Hygrothermal performance of natural building materials: Simulations and field monitoring of a case study home made of wood fiber insulation and clay
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
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.
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) | 0.000 | 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 it