A two-stage damage detection method for truss structures using a modal residual vector based indicator and differential evolution algorithm

Seyedpoor, S. M.; Montazer, Maryam

doi:10.12989/sss.2016.17.2.347

Cited by 19 publications

(9 citation statements)

References 26 publications

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“…Moreover, during the last years, the effectiveness of using the heuristic methods has been proven from two aspects. They enhance the probability of achieving the globally optimal solution and independence to evaluating the derivatives of functions [24][25][26]. Since the optimization-based damage identification problems may have numerous local solutions, selecting an efficient algorithm for solving the problem is essential.…”

Section: The Objective Functionmentioning

confidence: 99%

Damage identification in connections of moment frames using time domain responses and an optimization method

Pahnabi

Seyedpoor

2021

Front. Struct. Civ. Eng.

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Damage is defined as changes to the material and/or geometric properties of a structural system, comprising changes to the boundary conditions and system connectivity, adversely affecting the system's performance. Inspecting the elements of structures, particularly critical components, is vital to evaluate the structural lifespan and safety. In this study, an optimization-based method for joint damage identification of moment frames using the timedomain responses is introduced. The beam-to-column connection in a metallic moment frame structure is modeled by a zero-length rotational spring at both ends of the beam element. For each connection, an end-fixity factor is specified, which changes between 0 and 1. Then, the problem of joint damage identification is converted to a standard optimization problem. An objective function is defined using the nodal point accelerations extracted from the damaged structure and an analytical model of the structure in which the nodal accelerations are obtained using the Newmark procedure. The optimization problem is solved by an improved differential evolution algorithm (IDEA) for identifying the location and severity of the damage. To assess the capability of the proposed method, two numerical examples via different damage scenarios are considered. Then, a comparison between the proposed method and the existing damage identification method is provided. The outcomes reveal the high efficiency of the proposed method for finding the severity and location of joint damage considering noise effects.

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Section: The Objective Functionmentioning

confidence: 99%

Damage identification in connections of moment frames using time domain responses and an optimization method

Pahnabi

Seyedpoor

2021

Front. Struct. Civ. Eng.

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“…e use of the DEA in estimation of rock fracture sizes is described by Decker and Mauldon [16]. DEA also has been used for the detection of structural damage in structural engineering field (Seyedpoor et al [17], Seyedpoor and Montazer [18], and Zhang et al [1]). Despite being used in various fields with respect to the optimization problem, DEA is not used widely in the geotechnical engineering field.…”

Section: Revisit To Differential Evolution Algorithmmentioning

confidence: 99%

Tunnel Back Analysis Based on Differential Evolution Using Stress and Displacement

Kang

Choi

et al. 2020

Advances in Civil Engineering

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The stability of tunnels has mainly been evaluated based on displacement. Because displacement due to the excavation process is significant, back analysis of the structure and ground can be performed easily. Recently, the length of a segment-lined tunnel driven by the mechanized tunneling method is increasing. Because the internal displacement of a segment-lined tunnel is trivial, it is difficult to analyze the stability of segment-lined tunnels using the conventional method. This paper proposes a back analysis method using stress and displacement information for a segment-lined tunnel. A differential evolution algorithm was adopted for tunnel back analysis. Back analysis based on the differential evolution algorithm using stress and displacement was established and performed using the finite difference code, FLAC3D, and built-in FISH language. Detailed flowcharts of back analysis based on DEA using both monitored displacement stresses were also suggested. As a preliminary study, the target variables of the back analysis adopted in this study were the elastic modulus, cohesion, and friction angle of the ground. The back analysis based on the monitored displacement is useful when the displacement is significant due to excavation. However, the conventional displacement-based back analysis is unsuitable for a segment-lined tunnel after construction because of its trivial internal displacement since the average error is greater than 32% and the evolutionary calculation is finalized due to the maximum iteration criteria. The average error obtained from the proposed back analysis algorithm using both stress and displacement ranged within approximately 6–8%. This also confirms that the proposed back analysis algorithm is suitable for a segment-lined tunnel.

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“…More recently, Seyedpoor and Montazer analytically demonstrated success applying a twostage damage detection approach based on the residual force vector [37]. In Seyedpoor and Montazer's approach, a first pass is made where potential damage elements are identified before applying a differential evolution algorithm to determine the final location and severity of any damage present.…”

Section: Overview Of Structural Health Monitoringmentioning

confidence: 99%

Ambient Excitation Based Model Updating for Structural Health Monitoring via Dynamic Strain Measurements

Martins

Kosmatka

2018

2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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A two-stage damage detection method for truss structures using a modal residual vector based indicator and differential evolution algorithm

Cited by 19 publications

References 26 publications

Damage identification in connections of moment frames using time domain responses and an optimization method

Damage identification in connections of moment frames using time domain responses and an optimization method

Tunnel Back Analysis Based on Differential Evolution Using Stress and Displacement

Ambient Excitation Based Model Updating for Structural Health Monitoring via Dynamic Strain Measurements

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