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Record W4250107932 · doi:10.32920/ryerson.14650122

Field Study of Hygrothermal Performance of Cross‐Laminated Timber Wall Assemblies with Built‐In Moisture

2021· preprint· en· W4250107932 on OpenAlexaff
Victoria Ruth McClung

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsToronto Metropolitan UniversityUniversity of Waterloo
Fundersnot available
KeywordsDurabilityMoistureCross laminated timberStructural engineeringClimate zonesWettingMaterials scienceEnvironmental scienceField (mathematics)Civil engineeringGeotechnical engineeringEngineeringComposite materialGeologyMathematics

Abstract

fetched live from OpenAlex

Cross-laminated timber (CLT) panels have potential market in North America for building mid-rise structures due to their good structural and seismic performance, lightweight, and prefabricated nature. However, to ensure long-term durability, the hygrothermal performance of CLT wall assemblies needs to be evaluated in terms of drying and wetting potential before their widespread adoption in North America. A test wall was constructed with initially wetted CLT panels, and monitored over a year. The drying behaviour of the panels was analysed, and results were compared to hygrothermal simulations. It was found from the field data that no tested wall assemblies in the given climate prevented the panels from drying in enough time to prevent decay initiation. The hygrothermal simulation program is capable of predicting general trends, and can predict if a wall be safe, but tends to be overly conservative. Further refinement of the model for wood is needed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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.

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

Citations5
Published2021
Admission routes1
Has abstractyes

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