STRUCTURAL AND LIFE CYCLE ANALYSES FOR A TIMBER-CONCRETE HYBRID BUILDING
Bibliographic record
Abstract
The concerns related to the impact of construction materials are increasing globally.Timber-based hybrid buildings combine the structural benefits of multiple materials, reduce the carbon footprint, shorten construction times, and potentially improve seismic and building physics performances.In this paper, a ten-story timber-concrete hybrid building, designed for a location in the Guizhou Province, China, is compared to a pure concrete building.The structural analysis showed that the self-weight of the hybrid structure was reduced by 30% compared with the concrete structure, and the base shear forces in X-and Y-directions decreased by 43% and 29%, respectively.The life-cycle analysis showed that hybrid building had lower impacts than the concrete building in six categories: global warming potential, acidification potential, human health particulate, eutrophication potential, ozone depletion potential, and photochemical ozone formation potential.Specifically, in terms of global warming potential, the hybrid building had nearly 65% lower emissions, and the wood components have the additional advantage to store carbon over their lifetime.These results promote the development and application of high-rise timber-based hybrid buildings in China.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".