Investigation of Mechanical Properties of Different Fiber Reinforced Engineered Cement Composites
Bibliographic record
Abstract
Engineered cementitious composite (ECC) is a fiber reinforced cementitious material with multiple cracking qualities that induce pseudo-strain hardening prior to softening, which can reach up to a tensile strain of 3 to 8%.However, the production cost of ECC is high due to the high prices of synthetic fibers such as polyethylene (PE) and polyvinyl alcohol (PVA) fibers.So, the application of ECC is limited in the construction sector.The aim of the study is to evaluate the properties of a cheap fiber Polypropylene (PP) in an ECC and to check the effect of various fibers on the concrete matrix through non-destructive tests (NDTs).For this purpose, the ECC-M45 mix originally developed by Victor Li is followed.Firstly, oiled PVA (OPVA) fibers are used, to be later replaced by PE and PP fibers.The compressive & tensile strength of concrete mixes are compared followed by ultrasonic-pulse velocity (UPV) and rebound hammer (RH) tests.Results show that ECC-PE shows the highest tensile strength 5.87MPa followed by ECC-OPVA (3.74MPa) and ECC-PP (3.34MPa).ECC-PE also shows the highest ultimate strains 11.15% followed by ECC-PP (7.2%) and ECC-OPVA fibers (1.94%).ECC-PP shows continuous strain hardening indicating better multi-cracking than ECC-OPVA which shows a steep drop in stress beyond 3.74MPa, yielding 2MPa stress at ultimate strain.The compressive strength of ECC-OPVA is 57.85MPa which is 6.8% and 42% greater than ECC-PP and ECC-PE fibers, respectively.The non-destructive tests show both OPVA-ECC and PP-ECC as superior and a big quality difference between them and PE-ECC.Therefore, the NDTs familiarize more with the compressive strength test irrespective of the fiber type which shows that all fibers have good bonding ability.
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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 | 0.000 |
| 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 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".