Mechanical and Durability Characteristics of Latex‐Modified Fiber‐Reinforced Segment Concrete as a Function of Microsilica Content
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Bibliographic record
Abstract
This study evaluated the performance of latex‐modified fiber‐reinforced concrete (RC) segments as a function of the substitution level of microsilica and type of reinforced fiber, to address the problem of corrosion of steel segments and steel‐reinforced fiber segments, which are commonly used to shield tunnel‐boring machine (TBM) tunnels in urban spaces. Our study compared macro synthetic, steel, and hybrid (macro synthetic fiber + polypropylene fiber) reinforcing fibers. The substitution levels of microsilica used were 0, 2, 4, and 6%. The target strengths were set at 40 and 60 MPa to test compressive strength, flexural strength, chloride ion penetration resistance, and impact resistance. Testing of latex‐modified and fiber‐reinforced segment concrete showed that the compressive strength, flexural strength, and chloride ion penetration resistance increased with an increasing substitution level of microsilica. These improvements were attributed to the densification of the concrete due to filling micropores with microsilica. Micro synthetic fiber was more effective in terms of improved compressive strength, flexural strength, and chloride ion penetration resistance than steel fiber. These results were due to the higher number of micro synthetic fibers per unit volume compared with steel fiber, which reduced the void volume and suppressed the development of internal cracks. The optimal microsilica content and fiber volume fraction of micro synthetic fiber were 6% and 1%, respectively. To evaluate the effects of the selected mixtures and hybrid fibers simultaneously, other mixing variables were fixed and a hybrid fiber mixture (combination of macro synthetic fibers and polypropylene fibers) was used. The hybrid fiber mixture produced better compressive strength, flexural strength, chloride ion penetration resistance, and impact resistance than the micro synthetic fibers.
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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 | 0.000 |
| 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) | 0.000 | 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 it