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Measurement of LNAPL Flux Using Single‐Well Intermittent Mixing Tracer Dilution Tests

2012· article· en· W2012911055 on OpenAlexfundno aff
Tim Smith, Tom Sale, Mark Lyverse

Bibliographic record

VenueGround Water · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsnot available
FundersSuncor Energy Incorporated
KeywordsDilutionTRACERMixing (physics)Flux (metallurgy)MechanicsStability (learning theory)Soil scienceChemistryEnvironmental scienceThermodynamicsPhysics

Abstract

fetched live from OpenAlex

The stability of subsurface Light Nonaqueous Phase Liquids (LNAPLs) is a key factor driving expectations for remedial measures at LNAPL sites. The conventional approach to resolving LNAPL stability has been to apply Darcy's Equation. This paper explores an alternative approach wherein single-well tracer dilution tests with intermittent mixing are used to resolve LNAPL stability. As a first step, an implicit solution for single-well intermittent mixing tracer dilution tests is derived. This includes key assumptions and limits on the allowable time between intermittent mixing events. Second, single-well tracer dilution tests with intermittent mixing are conducted under conditions of known LNAPL flux. This includes a laboratory sand tank study and two field tests at active LNAPL recovery wells. Results from the sand tank studies indicate that LNAPL fluxes in wells can be transformed into formation fluxes using corrections for (1) LNAPL thicknesses in the well and formation and (2) convergence of flow to the well. Using the apparent convergence factor from the sand tank experiment, the average error between the known and measured LNAPL fluxes is 4%. Results from the field studies show nearly identical known and measured LNAPL fluxes at one well. At the second well the measured fluxes appear to exceed the known value by a factor of two. Agreement between the known and measured LNAPL fluxes, within a factor of two, indicates that single-well tracer dilution tests with intermittent mixing can be a viable means of resolving LNAPL stability.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.044
GPT teacher head0.236
Teacher spread0.192 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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