Seismic Performance and LCA Comparison between Concrete and Timber–Concrete Hybrid Buildings
Bibliographic record
Abstract
The growing demand for energy-efficient and environmentally sustainable building materials has led to an increasing interest in hybrid timber-concrete construction. These structures combine the advantages of the two materials, potentially reducing the carbon footprint, shortening construction timelines, and improving seismic and building physics performance. Herein the structural and environmental performance of ten-story timber-concrete hybrid and a pure concrete building, designed for the Guizhou Province, China, were compared. The structural analysis revealed a significant reduction in the self-weight and base shear of the hybrid structure. The life-cycle analysis demonstrated that the hybrid building outperformed the concrete building in six categories, including global warming potential, acidification potential, human health particulate, eutrophication potential, ozone depletion potential, and photochemical ozone formation potential. Notably, the hybrid building exhibited nearly 65% lower emissions in terms of global warming potential. Moreover, the inclusion of wood components offered the added benefit of carbon storage throughout their lifespan. These findings provide compelling support for the development and implementation of high-rise timber-based hybrid buildings in China. The advantages observed in both structural and environmental aspects encourage the adoption of this innovative construction approach, contributing to sustainable and eco-friendly building practices.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".