Utilization of splitting strips in fracture mechanics tests of quasi-brittle materials

İnce, Ragıp

doi:10.1007/s00419-021-01913-5

Cited by 7 publications

(1 citation statement)

References 27 publications

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“…Splitting strips were employed for determining the fracture behavior of quasi-brittle materials in square specimens with edge cracks. The experimentation adopted a two-parameter model for research inferences [31]. Notched specimens of fiber-reinforced concrete in flexure were subjected to cyclic loads, and the results suggested enhanced fracture and fatigue lives of specimens at higher load conditions [32].…”

Section: Introductionmentioning

confidence: 99%

Multigene Genetic Programming Based Prediction of Concrete Fracture Parameters of Unnotched Specimens

Sudhir

Beulah

2023

Civ Eng J

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This study explores the fracture energy of notched and unnotched concrete specimens subjected to the classical three-point bend test, instantiating a gradational step in the continued development of concrete fracture mechanics. An experimental campaign involving 18 notched test specimens and nine unnotched specimens of three different grades of concrete, an examination of the existing literature models for unnotched specimens, and a novel Multigene Genetic programming (MGGP) based concrete fracture energy model for unnotched specimens are integral to this study. As a salient result, the multiple approaches to quasi-brittle materials adopted in the study, highlighted the criticality of the determination of fracture energy, tensile strength and characteristic length for the crack width study. The failure modes of notched and unnotched specimens were found to be similar. The reported literature has mainly focused on a limited number of fracture energy influencing parameters. Therefore, six impact parameters have been chosen and incorporated into the present study to provide a more acceptable explanation of concrete fracture behaviour. A sensitivity analysis of the parameters and an error analysis of the model undertaken have established the accuracy and robustness of the developed MGGP model. Doi: 10.28991/CEJ-2023-09-02-011 Full Text: PDF

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Section: Introductionmentioning

confidence: 99%