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Ahmed M. Tahwia,Ashraf Heniegal,Mohamed S. Elgamal,Bassam A. Tayeh 사단법인 한국계산역학회 2021 Computers and Concrete, An International Journal Vol.27 No.1
The Artificial Neural Network (ANN) is a system, which is utilized for solving complicated problems by using nonlinear equations. This study aims to investigate compressive strength, rebound hammer number (RN), and ultrasonic pulse velocity (UPV) of sustainable concrete containing various amounts of fly ash, silica fume, and blast furnace slag (BFS). In this study, the artificial neural network technique connects a nonlinear phenomenon and the intrinsic properties of sustainable concrete, which establishes relationships between them in a model. To this end, a total of 645 data sets were collected for the concrete mixtures from previously published papers at different curing times and test ages at 3, 7, 28, 90, 180 days to propose a model of nine inputs and three outputs. The ANN model’s statistical parameter R2 is 0.99 of the training, validation, and test steps, which showed that the proposed model provided good prediction of compressive strength, RN, and UPV of sustainable concrete with the addition of cement.
Ahmed M. Tahwia,Gamal M. Elgendy,Mohamed Amin 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.82 No.2
This study investigates the resistance of sustainable ultra-high performance concrete (UHPC) on steel reinforcement corrosion. For enhancing the sustainability of UHPC, concrete mixes were prepared with ordinary Portland cement main binder, and mixes with moderate to high percentages of blast furnace cement (CEM III), fly ash (FA), and slag cement as partial replacements of the full quantity of the used cement. Linear polarization resistance technique was employed to estimate the electrochemical behavior of the concrete specimens. Results showed that the compressive strength and the resistance of steel to corrosion in marine environments can be enhanced by improving the sustainability of UHPC through incorporation of CEM III, FA, and slag cement. FA replacement of up to 50% with the addition of 15% SF content produced better compressive strength and steel corrosion resistance than slag cement whether with the use of ordinary Portland cement or blast furnace cement as the main binder.