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Author

Akbar Esfandiari

Other affiliations: Tufts University
Bio: Akbar Esfandiari is an academic researcher from Amirkabir University of Technology. The author has contributed to research in topics: Sensitivity (control systems) & Finite element method. The author has an hindex of 14, co-authored 40 publications receiving 701 citations. Previous affiliations of Akbar Esfandiari include Tufts University.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a structural damage detection algorithm using static test data is presented, which is characterized as a set of non-linear simultaneous equations that relate the changes in the static response to the location and severity of damage.

139 citations

Journal ArticleDOI
TL;DR: In this paper, a least square algorithm with appropriate normalization is used for solving the over-determined system of equations with noise-polluted data, and proper selection of measured frequency points improved the accuracy and convergence in finite element model updating.

114 citations

Journal ArticleDOI
TL;DR: In this paper, a new method is presented for the finite element model updating of structures at the element level utilizing Frequency Response Function data, which can be an alternative to conventional model updating methods even in the presence of mass modeling errors.

80 citations

Journal ArticleDOI
TL;DR: In this paper, a global algorithm for damage detection and assessment of structures based on parameter estimation method using finite element analysis and measured modal response of the structure is presented, where damage is considered as a change in the structural stiffness parameters.
Abstract: A global algorithm for damage detection and assessment of structures based on parameter estimation method using finite element analysis and measured modal response of the structure is presented. Damage is considered as a change in the structural stiffness parameters. Modal displacements (eigenvector) of a structure are characterized as a function of structural parameter that yields an indeterminate set of equations. Elemental damage equations which relate partially measured mode shape of the damaged structure to the change of structural parameter are developed using incomplete measured mode shapes. Based an optimization method these equations are solved to find changes of the structural parameters. Subsequently, Monte Carlo simulation is applied to study the sensitivity of this method to noise in measured modal displacements. The algorithm is tested in numerical simulation environment using a truss and a frame model. Results show the high capability of this method to detect damages of the structures when noise is present. Copyright © 2006 John Wiley & Sons, Ltd.

73 citations

Journal ArticleDOI
TL;DR: In this article, a sensitivity equation that diminishes adverse effects of incompleteness of FRF data is proposed for model updating, and the stiffness and mass parameters of the intact model are updated using the damped FRFs of the simulated damaged model.
Abstract: Summary Structural model updating by estimation of stiffness and mass parameters via monitoring of dynamic characteristics has attracted much attention in recent decades. In this study, frequency response functions (FRF) are utilized in order to identify unknown structural parameters using a sensitivity-based model updating approach. A sensitivity equation that diminishes adverse effects of incompleteness of FRF data is proposed for model updating. Efficiency of the proposed method and impacts of measurement errors and incompleteness of measured data are examined numerically through a truss reference example. The stiffness and mass parameters of the intact model are updated using the damped FRFs of the simulated damaged model. The results demonstrate that the proposed method is capable of precisely identifying the location and the severity of damage in all studied cases. Copyright © 2015 John Wiley & Sons, Ltd.

66 citations


Cited by
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Journal ArticleDOI
TL;DR: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented in this paper, and the damage identification algorithms in terms of signal processing are discussed.
Abstract: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...

1,613 citations

Journal ArticleDOI
TL;DR: In this article, a general summary and review of state-of-the-art and development of vibration-based structural damage detection methods is presented, and the principle of intelligent damage diagnosis and its application prospects in structural damage detecting are introduced.

527 citations

Journal ArticleDOI
TL;DR: This paper aims to fulfill the gap by presenting the highlights of the traditional methods and provide a comprehensive review of the most recent applications of ML and DL algorithms utilized for vibration-based structural damage detection in civil structures.

440 citations

01 Jan 2001
TL;DR: The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the value of the thing expected upon it’s 2 happening.
Abstract: Problem Given the number of times in which an unknown event has happened and failed: Required the chance that the probability of its happening in a single trial lies somewhere between any two degrees of probability that can be named. SECTION 1 Definition 1. Several events are inconsistent, when if one of them happens, none of the rest can. 2. Two events are contrary when one, or other of them must; and both together cannot happen. 3. An event is said to fail, when it cannot happen; or, which comes to the same thing, when its contrary has happened. 4. An event is said to be determined when it has either happened or failed. 5. The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the value of the thing expected upon it’s 2 happening.

368 citations

Journal ArticleDOI
TL;DR: In this paper, a non-probabilistic fuzzy approach and a probabilistic Bayesian approach for model updating for non-destructive damage assessment is presented. But the model updating problem is an inverse problem prone to ill-posedness and ill-conditioning.

338 citations