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Record W3215858333 · doi:10.7939/r3-656c-d183

Parametric Analysis for the Thermal Evaluation of Masonry Walls

2021· article· en· W3215858333 on OpenAlexaboutno aff
Amy Huynh

Bibliographic record

VenueUniversity of Alberta Library · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMasonryParametric statisticsGeologyStructural engineeringGeotechnical engineeringEngineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

Newer energy codes for buildings in Canada now require energy losses associated with thermal bridging in smaller components to be accounted for. In masonry cavity wall systems, most of the energy losses from thermal bridging are due to structural penetrations at floor levels located at the shelf angles, the supports of the brick veneer. This is mostly due to shelf angles being designed following outdated guidelines, resulting in large steel shelf angles that creates bands of thermal leakage around the entire building. These old practices are gradually being replaced with intermittently spaced stand-off shelf angle connectors which reduce the cross-sectional area of thermal bridging. Another contributing factor of thermal bridging in shelf angle systems is that they are mostly made of steel, which is a highly conductive material. New technologies, such as plastic polymers, have been proposed to reduce thermal bridging losses, but there are few studies on the performance of the various types of polymers. The current industry standard of performance-based building code compliance is 3D numerical thermal modeling, which provides accurate predictions of the thermal performance of exterior building envelope systems. Although 3D numerical modeling is a highly reliable simulation method (if performed correctly), a limitation is the lack of capacity to run models at the level of complexity required by the building codes. It is also a costly and timely process because it is often contracted out to third party consultants. This study uses 3D thermal modeling to investigate the influence of various parameters (i.e., stand-off shelf angle connector geometry, thermal properties, spacing of stand-off connectors, insulation thickness, and structural backup type) on the thermal performance of the envelope (i.e., heat flux through the assembly). These parameters were chosen as the focus of the study due to their high level of variability that may occur from detail to detail. A second goal of this study is to use the results of the 3D models to determine a numerical relationship to calculate thermal bridging effects of various influential parameters, instead of having to model a new assembly each time. For stand-off shelf angle connector geometry, it was found the heat flux difference between using a proprietary bracket and knife plate system was negligible. Additionally, reducing the spacing between stand-off shelf angle connectors appears to have the greatest range of influence on thermal performance for concrete masonry unit (CMU) backups on concrete slabs, and by extension, also steel stud backups. Wood stud backups are generally not affected by stand-off shelf angle connector spacing or insulation type and thickness. The linear transmittance results of the proprietary bracket, with a wood intermediate floor are almost the same value (same value when rounded to the nearest hundredth decimal point) regardless of insulation type and thickness. This is not surprising as the wood stud flooring has a low conductivity and the heat transferred from the interior to exterior that reaches the proprietary brackets is already a small amount. For CMU backups, changing from hot-dipped galvanized steel (HDG) steel to glass-fiber reinforced polymer (GFRP) knife plates, reduces the thermal bridging through the assembly because GFRP has a much lower conductivity than HDG steel. The difference appears to be more significant as the insulation thickness increases. For steel stud backups, the result from changing HDG to GFRP stand-off shelf angle connectors were more dramatic, as the GFRP connector had a linear transmittance that was nearly zero. This indicates that the full wall simulation provided a heat flux density value very close to its clear wall value. So generally, for a steel stud backup, a GFRP stand-off shelf angle connector is not considered a thermal bridge.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.183
Teacher spread0.169 · 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
Published2021
Admission routes1
Has abstractyes

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