The Relationship between Bond Strength and Critical Penetration Depth of Rust in Reinforced Concrete Structures
Bibliographic record
Abstract
Bond strength and critical penetration depth of rust are major factors that affect the service life of reinforced concrete structures. This research endevoured to establish a relationship between the bond strength and critical penetration depth of rust for reinforced concrete structures. There are 7 brands of Cem 1 cement in Kenya available for use in concrete structures. To achieve the desired objective, three Cem 1 cement brands (Cem A, B and C), fine aggregates, coarse aggregates and steel were obtained from the local Kenyan market. The chemical and physical properties of the materials were investigated. For a selected design strength of 25N/mm2, concrete materials were batched by weight and mixed by an electric pan mixer. For each brand of cement 9 cubes of size 150mm * 150mm * 150mm for a compression test, 9 cylinders of 150mm * 300mm for tensile strength and 9 cylinders of 150mm * 300mm for bond strength were cast. After 24 hours, the cast specimens were demoulded and immersed in curing tanks for 27 days. Specimens for compression, split tensile and bond strength were tested at 7,14 and 28 days. From the results, it was observed that the chemical composition of Cem 1 brands in the Kenyan market vary, which affects the hardening properties of concrete. A model for the critical penetration depth of rust in reinforced concrete was proposed by establishing a correlation between the spilt tensile and bond strength and substituting it in the Xu and Shayan model. The proposed and published models compared well. From the proposed model, a relationship between the critical penetration depth and bond strength was established. It was noted that the critical penetration depth increased with an increase in the bond strength of reinforced concrete. The results of this research are expected to contribute to the modeling of the service life of reinforced concrete structures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".