Sustainable reinforced concrete design: The role of ultra-high performance concrete (UHPC) in life-cycle structural performance and environmental impacts
Bibliographic record
Abstract
Ultra-high performance concrete (UHPC), an advanced type of concrete material that shows superior mechanical and durability performance, brings promises of reducing the material usage and increasing the life span of conventional concrete structures. However, the environmental benefits of adopting UHPC have not been well understood because of a lack of life-cycle comparison between UHPC and conventional concrete structures. To address this gap, a structural, corrosion, and carbon emissions analysis of UHPC and concrete beams of similar functions (i.e., strength and stiffness) was completed. In addition to adopting UHPC in the full section, a new composite beam concept was also proposed to have UHPC in the compression zone only. Based on finite element (FE) analysis, UHPC beams were designed to show similar stiffness and strength as the concrete beams while the cross-section areas were greatly reduced. Service life spans were then determined through a time-dependent multi-physics modeling framework. Subsequently, analysis regarding the material costs, initial and life-cycle carbon emission was done. The simulation results show that the composite beam can significantly reduce cross-sectional area and self-weight with less than 13% increase in material costs. The carbon emissions of the composite beam was over 25% lower than that of the concrete beam, both in the initial and life-cycle range. Additionally, full UHPC beams could show similar initial carbon emission and around 48% lower life-cycle carbon emissions compared to the concrete beams.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".