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Record W4289275220 · doi:10.1615/ichmt.2022.conv22.240

EFFECTS OF THE SOIL PROPERTIES ON CANADIAN WELLS PERFORMANCE: NUMERICAL SIMULATION

2022· article· en· W4289275220 on OpenAlexaboutno aff
Islam Boukail, Louay Fenchouch, Nabil Kharoua, Hamza Semmari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHeat transferThermal diffusivityHeat exchangerEnvironmental scienceInletSoil waterGeotechnical engineeringSoil scienceGeologyThermodynamicsGeomorphology

Abstract

fetched live from OpenAlex

Air-soil heat exchangers are among the most used in industrial applications involving heat transfer and therefore to face the increasing demand of renewable energy, especially in the residential sector. For this reason, this system is studied as a potential solution that could be integrated in the Positive Energy Pilot Building project. This study investigates the effect of different dry and saturated soils on the heat transfer. ANSYS Fluent is used for the simulation of a buried pipe. The pipe is 3m underground with a diameter of 0.11m. Different values of thermal diffusivity α=0.027-0.0715 m2/day for dry clay, saturated clay, dry gravel, saturated gravel, dry sand and saturated sand respectively are considered. The annual variation is presented to illustrate the characteristic periods with the corresponding performance of the heat exchanger. Then, more details are described for characteristic days of the year corresponding to extreme weather conditions (winter and summer). The physical interpretation shows the effect of different soil thermal diffusivities on the heat transfer. Saturated soils show better results for heat transfer and temperature difference between the inlet and outlet. Also, the effect of different Reynold numbers is studied where Re=10000-20000 for the saturated sand. The comparison showed that the best performance in terms of temperature difference was a value of 11.5 K during extreme periods of summer and winter. Re=14975 represents the optimal value of the Reynolds number under the conditions of the present study.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.667

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 head0.009
GPT teacher head0.185
Teacher spread0.177 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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