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Record W2057939706 · doi:10.1139/t09-078

Heat transport simulations in a heterogeneous aquifer used for aquifer thermal energy storage (ATES)

2010· article· en· W2057939706 on OpenAlexaffvenueabout
D. W. Bridger, D. M. Allen

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsSNC-Lavalin (Canada)Simon Fraser University
Fundersnot available
KeywordsAquiferAquifer testGeologyThermal energy storageGroundwaterGeotechnical engineeringAquifer propertiesGroundwater flowSpecific storageWater wellEnvironmental scienceHydrology (agriculture)Petroleum engineeringGroundwater recharge

Abstract

fetched live from OpenAlex

A modelling study was carried out to evaluate the influence of aquifer heterogeneity, as represented by geologic layering, on heat transport and storage in an aquifer used for aquifer thermal energy storage (ATES). An existing ATES system in Agassiz, British Columbia, Canada, was used as a case study. The system consists of four production wells completed in an unconfined heterogeneous aquifer consisting of interbedded sands and gravels. An additional dump well was installed to provide for heat dissipation during the peak cooling periods. Three monitoring wells and the production wells were logged for temperature periodically within the first 1.5 years of operation. A three-dimensional groundwater flow and heat transport model was developed using FEFLOW. Simulation results indicate that heat and (or) cold energy moved preferentially in discrete zones within the aquifer or at least entered the wells over discrete intervals. Monitoring data support model results, but show that thermal storage was successfully achieved despite a significant cooling operation during the first year.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.999

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)0.0020.000

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 designNot applicable
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

Citations56
Published2010
Admission routes3
Has abstractyes

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