Design of a structural insulating panel based on wood-based corrugated panels as an alternative to light-frame construction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The performance of building envelopes is one of the cores of environmental issues related to the construction sector. Lightweight wood framing, widely used in North America, appears to be a solution to be favored in this context. However, since structural thermal bridges are now considered in the thermal resistance of an opaque wall by the Canadian National Building Code, its thermal performance remains limited if it is to be maintained. Structural insulated panels (SIPs) are becoming increasingly popular in the scientific literature on construction. These systems have advantages over conventional systems, such as light-frame construction. This study focuses on the design of new envelope compositions based on wood-based corrugated panels. The design was carried out by reverse engineering conventional light-frame envelope systems. A functional specification was established based on the performance of traditional envelopes. These performances were evaluated according to thermal resistance, mold growth index, assembly time, environmental impact, cost, dimensions, etc. To calculate the mold growth index and thermal resistance, a model was built according to ASHRAE 160. It was run over a four-year period on COMSOL software. The results showed that one of the prototypes designed outperformed lightweight wood framing in terms of the specifications. • A design approach based on reverse engineering and specifications enabled us to design high-performance prototypes. • Mold growth indices for the compositions studied were calculated using Four-year hygrothermal simulations on COMSOL. • SIP-type assemblies integrating corrugated panels outperformed the currently recommended assembly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it