Thermal, Moisture and Energy Performance of a Hempcrete Test Structure in the Northern Prairie Climate of Manitoba, Canada
Bibliographic record
Abstract
The processing of industrial hemp, cannabis sativa, results in three basic constituents seed, fibre, and hurd. Within Manitoba the main focus is with seed and oil products. When considering the entire plant approximately 60-70% is the predominantly cellulose woody core called the hurd. A combination of hemp hurd, a binder and water in various proportions is used in the construction of buildings referred to as hempcrete. Hempcrete is used as an environmental barrier providing resistance to heat transfer and to manage moisture of the building envelope. Engineering and architectural designers practicing in the field of non-conventional material applications have clearly indicated a need for design data. This paper presents a portion of research data collected over the past 18 months from a 23.8 m2 (256 ft2) test building on the campus of the University of Manitoba at the Alternative Village. The design temperatures for this location range from-35°C to +32°C. The structure was built using 300 mm thick pre-fabricated hempcrete panels. In addition to indoor and exterior ambient conditions, the temperature is monitored at 40 locations within the envelope - at the interior, middle and exterior providing a profile through the wall system. Similarly, the relative humidity is monitored within the wall and used in conjunction with a sorption isotherm to estimate the moisture content within the assembly. The building is kept at a constant temperature during the heating season with the energy consumption monitored continuously. This building is one of several on the test site that are all identical in terms of size and configuration. This paper will provide a comparison between the thermal, moisture and energy performance of the hempcrete structure and a conventional wood frame, batt-insulated building that represents the vernacular construction in Manitoba.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".