Physical and microstructural properties of insulating hempcrete mixes and their impact as infill system on the foundations due to increase in dead load
Bibliographic record
Abstract
Hempcrete is a particularly promising lightweight, porous, and breathable biocomposite material that has the potential to significantly reduce the embodied energy related to the construction of buildings while improving their indoor air quality. However, hempcrete’s properties and performance depend on various parameters such as ingredient amounts, binder type, hurd characteristics (e.g., particle size and porosity), and the amount of water. Therefore, there is a great need for research that will focus on the development and production of hempcrete mixes and materials using local, Canadian resources. This research study characterizes the physical, microstructural, and mechanical properties of nine hempcrete mixes developed using lime and eco-friendly pozzolans such as metakaolin, crushed brick, and natural hydraulic lime in varying relative proportions. Furthermore, it compares three different types of hempcrete walls against the conventionally insulated walls of a single-story house located in Winnipeg, using S-Timber 2019 software. The microstructure analysis of hurd particles showed their porous nature. The dry densities of all design mix range from 294.59 kg/m3 to 399.68 kg/m3, with the majority (⁓73%) falling between 320 kg/m3 and 370 kg/m3. The average compression strength of the developed samples ranged between 0.11 MPa and 0.51 MPa, whereas the average splitting tensile strength ranged between 0.010 MPa and 0.0348 MPa. The results show a positive correlation between the hempcrete’s mechanical properties and density, mainly, in the case of compressive strength. The microstructure analysis of all the design mixes exhibit adequate adhesion at the interface, and present high carbonation with some hydrates. The main findings suggest that locally sourced metakaolin and crushed brick are excellent alternatives to the expensive, imported hydraulic lime. The modeling analysis indicates an increase in the dead loads and foundation sizes due to hempcrete infill compared to the base case. The results also indicate that the best option for a house considering the increase in dead loads and foundation sizes, is a wall case that meets the energy code through the thinner wall composed of 100 mm of mineral wool and 140 mm of hempcrete.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".