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Record W2980473868 · doi:10.3390/geosciences9100440

Dipole and Convergent Single-Well Thermal Tracer Tests for Characterizing the Effect of Flow Configuration on Thermal Recovery

2019· article· en· W2980473868 on OpenAlexaff
Jérôme de La Bernardie, Olivier Bour, Nicolas Guihéneuf, Eliot Chatton, Laurent Longuevergne, Tanguy Le Borgne

Bibliographic record

VenueGeosciences · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Guelph
FundersAgence Nationale de la Recherche
KeywordsThermalTRACERAdvectionInflowBoreholeDipoleGeologyMechanicsGeothermal gradientThermal diffusivityFlow (mathematics)AquiferMaterials scienceGeophysicsEnvironmental scienceGeotechnical engineeringMeteorologyGroundwaterChemistryThermodynamicsPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Experimental characterization of thermal transport in fractured media through thermal tracer tests is crucial for environmental and industrial applications such as the prediction of geothermal system efficiency. However, such experiments have been poorly achieved in fractured rock due to the low permeability and complexity of these media. We have thus little knowledge about the effect of flow configuration on thermal recovery during thermal tracer tests in such systems. We present here the experimental set up and results of several single-well thermal tracer tests for different flow configurations, from fully convergent to perfect dipole, achieved in a fractured crystalline rock aquifer at the experimental site of Plœmeur (H+ observatory network). The monitoring of temperature using Fiber-Optic Distributed Temperature Sensing (FO-DTS) associated with appropriate data processing allowed to properly highlight the heat inflow in the borehole and to estimate temperature breakthroughs for the different tests. Results show that thermal recovery is mainly controlled by advection processes in convergent flow configuration while in perfect dipole flow field, thermal exchanges with the rock matrix are more important, inducing lower thermal recovery.

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 score0.647
Threshold uncertainty score0.383

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)0.0000.000

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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