Bond–Slip Mechanism of Rammed Earth–Timber Joints in Chinese Hakka Tulou Buildings
Bibliographic record
Abstract
Hakka Tulou, a traditional form of Chinese building made of rammed earth and a timber frame, is characterized by its remarkable geometries, excellent thermal comfort, sustainability, and cultural value. The joints between rammed-earth walls and timber floor beams are critical structural elements and require an in-depth understanding of the load-bearing capacity for Hakka Tulou. To the best knowledge of the authors, this is the first study that investigates the bond–slip mechanism between timber beams and rammed earth. Eight pull-out tests were conducted on rammed earth–timber (RET) joints, in which the influence of compressive load, embedment length, and surface roughness was systematically studied. RET joints were analyzed based on the elastic solid-to-solid and pile-to-soil behaviors. The experimental results show that the bond–slip behavior could mainly be attributed to the friction, which depended on the normal stress and matric suction of unsaturated compacted earth. The test results were satisfactorily explained by geotechnical theories. Given the initial strength resulting from compaction and mobilized friction due to compression, a bond–slip model for rammed-earth structures was proposed. The parameters for the elastic zone were suggested for use in structural design. Rammed-earth buildings should be analyzed based on the principles of unsaturated soil mechanics, rather than elastic solid mechanics, even though rammed earth and underground soil are under fundamentally different conditions. The proposed design method for earth–timber joints could be applied to analyze Hakka Tulou or other similar earth buildings.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".