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Record W3039124853 · doi:10.1051/e3sconf/202017210003

Wetting and drying performance of cross-laminated timber related to on-site moisture protections: Field measurements and hygrothermal simulations

2020· article· en· W3039124853 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueE3S Web of Conferences · 2020
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsFPInnovationsConcordia University
Fundersnot available
KeywordsWettingMoistureCross laminated timberDurabilityTransverse planeEnvironmental scienceMaterials scienceStructural engineeringComposite materialGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Cross-laminated timber (CLT) panels are increasingly used in mid-rise buildings or even taller structures in North America. However, prolonged exposure to moisture during construction and in service is a durability concern for most wood products including CLT. To investigate practical solutions for reducing on-site wetting of mass timber construction, CLT specimens with a range of moisture protection measures, in six groups were tested in the backyard of FPInnovations’ Vancouver laboratory from Oct. 2017 to Jan. 2018. This study investigates the wetting and drying behaviours of the tested CLT specimens through 2-D hygrothermal simulations. The simulations are performed for base specimens (no protection measures) of group 1 (without joint or plywood spline) and group 2 (with a butt joint and plywood spline). For group 1, three data sources of material properties are used to create the models, and the data that led to the best agreement between simulations and measurement are used for creating the models of group 2. For group 2, two types of hygrothermal models are created with or without considering the differences in water absorption between the transverse and the longitudinal grain orientations. In addition, rain penetration is taken into account for the joint area. It is found that the model with considering the differences between transverse and longitudinal grain orientations shows a better agreement than that without considering such differences.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.286

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 head0.033
GPT teacher head0.249
Teacher spread0.216 · 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