Compressive behavior of FRP-tube-confined concrete short columns using recycled FRP materials from wind turbine blades: Experimental investigation and analytical modelling
Bibliographic record
Abstract
<abstract> <p>A major challenge in today's concrete construction is to lower its carbon footprint to the least possible level. This study provides insights on a new low-CO<sub>2</sub> alternative concrete whereby glass fiber-reinforced polymer (GFRP) materials from waste wind-turbine blades (WWTB)—termed as WWTB-GFRP—was utilized as: (ⅰ) replacement of Portland cement at 0%, 10%, 20%, and as (ⅱ) lightweight aggregate replacement for natural aggregates at 0%, 50%, and 100%. The resulting WWTB-GFRP concretes were used in concrete-filled fibre-reinforced polymer (FRP) tubes (CFFTs) whereby the latter serves as a stay-in-place formwork and external reinforcement. Pristine WWTB-GFRP materials (containing wood) and processed ones (by wood removal) were investigated. Results indicate that while both WWTB-GFRP powder and aggregates adversely affect the compression resistance (due to, respectively, the retarding effect of the powder and the slippery surface of the aggregates leading to reduced bonding with the bulk cementitious matrix), the confinement of WWTB-GFRP concrete with FRP tubes offers an innovative tool to restore the strength loss. In fact, valorizing WWTB-GFRP concrete in CFFTs allowed to increase the compressive resistance by more than 100%. Interestingly, under axial compression, FRP tube confinement shifted the stress–strain response from the conventional brittle response to a ductile one whereby the confinement affected the elastic and plastic responses differently. While FRP confinement increased in the elastic limit at higher WWTB-GFRP aggregate content, it resulted in lower slope of the plastic response at higher WWTB-GFRP aggregate content. An analytical assessment demonstrated that a WWTB-GFRP aggregate content of 55% will be optimum for enhancing both elastic and plastic responses. Building upon the ACI 440.2R-17 model for predicting the compressive response of confined concrete incorporating conventional aggregates, a modified model more sensitive to GFRP aggregates and with higher predictive ability was proposed. Research outcomes will contribute to recycling waste materials while endowing further sustainability to concrete.</p> </abstract>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".