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Record W4246481819 · doi:10.32920/ryerson.14656995

Evaluating the use of straw bales in achieving passive house certification (PHIUS+ 2015) in western Canada

2021· preprint· en· W4246481819 on OpenAlexaffabout
Ashley Lubyk

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsToronto Metropolitan UniversityUniversity of Calgary
Fundersnot available
KeywordsStrawEmbodied energyEnvironmental scienceCarbon footprintCertificationAgricultural engineeringComputer scienceGreenhouse gasEngineeringEcologyAgronomy

Abstract

fetched live from OpenAlex

Achieving Passive House certification requires super insulation which can significantly raise the embodied energy and carbon footprint of a project, effectively front-end loading the climate impact, especially where petrochemical foam-based products are used. This research sought to evaluate the use of straw bales - a low embodied energy, carbon sequestering agricultural by-product - to achieve PHIUS+2015 certification. A straw bale wall system was adapted to a single-family detached reference house designed to meet the Passive House standard. The wall system was evaluated for applicability across three Western Canadian cities using WUFI Passive energy simulation software to evaluate compliance; thermal bridging and hygrothermal performance were also evaluated. It was found that the proposed straw bale wall assembly satisfied the PHIUS+ 2015 requirements in all three locations - Saskatoon, Calgary, and Kelowna - with only minor changes required to the reference house design. The annual heating demand and peak heating load, the two targets most sensitive to design changes, were, respectively, 4% and 8.6% below the target in Saskatoon, 63.1% and 21.3% below in Calgary, and 63.1% and 32.6% below in Kelowna. The research also revealed that maintaining a high degree of air tightness is essential for satisfying the requirements. Overall, this research demonstrates that straw bales can be a beneficial component in creating high performance enclosures without exacting a large embodied carbon footprint.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.122
GPT teacher head0.299
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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