Cracking Pattern and Bearing Capacity of Steel Fiber-Reinforced Concrete Single-Layer Tunnel Lining
Bibliographic record
Abstract
In recent years, steel fiber-reinforced concrete (SFRC) single-layer linings have been used in tunnel engineering. Compared to plain concrete single-layer linings, SFRC single-layer linings demonstrate enhanced bearing capacity, durability, and sustainability. Existing studies primarily focused on the mechanical properties of SFRC; however, limited investigations have been conducted on the cracking pattern of SFRC linings. This study uses laboratory tests to examine the influence of steel fiber content and aspect ratio on the mechanical properties of concrete, such as compressive strength and elastic modulus. After the recommended content and aspect ratio of steel fiber are proposed through tests, the cracking pattern and safety performance of plain concrete and SFRC linings under surrounding rock pressure are studied using a similar model test. The test results indicate that the recommended steel fiber volume fraction and aspect ratio for CF35 SFRC are 0.58% and 70, respectively. Due to the effect of loose load, cracks initially develop on the inside of arch crowns in both plain concrete and SFRC single-layer linings. Subsequently, new cracks appear on the inside of the lining floor and the outside of the two wall feet. Numerous narrow cracks with rugged and winding expansion paths can be found on SFRC single-layer linings. Conversely, plain concrete single-layer linings exhibit fewer cracks with larger widths along a straighter path. The initial cracking load of a single-layer lining made of plain concrete is 0.027 MPa, whereas for a single-layer lining made of SFRC, it is 0.04 MPa. This indicates that SFRC can effectively enhance the initial cracking load of lining structures. In the event of damage to the lining, the most critical area for the plain concrete single-layer lining is at the two wall feet, where the minimum safety factor is 1.66. However, for the SFRC lining in the same location, the safety factor is 2.7, resulting in a 62.7% increase in safety.
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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 | 0.000 | 0.001 |
| 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".