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Record W7132116158

National Energy Code of Canada reference thermal resistance calculation methods compared to a validated 3D heat transfer simulation for framed walls containing thermal bridges

2020· article· en· W7132116158 on OpenAlexvenueaboutno aff
H. P. Schreiber, T. V. Moore, M. Ghobadi

Bibliographic record

VenueNPARC · 2020
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsnot available
Fundersnot available
KeywordsThermal resistanceASHRAE 90.1ThermalCode (set theory)Sensitivity (control systems)Heat transferSection (typography)Path (computing)
DOInot available

Abstract

fetched live from OpenAlex

Construction of buildings in Canada requires adherence to the minimum requirements of the National Energy Code for Buildings (NECB) through one of three respective compliance paths: the prescriptive path, the trade-off path, or the performance path. The most straight forward path is the prescriptive path, which defines minimum performance levels for different components and assemblies of the building to meet for compliance. One prescriptive requirement is a minimum effective thermal resistance value for the wall assembly. Within the prescriptive path, methods are referenced for determining the effective thermal resistance of wall assemblies, as detailed in section 3.1.1.5(5) of the NECB. Specifically, the effective thermal resistance of a wall assembly can be determined through either testing a representative wall assembly in accordance with ASTM C1363, or, calculation using: ISO 14683, two-or three dimensional modelling, or the calculation methods described in the ASHRAE Handbook of Fundamentals. Additional guidance for the use of the calculation methods described in the ASHRAE Handbook of Fundamentals for calculating the effective thermal resistance of framed walls (i.e. wood and steel stud framed) in accordance with the NECB is provided in the NECB “Users Guide”. This paper investigates the accuracy of using the methods described in the “User’s Guide” on three representative steel stud framed wall assemblies with increasing thickness of exterior insulation: none, 25 mm and 50 mm of thickness. The accuracy of each calculation method is determined by comparing the results to ASTM C1363 guarded hot box tests. This paper will focus on the accuracy of these calculation methods and include some commentary on any restrictions that should be imposed on the use of these methods, especially in instances where the framing can significantly influence the effective thermal resistance of the wall assembly through thermal bridging.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.213
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.005

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 head0.054
GPT teacher head0.290
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes2
Has abstractyes

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