Finite element model updating of concrete structures based on imprecise probability

Biswal, Suryakanta; Ramaswamy, Ananth

doi:10.1016/j.ymssp.2017.02.042

Cited by 17 publications

(6 citation statements)

References 21 publications

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“…[26][27][28] Bayesian methods stand out as a frequently employed strategy in model updating, providing a probabilistic perspective to address the challenges of refining models. [29][30][31] The most common method of Bayesian updating is carried out through sampling techniques, such as Markov chain Monte Carlo (MCMC) methods. Uribe et al 32 explored how varying the prior random field model influences the resolution of Bayesian inverse problems.…”

Section: Introductionmentioning

confidence: 99%

Experimental model updating of slope considering spatially varying soil properties and dynamic loading

Wang,

Ouyang,

Fragkoulis

et al. 2024

Earthquake Engineering and Resilience

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The widespread threat posed by slope structure failures to human lives and property safety is widely acknowledged. Additionally, natural soil often displays spatial variability due to geological deposition and other factors. Therefore, predicting the seismic response of slopes subjected to ground motions and inversely analyzing the spatial distribution of soils remains an unresolved issue. In the present work, a shaking table experimental test is first designed and carried out, in which a soft‐soil slope dynamic system is established. To capture the seismic response of the soft‐soil slope, specifically the experimental characteristic of acceleration and soil pressure response in both spatial domain and time domain, a series of sensors were pre‐embedded in the slope. Subsequently, a model updating approach is proposed for slope seismic analysis that incorporates spatial variability of soil. In addition, to enhance computational efficiency, the dimensionality reduction of Karhunen–Loève expansion method is introduced to reduce inverse analysis parameters. On the basis of 34 samples collected from experimental data, it is shown that near‐fault pulse‐like ground motions deliver greater concentrated energy, causing more severe damage to slope structures, especially the topsoil layer. Furthermore, using data obtained from a shaking table test subjected to ground motion Recorded Sequence Number 158H1 from the Pacific Earthquake Engineering Research Center NGA‐West2 database as an example, it is also shown that the proposed approach demonstrates high accuracy in predicting the spatial distribution of the maximum shear modulus in soil slope dynamic systems. The present work not only addresses the challenges posed by mainshock–aftershock effects but also highlights the potential of model updating approaches to enhance the understanding of slope behavior under seismic loading conditions.

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Section: Introductionmentioning

confidence: 99%

Experimental model updating of slope considering spatially varying soil properties and dynamic loading

Wang,

Ouyang,

Fragkoulis

et al. 2024

Earthquake Engineering and Resilience

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“…The number of samples in Markov chain is considerably smaller. Among these algorithms, MH-based MCMC is the most common method used in the application of FE model updating [26,30]. When MHbased MCMC method is applied, a proposal distribution is formulated to guide the sample generation over the entire parametric space.…”

Section: Introductionmentioning

confidence: 99%

Computational inference of vibratory system with incomplete modal information using parallel, interactive and adaptive Markov chains

Zhou

Tang

2021

Journal of Sound and Vibration

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“…In addition to numerical finite element analyses and analytical calculation, nondestructive ambient vibration examinations are widely conducted to get the dynamic features in functioning condition without any external forces. A vast amount of literature can be found regarding the finite element model updating of steel structures, 13–20 reinforced concrete structures, 21–27 base isolated structures, 28 timber structures, 29,30 and masonry structures 31–36 . However, there are very limited studies about the ambient vibration test‐based system identification and FEM updating of concrete steel composite structures 37–39 …”

Section: Introductionmentioning

confidence: 99%

Model updating‐based automated damage detection of concrete‐encased composite column‐beam connections

Nasery

Hüsem

Okur

et al. 2020

Struct Control Health Monit

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Summary This paper presents a comparative study about the numerical and experimental system identification and model updating‐based automated damage detection of concrete‐encased composite column‐beam connections. Four different column‐beam connection types named as CBC#A, CBC#B, CBC#C, and CBC#D were considered without any changes in geometrical configuration. Numerical and experimental dynamic characteristics were extracted by initial finite element analysis and nondestructive experimental measurements for undamaged condition. Enhanced frequency domain decomposition (EFDD) method was used for experimental modal extractions. A good agreement was observed between experimental natural frequencies but not enough correlation between damping ratios for all connection types. Maximum differences between initial finite element and undamaged experimental results were calculated as 34.68% for CBC#A, 40.78% for CBC#B, 33.15% for CBC#C, and 47.13% for CBC#D type connection details. The differences were reduced to 0.24%, 0.24%, 0.16%, and 0.15%, respectively, by automated model updating procedure using spring coefficient, modulus of elasticity and weight per unit volume. In the case of the damaged condition, lateral forces were applied to simulate the effect of an earthquake. Cracks strongly affected the natural frequencies. The mode shapes were not broken evidently after damaged conditions. The mode shapes definitely deviated a bit, but generally the same after damages. The natural frequencies have decreased non‐monotonically due to the decrease in the rigidity of the column and beam at the cracked section. Maximum differences were calculated as 14.96% for CBC#A, 41.08% for CBC#B, 31.35% for CBC#C, and 45.93% for CBC#D type connection details. After automated model updating the above‐mentioned differences were reduced to 0.35%, 0.78%, 0.73%, and 0.85% respectively. Contour diagrams of changes of updating parameters were plotted for damage identification. The regions with high difference rates indicated the location of the damage.

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Finite element model updating of concrete structures based on imprecise probability

Cited by 17 publications

References 21 publications

Experimental model updating of slope considering spatially varying soil properties and dynamic loading

Experimental model updating of slope considering spatially varying soil properties and dynamic loading

Computational inference of vibratory system with incomplete modal information using parallel, interactive and adaptive Markov chains

Model updating‐based automated damage detection of concrete‐encased composite column‐beam connections

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