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Record W2005663192 · doi:10.1021/es026275r

Dissolution of Entrapped DNAPLs in Variable Aperture Fractures:  Experimental Data and Empirical Model

2003· article· en· W2005663192 on OpenAlexaff
Sarah Dickson‐Anderson, Neil R. Thomson

Bibliographic record

VenueEnvironmental Science & Technology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDissolutionMass transferMineralogyMass transfer coefficientChemistryEnvironmental scienceGeologyMaterials scienceChromatography

Abstract

fetched live from OpenAlex

An appreciation of the dissolution from entrapped nonaqueous phase liquids (NAPLs) in fractures is essential as we attempt to understand and predict the fate of NAPLs present in fractured rock systems. Eight long-term dissolution experiments using 1,1,1-trichloroethane and trichloroethylene were conducted in two laboratory-scale dolomitic limestone variable aperture fractures under various conditions. Between 560 and 2600 fracture volumes of water were passed through the fractures resulting in the removal of 10-60% of the initial mass trapped. The effluent concentration profiles revealed three distinct and characteristic stages of dissolution: an initial pseudosteady stage, a transient stage, and a tailing stage. On average, 8% of the initial volume of NAPL present was removed during the initial pseudosteady stage. Data from the dissolution experiments were used in conjunction with statistical techniques to develop a continuous empirical model describing the initial pseudosteady and transient stages of dissolution. The model was used to successfully replicate effluent concentration data from two separate and independent dissolution experiments. The experimental results provide an indication of the expected dissolution behavior of entrapped NAPLs, while the developed model is a useful tool for characterizing mass transfer rates in variable aperture fractures.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations34
Published2003
Admission routes1
Has abstractyes

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