Multi-scale reliability analysis of FRP truss bridges with hybrid random and interval uncertainties

Zhou, Xiaochao; Wang, Neng-Wei; Xiong, Wen; Wu, Wenqing; Cai, Chaocan

doi:10.1016/j.compstruct.2022.115928

Cited by 11 publications

(13 citation statements)

References 41 publications

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“…Rather, they investigated the effects of uncertainty sources on the different behaviors (especially dynamic behaviors) of these structures. A summary of these studies [15][16][17][18][19][20][21][22][23][24][25][26][27] is presented in Fig. 2.…”

Section: Figmentioning

confidence: 99%

A novel hybrid multi-stage probabilistic algorithm for the damage detection of carbon nanotube panels by considering the uncertainty of materials and mechanical properties

Khayat,

Amoushahi

2024

Preprint

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Composite materials have a high level of uncertainty (intrinsic and non-intrinsic) due to the manufacturing process as well as the placement of different phases of their constituent materials. These uncertainties can be identified in both macro and micro scales. Identifying the behavior of structures made of composite materials without taking into account the uncertainties, whether due to identification or modeling, can lead to unrealistic results, especially in the dynamic behavior of structures. One of these cases is the identification of damage types in composite structures which is usually done by using dynamic responses. Damages in composite materials or structures usually occur during construction or operation. The correct modeling of uncertainty sources is one of the most important factors in identifying the geometry, location, and severity of damages accurately. The uncertainties related to the position and placement of carbon nanotubes (CNTs) can cause noticeable changes in the characteristics of composite materials reinforced with CNTs. For this reason, in the present study, we identified damages in CNT panels by considering all possible sources of uncertainty. A probabilistic multi-stage reliability-based method was proposed in this study to detect damage in these structures. In order to model the intrinsic and non-intrinsic sources of uncertainty, a modified point estimation method (MPEM) was used. In addition, an enhanced differential quadrature (DQ) method was used to model the CNT panels. In each step of the proposed algorithm, the probability of damage in each element of the panels was calculated by analyzing the possible damages. According to the results of the previous step, the elements with a low failure probability were gradually sifted in the next steps. The sieved elements in each step were considered as intact elements in the next step. This systematic filtering of design variables can simultaneously reduce the dimensions and speed up the optimization problem. Finally, the probability of damage was calculated based on the probability density function of various damage severities and positions. The developed approach was applied for damage detection on a laboratory-tested plate to illustrate the efficiency of the proposed method. The effects of using different damage positions and severity levels on the diagnosis results were discussed. The results demonstrated that the number of frequencies and modes of vibration required to identify the position and severity of damages accurately is different according to the damage scenarios and the percentage of uncertainty.

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Section: Figmentioning

confidence: 99%

A novel hybrid multi-stage probabilistic algorithm for the damage detection of carbon nanotube panels by considering the uncertainty of materials and mechanical properties

Khayat,

Amoushahi

2024

Preprint

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“…It is used to demonstrate applicability of the proposed method by comparing with the conventional method based on the Monte Carlo simulation. Middle span deflection has been considered, and the limit state function is defined as [57,58]:…”

Section: Numerical Examples 41 a Seven-bar Planar Frp Truss Structurementioning

confidence: 99%

“…To circumvent superfluous computations, only those uncertainty parameters with significant impact are considered, leading to the following LSF: This study particularly emphasizes the impacts of multi-scale and multi-source uncertainties on bridge reliability and the construction of metamodels. Relying on literature references [57,64], we delve into the microscopic mechanical properties of the glass fiber and matrix. As illustrated, considering all random and interval variables under imposed load and self-weight at their mean or central values (Table 6), the maximum vertical displacement is determined to be 0.0335 m(Figure 18).…”

Section: Classification and Characteristics Of Uncertainty Parametersmentioning

confidence: 99%

“…where 𝑑 represents the limit value of bridge displacement, which is set at the stipulated deflection of truss bridges, 𝐿/800. The material density 𝜌 is calculated based on a permissible deviation of 7% in unit area mass as stipulated in reference [57] and converted…”

Section: Classification and Characteristics Of Uncertainty Parametersmentioning

confidence: 99%

where neglecting the self-weight of the members, nodes 4, 5, and 2 are subjected to concentrated loads represented by

, and

, respectively. The term

designates the maximum permissible displacement, set at 40 mm.…”

Section: Numerical Examplesmentioning

confidence: 99%

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A Metamodel-Based Multi-Scale Reliability Analysis of FRP Truss Structures under Hybrid Uncertainties

Zhao,

Zhou,

2023

Materials

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This study introduces a Radial Basis Function-Genetic Algorithm-Back Propagation-Importance Sampling (RBF-GA-BP-IS) algorithm for the multi-scale reliability analysis of Fiber-Reinforced Polymer (FRP) composite structures. The proposed method integrates the computationally powerful RBF neural network with GA, BP neural network and IS to efficiently calculate inner and outer optimization problems for reliability analysis with hybrid random and interval uncertainties. The investigation profoundly delves into incorporating both random and interval parameters in the reliability appraisal of FRP constructs, ensuring fluctuating parameters within designated boundaries are meticulously accounted for, thus augmenting analytic exactness. In application, the algorithm was subjected to diverse structural evaluations, including a seven-bar planar truss, an architectural space dome truss, and an intricate nonlinear truss bridge. Results demonstrate the algorithm’s exceptional performance in terms of model invocation counts and accurate failure probability estimation. Specifically, within the seven-bar planar truss evaluation, the algorithm exhibited a deviation of 0.08% from the established failure probability benchmark.

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Off‐axis compression behavior and failure mechanisms of needled carbon/quartz fiber reinforced phenolic resin composite based on acoustic emission

Kuang,

Li,

Wang

et al. 2024

Polymer Composites

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The effect of the off‐axis angle (note as θ) on compressive properties and failure mechanisms in needled carbon/quartz fiber reinforced phenolic resin (CF‐QF/PF) composite has been investigated. For this objective, a series of quasi‐static off‐axis compression tests were performed, and a more precise and general model for predicting the compressive modulus and strength has been proposed. Further, the acoustic emission (AE) technology, including parameter‐based analysis and the Hilbert Huang Transform (HHT) method, was also employed to scrutinize the intricate damage mechanisms. The results show that specimens with θ = 0° exhibit linear and brittle behavior and are the most dangerous scenarios because delamination (accounting for 58% of the total AE accumulative energy) dominates their failure. For specimens with small off‐axis angles (0° < θ ≤ 45°), the fiber‐matrix interface determines their compressive properties. While for specimens with large off‐axis angles(45° < θ ≤ 90°), the enhanced transverse load‐bearing capacity of fibers becomes the dominant factor, characterized by significant debonding (33% when θ = 60°) and fiber breakage (27% when θ = 90°). Finally, these results were verified by optical microscopy (OM) and scanning electron microscopy images (SEM).Highlights Off‐axis compression behaviors of needled CF‐QF/PF composite are studied. A more precise and general model for predicting off‐axis compression properties is proposed. Acoustic emission technology is used to quantify different types of damage. Failure mechanisms are revealed by combining in‐situ and offline techniques.

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Multi-scale reliability analysis of FRP truss bridges with hybrid random and interval uncertainties

Cited by 11 publications

References 41 publications

A novel hybrid multi-stage probabilistic algorithm for the damage detection of carbon nanotube panels by considering the uncertainty of materials and mechanical properties

A novel hybrid multi-stage probabilistic algorithm for the damage detection of carbon nanotube panels by considering the uncertainty of materials and mechanical properties

A Metamodel-Based Multi-Scale Reliability Analysis of FRP Truss Structures under Hybrid Uncertainties

Off‐axis compression behavior and failure mechanisms of needled carbon/quartz fiber reinforced phenolic resin composite based on acoustic emission

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