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Record W2943946026 · doi:10.5539/enrr.v9n2p61

Natural Ventilation in Isolated Subsurface Structures in the Infrastructure: A Review

2019· review· en· W2943946026 on OpenAlexvenueno aff
Neil McManus, Assed Haddad

Bibliographic record

VenueEnvironment and Natural Resources Research · 2019
Typereview
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsNatural ventilationCover (algebra)Natural (archaeology)Atmosphere (unit)Ventilation (architecture)Air movementWork (physics)Environmental scienceComputer scienceMining engineeringGeologyMechanical engineeringEngineeringMeteorologyGeographyAtmospheric sciences

Abstract

fetched live from OpenAlex

The subsurface infrastructure contains many types of structures. Some are networked together in open systems while others are completely independent from each other. This study provides a summary of findings concerning ventilation induced by natural forces from reports published in the literature + additional unreported information concerning isolated subsurface structures. Isolated subsurface structures meet criteria for classification as confined spaces. Isolated subsurface structures experience two-way exchange of the internal atmosphere with the external atmosphere when the manhole cover or access hatch contains one or more openings. This finding is not appreciated by current practitioners of occupational health and safety knowledgeable in the area of confined spaces. Presently identified factors influencing ventilation induced by natural forces include the number/area of openings in the manhole cover, differences in temperature between the interior airspace and the external atmosphere, and air movement along the surface of the ground. Additional factors could include size or number of individual openings, placement of openings in the manhole cover or hatch, shape of the openings, and shape of the path followed during air exchange. In some cases, application of additional analysis provides information contained in the data but not presented in these documents. Demonstrating and understanding the interaction between these factors will enable optimization of design to maximize the rate of air exchange. Optimizing the rate of air exchange is essential to minimizing to the extent possible the risk posed to passersby and to workers engaged in preparation for entry and work inside these structures.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
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 head0.035
GPT teacher head0.314
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2019
Admission routes1
Has abstractyes

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