Impact of Moisture and Load on Vertical Movement of a Simulated Platform Frame Wood Structure
Bibliographic record
Abstract
Abstract The objective of this study was to assess the relative contributions of wood shrinkage and building dead loads to vertical displacement in the form of height loss for wood-frame structures. Identifying the relative contributions of these factors while monitoring full-sized buildings presents significant challenges; therefore, a laboratory test was conducted under controlled hygrothermal conditions and loading. Two small-scale wood-frame structures were constructed with dimension lumber wall assemblies and floor joists. Both model structures were equipped with vertical movement and moisture content (MC) monitoring systems. The structures were conditioned in a chamber to a MC of approximately 20 %, and then moved into the laboratory environment for drying and loading. Model Structure No. 1 was loaded immediately; model Structure No. 2 was not loaded until after the wood had dried to the equilibrium MC. By using a unique lever system, the applied load simulated a dead load that could be experienced by the bottom floor of a six-story wood-frame building. Shrinkage coefficients were measured using samples cut from the horizontal framing members. The results suggested that the loads “forced” the structures to displace downward. At the driest time in the laboratory, the total movement of model Structure No. 1 reached a maximum of about 19 mm after 10 months, which is comparable to in situ recorded measurements from the bottom floor of a four-story wood-frame building in coastal British Columbia. Shrinkage appeared to account for 70 % of the total vertical movement, with the remaining 30 % contributable to load-induced displacement under the conditions of this test. Model Structure No. 2 showed less vertical movement but more initial displacement than model Structure 1 due to a larger settlement. This study suggested that there may be a need to consider the effect of loads in addition to wood shrinkage when estimating building height loss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".