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논문 기본 정보

자료유형
학술저널
저자정보
Ali Toghroli (University of Malaya) Ehsan Darvishmoghaddam (University of Malaya) Yousef Zandi (Islamic Azad University) Mahdi Parvan (Islamic Azad University) Maryam Safa (University of Malaya) Mu’azu Mohammed Abdullahi (Jubail University College) Abbas Heydari (Young Researchers and Elite Club) Karzan Wakil (University of Human Development) Saad A.M. Gebreel (Omar Al-Mukhtar University) Majid Khorami (Universidad Tecnológica Equinoccial)
저널정보
한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.21 No.5
발행연도
2018.1
수록면
525 - 530 (6page)

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As a nondestructive testing method, the Schmidt rebound hammer is widely used for structural health monitoring. During application, a Schmidt hammer hits the surface of a concrete mass. According to the principle of rebound, concrete strength depends on the hardness of the concrete energy surface. Study aims to identify the main variables affecting the results of Schmidt rebound hammer reading and consequently the results of structural health monitoring of concrete structures using adaptive neuro-fuzzy inference system (ANFIS). The ANFIS process for variable selection was applied for this purpose. This procedure comprises some methods that determine a subsection of the entire set of detailed factors, which present analytical capability. ANFIS was applied to complete a flexible search. Afterward, this method was applied to conclude how the five main factors (namely, age, silica fume, fine aggregate, coarse aggregate, and water) used in designing concrete mixture influence the Schmidt rebound hammer reading and consequently the structural health monitoring accuracy. Results show that water is considered the most significant parameter of the Schmidt rebound hammer reading. The details of this study are discussed thoroughly.

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