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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.27 No.1
- 발행연도
- 2021.1
- 수록면
- 21 - 28 (8page)
이용수
초록· 키워드
오류제보하기
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.
목차
등록된 정보가 없습니다.
참고문헌 (45)
참고문헌 신청
Esmael Aflaki / 2017 / Laboratory tests for studying the performance of grouted micro-fine cement / Computers and Concrete, An International Journal 20(2):145~154
Hisham Alabduljabbar / 2020 / Prediction of the flexural behavior of corroded concrete beams using combined method / Structures 25:1000~1008
Al-Mishhadani, S. A. / 2012 / Effect of age on nondestructive tests results for existing concrete / Iraqi J. Mech. Mater. Eng 12(4):630~646
Ali-Benyahia, K. / 2010 / Correlation between nondestructive and destructive tests of low strength concrete / 37th IAHS World Congress on Housing Science
Kamran Amini / 2016 / Advancing concrete strength prediction using non-destructive testing: Development and verification of a generalizable model / Construction and Building Materials 102:762~768
Hisham Alabduljabbar / 2020 / Prediction of the flexural behavior of corroded concrete beams using combined method / Structures 25:1000~1008
Al-Mishhadani, S. A. / 2012 / Effect of age on nondestructive tests results for existing concrete / Iraqi J. Mech. Mater. Eng 12(4):630~646
Ali-Benyahia, K. / 2010 / Correlation between nondestructive and destructive tests of low strength concrete / 37th IAHS World Congress on Housing Science
Kamran Amini / 2016 / Advancing concrete strength prediction using non-destructive testing: Development and verification of a generalizable model / Construction and Building Materials 102:762~768
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