Adapting ANNs in SONREB Test to Estimate Concrete Compressive Strength

Yu Ren Wang; Loan T.Q. Ngo; Yi Fan Shih; Yen Ling Lu; Yi Ming Chen

doi:10.4028/www.scientific.net/KEM.792.166

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HomeKey Engineering MaterialsKey Engineering Materials Vol. 792Adapting ANNs in SONREB Test to Estimate Concrete...

Adapting ANNs in SONREB Test to Estimate Concrete Compressive Strength

Abstract:

SONREB method is a non-destructive testing (NDT) method for estimating the concrete compressive strength. It is conducted by combining two popular NDT methods: ultrasonic pulse velocity (UPV) test and rebound hammer (RH) test. Several researches have been attempted to find the correlation of the different testing method data with actual compressive strength. This research proposes a new Artificial Intelligence based approach, Artificial Neural Networks (ANNs), to estimate the concrete compressive strength using the UPV and RH test data. Data from a total of 315 cylinder concrete samples are collected to develop and validate the ANFIS prediction model. The model prediction results are compared with actual compressive strength using mean absolute percentage error (MAPE). With the adaption of ANFIS, the estimation error of SONREB test can be reduced to 5.98% (measured by MAPE).

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Periodical:

Key Engineering Materials (Volume 792)

Pages:

166-169

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.792.166

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Online since:

December 2018

Authors:

Yu Ren Wang*, Loan T.Q. Ngo, Yi Fan Shih, Yen Ling Lu, Yi Ming Chen

Keywords:

ANNs, Concrete Compressive Strength, Non-Destructive Testing, Rebound Hammer Test, SONREB, Ultrasonic Pulse Velocity Test

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