• 제목/요약/키워드: Damage parameters

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Static and dynamic behaviour of square plates with inhomogeneity subjected to non-uniform edge loading (compression and tension)

  • Prabhakara, D.L.;Datta, P.K.
    • Structural Engineering and Mechanics
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    • 제4권2호
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    • pp.163-176
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    • 1996
  • The tension and compression buckling behaviour of a square plate with localized zones of damage and subjected to non-uniform loading is studied using a finite element analysis. The influence of parameters such as position of damage, extent of damage, size of damage and position of load on instability behaviour are discussed. The dynamic behaviour for certain load and damage parameters are also presented. It is observed that the presence of damage has a marked effect on the static buckling load and natural frequency of the plate.

An efficient hybrid TLBO-PSO-ANN for fast damage identification in steel beam structures using IGA

  • Khatir, S.;Khatir, T.;Boutchicha, D.;Le Thanh, C.;Tran-Ngoc, H.;Bui, T.Q.;Capozucca, R.;Abdel-Wahab, M.
    • Smart Structures and Systems
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    • 제25권5호
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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.

Fragility based damage assesment in existing precast industrial buildings: A case study for Turkey

  • Senel, Sevket Murat;Kayhan, Ali Haydar
    • Structural Engineering and Mechanics
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    • 제34권1호
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    • pp.39-60
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    • 2010
  • In Turkey, majority of industrial facilities are composed of precast buildings. However, precast buildings have suffered extensive damage during Kocaeli and Duzce (1999) and Adana-Ceyhan (1998) earthquakes. Therefore, in this study, fragilities of existing building stock and damage probabilities of precast buildings were studied. For this purpose, building inventories were prepared and variation of structural parameters was determined by investigating the design project of 65 precast buildings constructed in Denizli, Turkey. Twelve analysis models which reflect the stiffness, strength and ductility properties of building inventory were constructed. After the definition of strain based displacement limits and corresponding damage states for buildings, displacement demands were calculated by using non linear time history analysis. During the analyses 360 strong ground motion records were used. Exceedence ratios of concerned damage limits was calculated by checking the displacement demands and then PGV based fragility curves were constructed. Efficiency of strength, stiffness and ductility properties of existing precast buildings were investigated by comparing the fragility curves. The results have shown that the most effective parameters that govern the damage probabilities of precast buildings are stiffness and ductility. It was also stated that the results of fragility analysis and damage and failure observations performed after Kocaeli and Duzce Earthquakes are compatible.

Bayesian structural damage detection of steel towers using measured modal parameters

  • Lam, Heung-Fai;Yang, Jiahua
    • Earthquakes and Structures
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    • 제8권4호
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    • pp.935-956
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    • 2015
  • Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.

Development of Empirical Formulas for Approximate Spectral Moment Based on Rain-Flow Counting Stress-Range Distribution

  • Jun, Seockhee;Park, Jun-Bum
    • 한국해양공학회지
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    • 제35권4호
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    • pp.257-265
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    • 2021
  • Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.

Numerical and experimental investigation for damage detection in FRP composite plates using support vector machine algorithm

  • Shyamala, Prashanth;Mondal, Subhajit;Chakraborty, Sushanta
    • Structural Monitoring and Maintenance
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    • 제5권2호
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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.

A model experiment of damage detection for offshore jacket platforms based on partial measurement

  • Shi, Xiang;Li, Hua-Jun;Yang, Yong-Chun;Gong, Chen
    • Structural Engineering and Mechanics
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    • 제29권3호
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    • pp.311-325
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    • 2008
  • Noting that damage occurrence of offshore jacket platforms is concentrated in two structural regions that are in the vicinity of still water surface and close to the seabed, a damage detection method by using only partial measurement of vibration in a suspect region was presented in this paper, which can not only locate damaged members but also evaluate damage severities. Then employing an experiment platform model under white-noise ground excitation by shaking table and using modal parameters of the first three modes identified by a scalar-type ARMA method on undamaged and damaged structures, the feasibility of the damage detection method was discussed. Modal parameters from eigenvalue analysis on the structural FEM model were also used to help the discussions. It is demonstrated that the damage detection algorithm is feasible on damage location and severity evaluation for broken slanted braces and it is robust against the errors of baseline FEM model to real structure when the principal errors is formed by difference of modal frequencies. It is also found that Z-value changes of modal shapes also play a role in the precise detection of damage.

An inverse approach based on uniform load surface for damage detection in structures

  • Mirzabeigy, Alborz;Madoliat, Reza
    • Smart Structures and Systems
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    • 제24권2호
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    • pp.233-242
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    • 2019
  • In this paper, an inverse approach based on uniform load surface (ULS) is presented for structural damage localization and quantification. The ULS is excellent approximation for deformed configuration of a structure under distributed unit force applied on all degrees of freedom. The ULS make use of natural frequencies and mode shapes of structure and in mathematical point of view is a weighted average of mode shapes. An objective function presented to damage detection is discrepancy between the ULS of monitored structure and numerical model of structure. Solving this objective function to find minimum value yields damage's parameters detection. The teaching-learning based optimization algorithm has been employed to solve inverse problem. The efficiency of present damage detection method is demonstrated through three numerical examples. By comparison between proposed objective function and another objective function which make use of natural frequencies and mode shapes, it is revealed present objective function have faster convergence and is more sensitive to damage. The method has good robustness against measurement noise and could detect damage by using the first few mode shapes. The results indicate that the proposed method is reliable technique to damage detection in structures.

Damage assessment of shear buildings by synchronous estimation of stiffness and damping using measured acceleration

  • Shin, Soobong;Oh, Seong Ho
    • Smart Structures and Systems
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    • 제3권3호
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    • pp.245-261
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    • 2007
  • Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

Assessment of modal parameters considering measurement and modeling errors

  • Huang, Qindan;Gardoni, Paolo;Hurlebaus, Stefan
    • Smart Structures and Systems
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    • 제15권3호
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    • pp.717-733
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    • 2015
  • Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.