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Record W3047039983 · doi:10.3390/w12082222

Impact of Standing Column Well Operation on Carbonate Scaling

2020· article· en· W3047039983 on OpenAlexafffund
Léo Cerclet, Benoît Courcelles, Philippe Pasquier

Bibliographic record

VenueWater · 2020
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCloggingCalciteGroundwaterEnvironmental scienceCalcium carbonateCarbonate mineralsScalingEnvironmental engineeringHydrology (agriculture)ChemistryMineralogyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Standing column well constitutes a recent promising solution to provide heating or cooling and to reduce greenhouse gases emissions in urban areas. Nevertheless, scaling issues can emerge in presence of carbonates and impact their efficiency. Even though a thermo-hydro-geochemical model demonstrated the impact of the water temperature on carbonate concentration, this conclusion has not been yet demonstrated by field investigations. To do so, an experimental ground source heat pump system connected to a standing column well was operated under various conditions to collect 50 groundwater samples over a period of 267 days. These field samples were used for mineral analysis and laboratory batch experiments. The results were analyzed with multivariate regression and geochemical simulations and confirmed a clear relationship between the calcium concentrations measured in the well, the temperature and the calcite equilibrium constant. It was also found that operating a ground source heat pump system in conjunction with a small groundwater treatment system allows reduction of calcium concentration in the well, while shutting down the system leads to a quite rapid increase at a level consistent with the regional calcium concentration. Although no major clogging or biofouling problem was observed after two years of operation, mineral scales made of carbonates precipitated on a flowmeter and hindered its operation. The paper provides insight on the impact of standing column well on groundwater quality and suggests some mitigation measures.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.701

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)0.0010.000

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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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 designSimulation or modeling
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

Citations10
Published2020
Admission routes2
Has abstractyes

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