Cost-Effective UHPC for Accelerated Bridge Construction: Material Properties, Structural Elements, and Structural Applications
Bibliographic record
Abstract
Accelerated bridge construction (ABC) is becoming progressively popular in China due to its advantages in sustainable development. However, some challenges still prevent it from being further widespread, especially in some harsh environments. As one of the greatest advances in material science, ultra-high-performance concrete (UHPC) is regarded as a competitive option for addressing the challenges of ABC due to its excellent material properties. A new cost-effective UHPC was developed with some modifications to weaken some adverse factors influencing the applications of UHPC in ABC, that is, high initial cost of material and steam/extreme heating curing requirements. Cost-effective UHPC is deemed to have the potential to build the critical zones of precast bridges, such as stress concentration zone, fatigue stress zone, inelastic deformation zone, harsh environment exposure zone, and late-cast joint zone, considering its material properties. In recent years, a series of tests have been done to investigate the cost-effective UHPC’s material properties and its structural elements’ mechanical behaviors. This paper systematically reports the cost-effective UHPC alternative for ABC from the laboratory tests on material properties and structural elements to real bridge implementations. Some challenges and future opportunities are presented for reference. The experimental results show that the cost-effective UHPC can have superior material properties and its structural elements can have satisfactory mechanical behaviors. Real engineering examples demonstrated that the cost-effective UHPC enables precast bridges to be lighter in weight, have higher strength, and support longer spans. The biggest challenge may be that more research and engineering examples are required to validate the feasibility of UHPC codes for cost-effective UHPC when it is applied in ABC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".