Finite-Element Investigation of the Structural Behavior of Basalt Fiber Reinforced Polymer (BFRP)- Reinforced Self-Compacting Concrete (SCC) Decks Slabs in Thompson Bridge
Bibliographic record
Abstract
The need for a sustainable development and improved whole life performance of concrete infrastructure has led to the requirement of more durable and sustainable concrete bridges alongside accurate predictive analysis tools. Using the combination of Self-Compacting Concrete (SCC) with industrial by-products and fiber-reinforced polymer (FRP), reinforcement is anticipated to address the concerns of high carbon footprint and corrosion in traditional steel-reinforced concrete structures. This paper presents a numerical investigation of the structural behavior of basalt fiber-reinforced polymer (BFRP)-reinforced SCC deck slabs in a real bridge, named Thompson Bridge, constructed in Northern Ireland, U.K. A non-linear finite element (FE) model is proposed by using ABAQUS 6.10 in this study, which is aimed at extending the previous investigation of the field test in Thompson Bridge. The results of this field test were used to validate the accuracy of the proposed finite element model. The results showed good agreement between the test results and the numerical results; more importantly, the compressive membrane action (CMA) inside the slabs could be well demonstrated by this FE model. Subsequently, a series of parametric studies was conducted to investigate the influence of different parameters on the structural performance of the deck slabs in Thompson Bridge. The results of the analyses are discussed, and conclusions on the behavior of the SCC deck slabs reinforced by BFRP bars are presented.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".