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Record W2019363177 · doi:10.1520/gtj100067

Falling-Head Permeability Tests in an Unconfined Sand Aquifer

2006· article· en· W2019363177 on OpenAlexaff
RP Chapuis, Véronique Dallaire, François Gagnon, Denis Marcotte, Michel Chouteau

Bibliographic record

VenueGeotechnical Testing Journal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGeotechnical engineeringAquiferPermeability (electromagnetism)GeologyHead (geology)Hydraulic headGroundwaterGeomorphology

Abstract

fetched live from OpenAlex

Abstract This paper examines the reliability of hydraulic conductivity estimates, k, obtained using equations of Hvorslev (1951) or Bouwer and Rice (1976) for falling-head tests in monitoring wells (MWs) having short screens at the bottom of an unconfined sand aquifer. Two issues are examined. First, the equations come from the theory of steady-state flow whereas a variable-head test means transient flow with a changing water table position. This first problem was investigated using a finite element analysis, taking into account the sand capillary retention curve and its saturated-unsaturated permeability. The main result was that the equations can still be used for variable-head tests. The effects of specific storage (elastic deformation of the solid matrix in saturated conditions) and delayed gravity drainage (frequently schematized by a specific yield) can be neglected for these tests. The second issue is how partial clogging or fine particle washing against the screen can influence the k value. This practical problem was investigated by using a surge block to develop MWs and then performing successive permeability tests to assess the effects of development. Before development, the tests provided k values in the range 1 to 12×10-2 cm/s, the average being equal to 2/3 of the large-scale k value obtained using a pumping test under steady-state condition. After development, the tests provided k values that were increased by 50% on average, and thus their mean value became almost equal to the pumping test k value.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.034
GPT teacher head0.273
Teacher spread0.239 · 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 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

Citations19
Published2006
Admission routes1
Has abstractyes

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