Evaluating pod-based unsupervised damage identification using controlled damage propagation of out-of-service bridges

Ardani, Samira; Akintunde, Emmanuel; Linzell, Daniel G.; Azam, Saeed Eftekhar; Alomari, Qusai

doi:10.1016/j.engstruct.2023.116096

Cited by 5 publications

(1 citation statement)

References 32 publications

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“…Model order eduction methods such as proper orthogonal decomposition (POD), have pinpointed dependable and efficient strategies for damage identification [34]. The POD technique is exploited for processing substantial volumes of high-dimensional data, facilitating computational analysis to anticipate the future dynamics of the system [35].…”

Section: Introductionmentioning

confidence: 99%

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

Zenzen,

Ayadi,

Benaissa

et al. 2024

Comptes Rendus. Mécanique

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In recent years, substantial investments in structural construction underscore the paramount importance of ensuring structural integrity for safety and dependability. Structural Health Monitoring (SHM) has emerged as a pivotal tool for assessing structural health, with an emphasis on damage detection, localisation, and quantification, particularly through vibration-based methods that exploit variations in modal properties as precursors to structural damage. This study presents an innovative methodology that synergistically combines Proper Orthogonal Decomposition and Radial Basis Function interpolation for predicting structural responses based on crack parameters. Additionally, the YUKI algorithm, leveraging population clustering for optimisation, is introduced. The approach is rigorously assessed through experimental analysis of two distinct beams (Beam I and Beam II) exhibiting varying crack depths. The results demonstrate the effectiveness of the POD-RBF-YUKI approach, indicating a notable level of accuracy and consistency. Comparative

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Section: Introductionmentioning

confidence: 99%

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

Zenzen,

Ayadi,

Benaissa

et al. 2024

Comptes Rendus. Mécanique

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Solving large numerical substructures in real‐time hybrid simulations using proper orthogonal decomposition

Zhang,

Ding,

Wang

et al. 2024

Earthq Engng Struct Dyn

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Real‐time hybrid simulation (RTHS) technique significantly streamlines experimental procedures by allowing researchers to study a substantial portion of the structure through numerical analysis. For effective real‐time interconnectivity between the investigated substructures, the numerical component must be solved within an extremely tight time frame. However, achieving a real‐time solution for large numerical substructures presents a major challenge. Hence, this paper proposes the Proper Orthogonal Decomposition (POD) method to reduce computational burden in RTHS and shows its implementation. The merits of the approach are shown by comparisons between the full‐order and reduced‐order numerical substructures, including nonlinearities. A shear frame retrofitted with superelastic shape memory alloy dampers is investigated as a numerical model. The soil‐structure interaction is also included using a finite element half‐space model with an artificial viscous‐spring boundary. Furthermore, the numerical substructure is coupled with shaking table experiments of a tuned liquid column damper to prove the feasibility of the method. With POD, the studied nonlinear numerical substructure can simulate up to 2655 degrees‐of‐freedom (DOFs) with a given hardware setup, while the full‐order model is limited to 135 DOF, underscoring the significance of the POD method in RTHS.

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Bridge damage localization and quantification using deep learning and FEM static simulation

Sun,

Song,

2024

Mechanical Systems and Signal Processing

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Evaluating pod-based unsupervised damage identification using controlled damage propagation of out-of-service bridges

Cited by 5 publications

References 32 publications

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF

Solving large numerical substructures in real‐time hybrid simulations using proper orthogonal decomposition

Bridge damage localization and quantification using deep learning and FEM static simulation

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