• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.287-292
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• 1998

In particle or short-fiber reinforced composites. cracking of the reinforcements is a significant damage mode because the broken reinforcements lose load carrying capacity. This paper deals with the load carrying capacity of intact and broken ellipsoidal inhomogeneities embedded in an infinite body and a damage theory of particle or short-fiber reinforce composites. The average stress in the inhomogeneity represents its load carrying capacity. and the difference between the average stresses of the intact t and broken inhomogeneities indicates the loss of load carrying capacity due to cracking damage. The composite in damage process contains intact and broken reinforcements in a matrix. An incremental constitutive relation of particle or short-fiber reinforced composites including the progressive cracking damage of the reinforcements have been developed based on the Eshelby's equivalent inclusion method and Mori and Tanaka's mean field concept. Influence of the cracking damage on the stress-strain response of the composites is demonstrated.

• Smart Structures and Systems
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• v.19 no.4
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• pp.449-461
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• 2017

One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

• Computers and Concrete
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• v.1 no.2
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• pp.131-150
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• 2004

We present in this work a coupled phenomenological chemo-mechanical model that represents the degradation of concrete-like materials. The chemical behaviour is described by the nowadays well known simplified calcium leaching approach. And the mechanical damage behaviour is described by a continuum damage model which involves the gradient of the damage quantity. The coupled nonlinear problem at hand is addressed within the context of the finite element method. For the equation governing the calcium dissolution-diffusion part of the problem, special care is taken to treat the highly nonlinear calcium conductivity and solid calcium functions. The algorithmic design is based on a Newton-type iterative scheme where use is made of a recently proposed relaxed linearization procedure. And for the equation governing the damage part of the problem, an augmented Lagrangian formulation is used to take into account the damage irreversibility constraint. Finally, numerical simulations are compared with experimental results on cement paste.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1065-1073
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• 2002

A new damage identification technique using static displacement data is developed to assess the structural integrity of bridge structures. In the conventional damage assessment techniques using dynamic response, it is usually difficult to obtain a significant natural frequencies variation from the measured data because the natural frequencies variation is intrinsically not sensitive to the damage of a bridge. In this proposed identification method, the stiffness reduction of the bridges can be estimated using the static displacement data measured periodically and a specific loading test is not required. The static displacement data due to the dead load of the bridge structure can be measured by devices such as a laser displacement sensor. In this study, structural damage is represented by the reduction in the elastic modulus of the element. The damage factor of the element is introduced to estimate the stiffness reduction of the bridge under consideration. Finally, the proposed algorithm is verified using various numerical simulation and compared with other damage identification method. Also, the effect of noise and number of damaged elements on the identification are investigated. The results show that the proposed algorithm is efficient for damage identification of the bridges.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.300-307
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• 2002

Damage estimation methods are classified into two groups according to the dependence on the FE model : signal-based and model-based methods. Signal-based damage estimation methods are generally appropriate for detection of damage location, whereas not effective for estimation of damage severities. Model-based damage estimation methods are difficult to apply directly to the structures with a large number of the probable damaged members. It is difficult to obtain the exact model representing the real bridge behavior due to the modeling errors. The modeling errors even may exceed the modal sensitivity on damage. In this study, Model-based damage detection method which can effectively consider the modeling errors is suggested. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness of the presented method.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Smart Structures and Systems
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• v.26 no.1
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• pp.35-47
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• 2020

This paper proposes the use of transmissibility functions combined with a machine learning algorithm, Artificial Neural Networks (ANNs), to assess damage in a truss bridge. A new approach method, which makes use of the input parameters calculated from the transmissibility function, is proposed. The network not only can predict the existence of damage, but also can classify the damage types and identity the location of the damage. Sensors are installed in the truss joints in order to measure the bridge vibration responses under train and ambient excitations. A finite element (FE) model is constructed for the bridge and updated using FE software and experimental data. Both single damage and multiple damage cases are simulated in the bridge model with different scenarios. In each scenario, the vibration responses at the considered nodes are recorded and then used to calculate the transmissibility functions. The transmissibility damage indicators are calculated and stored as ANNs inputs. The outputs of the ANNs are the damage type, location and severity. Two machine learning algorithms are used; one for classifying the type and location of damage, whereas the other for finding the severity of damage. The measurements of the Nam O bridge, a truss railway bridge in Vietnam, is used to illustrate the method. The proposed method not only can distinguish the damage type, but also it can accurately identify damage level.

• Smart Structures and Systems
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• v.24 no.4
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• pp.475-490
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• 2019

The detection of structural damage without a priori information on the healthy state is challenging. In order to address the issue, the study presents a baseline-free approach to detect damage in beam structures based on an actual influence line. In particular, a multi-segment function-fitting calculation is developed to extract the actual deflection influence line (DIL) of a damaged beam from bridge responses due to a passing vehicle. An intact basis function based on the measurement position is introduced. The damage index is defined as the difference between the actual DIL and a constructed function related to the intact basis, and the damage location is indicated based on the local peak value of the damage index curve. The damage basis function is formulated by using the detected damage location. Based on the intact and damage basis functions, damage severity is quantified by fitting the actual DIL using the least-square calculation. Both numerical and experimental examples are provided to investigate the feasibility of the proposed method. The results indicate that the present baseline-free approach is effective in detecting the damage of beam structures.

• Computers and Concrete
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• v.27 no.1
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• pp.29-39
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• 2021

This study aimed to develop a method for the determination of the damaged story in reinforced concrete (RC) structure with ambient vibrations, based on modified jerk energy methodology. The damage was taken as a localized reduction in the stiffness of the structural member. For loading, random white noise excitation was used, and dynamic responses from the finite element model (FEM) of 4 story RC shear frame were extracted at nodal points. The data thus obtained from the structure was used in the damage detection and localization algorithm. In the structure, two damage configurations have been introduced. In the first configuration, damage to the structure was artificially caused by a local reduction in the modulus of elasticity. In the second configuration, the damage was caused, using the Elcentro1940 and Kashmir2005 earthquakes in real-time history. The damage was successfully detected if the frequency drop was greater than 5% and the mode shape correlation remained less than 0.8. The results of the damage were also compared to the performance criteria developed in the Seismostruct software. It is demonstrated that the proposed algorithm has effectively detected the existence of the damage and can locate the damaged story for multiple damage scenarios in the RC structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.43-58
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• 2002

A methodology to nondestructively locate and estimate size of damage in beam-type structures using a few natural frequencies or a few mode shapes is presented. A damage-localization algorithm to locate damage from changes in natural frequencies and a damage-sizing algorithm to estimate crack-size from natural frequency perturbation are outlined. A damage index algorithm to localize and estimate severity of damage from monitoring changes in mode shapes is outlined. The frequency-based method and the mode-shape-based method are evaluated for several damage scenarios by locating and sizing damage in PS concrete beams lot which a few natural frequencies and mode shapes are generated from finite element models. The result of the analyses indicates that the two methods correctly localize and closely estimate the size of the crack simulated in the test beam.