Microscale Investigation of Strength and Failure Behavior of Rock-Concrete Interfaces Under Tensile Loading
Bibliographic record
Abstract
ABSTRACT: Tensile failure and detachment of rock-concrete interfaces in civil engineering structures such as gravity dams is considered as one of the critical factors in controlling the stability of these structures. Despite the large number of studies, the fracturing process along the rock-concrete interfaces under tensile loading is not yet well understood. In this study, digital image correlation and acoustic emission techniques were employed to investigate the effect of the interface on the strength and the fracture properties of granite-mortar specimens under tensile loading. Our results indicated that the tensile strength of the granite-mortar interfaces was smaller than that of either the granite or the mortar. It was found that the tensile strength of the interface was controlled by both interface (adhesive strength) and the mortar (cohesive strength). The DIC results showed that FPZ is mainly limited to a narrow band along the interface, while the AE analysis revealed that the FPZ covers the interface area and a considerable portion of the mortar. AE better illustrated that the fracture may initiate at the interface and then kink into the mortar. In addition, it was seen that the surface roughness of the generated fractures is material dependent, i.e., fractures generated in granite were roughest, while fractures formed along the interface had the lowest roughness values. The finding of this study can improve our understanding of the tensile strength and behavior of rock-concrete interfaces, leading to the safer design of engineering structures. 1. INTRODUCTION In geomechanics, rock-concrete interfaces are frequently seen in civil and mining engineering applications such as tunnel linings, concrete gravity dams, concrete retaining walls, socketed piers, and shotcrete as a support for rock mass (Fishman, 2009; Chang et al., 2018). In such structures, the interface between rock and concrete is usually considered as the weakest structural zone, causing the initiation and growth of cracks and final failure along the interface (Zhong et al., 2014; Dong et al., 2019).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".