• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.3
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• pp.101-107
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• 2014

Damage location and extent of structure could be detected by the inverse analysis on dynamic response properties such as frequencies and mode shapes. The dynamic response of building structures has many noise and affected by nonstructural members and, above all, the behavior of building structure is more complex than civil structure and this makes the damage detection difficult. In recent researches the damage is detected by the indirect index such as sensitivity or assumed values. However, for the more reasonable damage detection, it needs to use the damage index directly induced from dynamic equation. The purpose of this study is to provide the damage detection method on shear building structures by the damage index directly induced from dynamic equation. The provided damage index could be estimated from measured mode shape of undamaged structure and frequency difference between undamaged and damaged structure. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. The damage index at damaged story represents (-) sign and 15 times than other undamaged sories.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.277-293
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• 2024

Shored Mechanically Stabilized Earth (SMSE) walls are types of soil retaining structures that increase soil stability under static and dynamic loads. The damage caused by an earthquake can be determined by evaluating the probabilistic seismic response of SMSE walls. This study aimed to assess the seismic performance of SMSE walls and provide fragility curves for evaluating failure levels. The generated fragility curves can help to improve the seismic performance of these walls through assessing and controlling variables like backfill surface settlement, lateral deformation of facing, and permanent relocation of the wall. A parametric study was performed based on a non-linear elastoplastic constitutive model known as the hardening soil model with small-strain stiffness, HSsmall. The analyses were conducted using PLAXIS 2D, a Finite Element Method (FEM) program, under plane-strain conditions to study the effect of the number of geogrid layers and the axial stiffness of geogrids on the performance of SMSE walls. In this study, three areas of damage (minor, moderate, and severe) were observed and, in all cases, the wall has not completely entered the stage of destruction. For the base model (Model A), at the highest ground acceleration coefficient (1 g), in the moderate damage state, the fragility probability was 76%. These values were 62%, and 54%, respectively, by increasing the number of geogrids (Model B) and increasing the geogrid stiffness (Model C). Meanwhile, the fragility values were 99%, 98%, and 97%, respectively in the case of minor damage. Notably, the probability of complete destruction was zero percent in all models.

• Coupled systems mechanics
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• v.4 no.1
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• pp.19-36
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• 2015

Modelling and analysis of a brick masonry building involves uncertainties like modelling assumptions and properties of local material. Therefore, it is necessary to perform a calibration to evaluate the dynamic properties of the structure. The response of the finite element model is improved by predicting the parameter by performing linear dynamic analysis on experimental data by comparing the acceleration. Further, a nonlinear dynamic analysis was also performed comparing the roof acceleration and damage pattern of the structure obtained analytically with the test findings. The roof accelerations obtained analytically were in good agreement with experimental roof accelerations. The damage patterns observed analytically after every shock were almost similar to that of experimental observations. Damage pattern with amplification in roof acceleration exhibit the potentiality of earthquake resistant measures in brick masonry models.

• Smart Structures and Systems
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• v.20 no.6
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• pp.669-682
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• 2017

The normalised version of bispectrum, the so-called bicoherence, has often proved a reliable method of damage detection on engineering applications. Indeed, higher-order spectral analysis (HOSA) has the advantage of being able to detect non-linearity in the structural dynamic response while being insensitive to ambient vibrations. Skewness in the response may be easily spotted and related to damage conditions, as the majority of common faults and cracks shows bilinear effects. The present study tries to extend the application of HOSA to damage localisation, resorting to a neural network based classification algorithm. In order to validate the approach, a non-linear finite element model of a 4-meters-long cantilever beam has been built. This model could be seen as a first generic concept of more complex structural systems, such as aircraft wings, wind turbine blades, etc. The main aim of the study is to train a Neural Network (NN) able to classify different damage locations, when fed with bispectra. These are computed using the dynamic response of the FE nonlinear model to random noise excitation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.550-557
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• 2004

In this paper, structural damage in PSC bridges is monitored by using model-based damage detection methods. First numerical experiments on the test structure are described. Dynamic responses of the test structures are obtained fur several damage scenarios. The change in natural frequency and the change in nude shape curvature are selected as features to represent the states of the structure. Next a damage localization algorithm from monitoring the changes in natural frequency is outlined. Also, the damage localization algorithm from monitoring the changes in nude shapes is outlined. Finally, the damage localization algorithms are used to predict damage in the test structure. The results of the analysis indicate that the model-based damage detection methods correctly predicted damage in the test structure.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• Steel and Composite Structures
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• v.24 no.4
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• pp.409-423
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• 2017

This paper presents an experimental study on damage evolution laws of solid-web steel reinforced concrete (SRC) T-shaped columns along the direction of the web under various loadings. Ten specimens with a scale ratio of 1/2 and a shear span ratio of 2.5 were designed and fabricated. The influences of various parameters, including the axial compression ratio, steel ratio, and loading mode, were examined. The mechanical performances including load-displacement curve and energy dissipation capacity under the monotonic and low cyclic loadings were analyzed. Compared with the monotonic loading, bearing capacity, ultimate deformation capacity, and energy dissipation capacity of the specimens decrease to some extent with the increase of the displacement amplitude and the number of loading cycle. The results show that the damage process of the SRC T-shaped column can be divided into five stages, namely non-damage, slight-damage, steadily-developing-damage, severe-damage and complete-damage. Finally, based on the Park-Ang model, a modified nonlinear damage model which combines the maximum deformation with hysteretic energy dissipation is proposed by taking into account the dynamic influence of the aforementioned parameters. The results show that the modified model in this paper is more accurate than Park-Ang model and can better describe the damage evolution of SRC T-shaped columns.

• Smart Structures and Systems
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• v.22 no.5
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• Structural Engineering and Mechanics
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• v.46 no.1
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• pp.75-90
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• 2013

In order to identify damage of highway bridges rapidly, a method for damage identification using dynamic response of bridge induced by moving vehicle and static test data is proposed. To locate damage of the structure, displacement energy damage index defined from the energy of the displacement response time history is adopted as the indicator. The displacement response time histories of bridge structure are obtained from simulation of vehicle-bridge coupled vibration analysis. The vehicle model is considered as a four-degree-of-freedom system, and the vibration equations of the vehicle model are deduced based on the D'Alembert principle. Finite element method is used to discretize bridge and finite element model is set up. According to the condition of displacement and force compatibility between vehicle and bridge, the vibration equations of the vehicle and bridge models are coupled. A Newmark-${\beta}$ algorithm based professional procedure VBAP is developed in MATLAB, and used to analyze the vehicle-bridge system coupled vibration. After damage is located by employing the displacement energy damage index, the damage extent is estimated through the least-square-method based model updating using static test data. At last, taking one simply supported bridge as an illustrative example, some damage scenarios are identified using the proposed damage identification methodology. The results indicate that the proposed method is efficient for damage localization and damage extent estimation.