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Record W4402650859 · doi:10.1051/e3sconf/202456926001

Evaluation of the performance of bituminous geomembranes (BGMs) as vapour barriers

2024· article· en· W4402650859 on OpenAlexaff
Antara Arif, F.B. Abdelaal, Sam Bhat

Bibliographic record

VenueE3S Web of Conferences · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsEnvironment and Climate Change CanadaQueen's University
Fundersnot available
KeywordsGeomembraneAsphaltEnvironmental scienceForensic engineeringMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Vapour barriers (VBs) are essential in maintaining the indoor air quality of home basements or industrial facilities, especially when subsurface contamination poses a risk to human health. It is of utmost importance that the material installed as VB has the capacity to prevent contaminant migration into the indoor air space and reduce its concentration to an acceptable limit. Bituminous geomembranes (BGMs) have been used as contaminant barriers in spite of the gap in research regarding the permeation of volatile organic compounds (VOCs) through BGMs. This study examines the performance of a 4.1mm thick elastomeric BGM as a diffusive barrier to four commonly found VOCs; benzene, toluene, ethylbenzene, and xylenes (BTEX), utilizing computer modelling of contaminant migration from a contaminated soil source to a hypothetical warehouse building constructed on a brownfield site. The effectiveness of BGM in preventing vapour intrusion is evaluated based on its capacity to keep the indoor air concentration of the contaminant below the recommended exposure limits (RELs). Based on the modelling results, the BGM can be expected to perform as a very efficient VB for the simulated warehouse if quality control can be ensured during installation. This modelling approach can be adopted to investigate BGMs’ performance in different remediated site scenarios to make scope for a robust decision-making process regarding the construction and the engineering control requirements.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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 teacher head, not a consensus.

Study designObservational
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
Published2024
Admission routes1
Has abstractyes

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