Hygrothermal performance of natural building materials: Simulations and field monitoring of a case study home made of wood fiber insulation and clay
Bibliographic record
Abstract
This contribution presents temperature and relative humidity data monitored over nearly two years for a case study building made of natural building materials. The case study building is a single-family house located in Denmark made of wood fiber insulation, wood fiber boards and indoor clay plaster without any membranes. Three different types of cladding systems have been tested: 1) mineral plaster rendering; 2) wood cladding applied directly over wood fiberboards; 3) wood cladding with a ventilated cavity. Monitored data is provided and compared with simulations performed with a commercial hygrothermal software. The moisture content and mold growth index are calculated from monitored data. The data indicates that the hygrothermal performance of the roof is excellent (RH < 70%); the hygrothermal performance of the walls with the three different cladding systems is good; one out of two sensor groups in the floor exhibits a moisture content up to 18% at the cold side of the insulation during summer and fall. Securing sufficient and evenly distributed crawlspace ventilation is recommended for eliminating concerns of eventual mold growth. Measurements show that materials employed in this house respond quickly to moisture changes, more quickly that simulated data. This work highlights the need for validating and adjusting WUFI simulation results with measured data to provide reliable results for building envelopes composed of highly hygroscopic plant-based materials. For these assemblies in these conditions, including a vapor retarder is not needed for achieving a satisfactory hygrothermal behavior.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".