage data. In addition, the development and modification procedure of flood depth-damage functions for school buildings is presented in this paper, and the developed damage functions are verified by comparing them with the existing method. It is expected that the process of developing and applying flood depth-damage functions presented in this study can be used in the cost benefit analysis of flood damage mitigation measures.

• Advances in concrete construction
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• v.1 no.2
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• pp.187-200
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• 2013

The damage level in structures (global scale), elements (intermediate scale) and sections (local scale) can be evaluated using a single parameter called the "Damage Index". Part of the damage attributed to the local scale relates to the damage sustained by the materials of which the section is made. This study investigates the damage of concrete subjected to monotonic compressive loading using four different damage models - one proposed here for the first time and three other well-known models. The analytical results show that the proposed model is promising yet simple and effective for evaluating the damage of concrete. The proposed damage model of concrete with its promising characteristics indicated, appears to be a useful tool in the damage assessment of structures made of concrete.

• Earthquakes and Structures
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• v.15 no.5
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• pp.529-540
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• 2018

The influences of initial damage paths and aftershock (AS) spectral shape on the assessment of AS collapse fragility are investigated. To do this, a four-story ductile reinforced concrete (RC) frame structure is employed as the study case. The far-field earthquake records recommended by FEMA P695 are used as AS ground motions. The AS incremental dynamic analyses are performed for the damaged structure. To examine the effect of initial damage paths, a total of six kinds of initial damage paths are adopted to simulate different initial damage states of the structure by pushover analysis and dynamic analysis. For the pushover-based initial damage paths, the structure is "pushed" using either uniform or triangle lateral load pattern to a specified damage state quantified by the maximum inter-story drift ratio. Among the dynamic initial damage paths, one single mainshock ground motion or a suite of mainshock ground motions are used in the incremental dynamic analyses to generate a specified initial damage state to the structure. The results show that the structure collapse capacity is reduced as the increase of initial damage, and the initial damage paths show a significant effect on the calculated collapse capacities of the damaged structure (especially at severe damage states). To account for the effect of AS spectral shape, the AS collapse fragility can be adjusted at different target values of ${\varepsilon}$ by using the linear correlation model between the collapse capacity (in term of spectral intensity) and the AS ${\varepsilon}$ values, and coefficients of this linear model is found to be associated with the initial damage states.

• Smart Structures and Systems
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• v.14 no.5
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• pp.917-942
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• 2014

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.