Fusion of Rebound Number and Ultrasonic Pulse Velocity Data for Evaluating the Concrete Strength Using Bayesian Updating

Lad, Devang B.; Faroz, Sharvil Alex; Ghosh, Siddhartha

doi:10.1007/978-981-13-9008-1_35

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Combination of multiple tests has been suggested to improve the reliability for the interpretation of results (ACI, 2003). The concept of combining information from multiple sources or tests in a Bayesian setting is called Bayesian data fusion (Faroz, 2017;Lad et al, 2020).…”

Section: Data Fusionmentioning

confidence: 99%

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Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

2022

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Identification of in situ concrete characteristic strength (CCS) of deteriorating RC structures directly affects their rehabilitation. Contemporary practices lack the ability to yield CCS or at most produce an unrealistic estimate, because: (i) core tests are few due to technical and economic constraints and their positioning is random, inducing bias in the strength estimate, (ii) non-destructive tests (NDT) are themselves not good estimators of project specific strength, (iii) tests are only local indicators and most practising engineers are unaware of how to process the spatial variability. This paper overcomes these limitations with a novel and implementable framework, for an asset manager to make scientific estimates of CCS. This is a tri-level framework: (1) NDT are performed to capture the spatial variability of the investigated concrete; (2) core extractions are guided by the prior NDT information, to avoid bias in test location selection; (3) NDT and coring results are fused via Bayesian NDT test calibration and updating of the probability distribution of Realistic Estimation of Concrete Strength the concrete strength. The proposed framework is implemented for the assessment and rehabilitation of a critical hospital complex in India.

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Section: Data Fusionmentioning

confidence: 99%

“…4 cannot be directly used to form the likelihood function as in the case of core values. The likelihood function of f c , for a single measurement of V i is thus formulated as (Faroz, 2017;Lad et al, 2020)…”

Section: Likelihood Formulationmentioning

confidence: 99%

Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

2022

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“…In recent years, the ultrasonic pulse-based structural health monitoring (SHM) method has been widely used to detect the depth of underwater concrete cracks owing to the strong penetration ability and simplicity of operation [ 7 , 8 ]. However, the traditional crack detection method usually uses only a specific component of the crack-related information (energy attenuation, travel time of diffracted wave, or the scattered wave field).…”

Section: Introductionmentioning

confidence: 99%

Time Reverse Modeling of Damage Detection in Underwater Concrete Beams Using Piezoelectric Intelligent Modules

Liang

Chen

Shao

et al. 2020

Sensors

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Underwater cracks in concrete structures are often difficult to detect due to their complexity of the service environment. With numerical and experimental analysis of concrete beams immersed in water, an active monitoring system, based on a cement-based piezoelectric intelligent module array (CPIMA), was developed to locate and quantify the underwater cracks. Time reversal (TR) of the stress wave field is accomplished to focus on the crack area through the concrete beam specimen by the system. First, a piezoelectric actuator is applied to emit the initial propagating wave, which can be reflected, attenuated, and diffracted by the crack, transmitted through water filled in the crack, as well as diffracted by the coarse aggregates. To extract the damage waveforms associated with the crack and analyze the robust time-reversal invariance under the high-order multiple scattering effect, a pair of homogeneous and heterogeneous forward finite element (FE) models is established. Then, the damage waveforms are time-reversed and re-propagated in the inverse numerical model, where an optimal refocusing is achieved on the crack that behaves as an acoustic source. Finally, the damage area is obtained in the form of the stacked energy distribution of each time step. The focus results are represented by cloud images and compared with root-mean-square deviation (RMSD) values. Numerical simulation and experiments show that this method can identify and quantify underwater cracks effectively.

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Combining different field tests with minimum laboratory ones to enhance the deterioration assessment of standing concrete structures

Khaled

Ali

Risan

et al. 2021

Materials Today: Proceedings

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Fusion of Rebound Number and Ultrasonic Pulse Velocity Data for Evaluating the Concrete Strength Using Bayesian Updating

Cited by 4 publications

References 8 publications

Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

Tri-level Framework for Realistic Estimation of Concrete Strength Using Bayesian Data Fusion of UPV and Guided Coring

Time Reverse Modeling of Damage Detection in Underwater Concrete Beams Using Piezoelectric Intelligent Modules

Combining different field tests with minimum laboratory ones to enhance the deterioration assessment of standing concrete structures

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