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Record W4416705957 · doi:10.26868/25222708.2025.1737

Helium-based modelling approach for studying thermal-induced airflows in street canyon

2025· article· W4416705957 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBuilding Simulation Conference proceedings · 2025
Typearticle
Language
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUrban heat islandCanyonWind tunnelThermalStreet canyonBuoyancyAirflowUrban planningThermal comfort

Abstract

fetched live from OpenAlex

Non-isothermal phenomena in urban environment encounter considerable challenges, particularly in sub-scale implementations. When scaling down a realistic urban neighbourhood to a physical model in an appropriate size that is applicable for laboratory tests, achieving representative thermal boundary conditions often necessitates unrealistically high temperatures. To address this, a helium-based modelling approach is proposed as a cost-effective and safer alternative to traditional heating methods in wind tunnel experiments. By simulating buoyancy effects using helium, this method replicates thermal airflows, enabling the study of buoyancy-driven flow characteristics and heat distribution in urban spaces. A single street canyon model was employed to validate the similarity between hot air and helium within this framework. Preliminary results demonstrate the approach’s effectiveness and underscore its potential to advance urban environment research.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.056
GPT teacher head0.291
Teacher spread0.235 · 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