MétaCan
Menu
Back to cohort
Record W2001687194 · doi:10.1063/1.4812647

A transient natural convection heat transfer model for geothermal borehole heat exchangers

2013· article· en· W2001687194 on OpenAlexaff
Seyed Ali Ghoreishi‐Madiseh, Ferri Hassani, Abdolmajid Mohammadian, Peter Radziszewski

Bibliographic record

VenueJournal of Renewable and Sustainable Energy · 2013
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of OttawaMcGill University
Fundersnot available
KeywordsMechanicsHeat transferNatural convectionCombined forced and natural convectionThermodynamicsConvective heat transferHeat exchangerHeat capacity rateMaterials scienceHeat spreaderPhysics

Abstract

fetched live from OpenAlex

The effect of buoyancy-driven natural convection on the performance of ground-coupled heat exchangers of closed loop geothermal systems is investigated. The governing equations of continuity, momentum, and energy balance are derived, taking into account a porous ground medium fully saturated with liquid water. Boussinesq approximation is used to model the effect of buoyancy forces in water. A three-dimensional finite-volume discretization method over a structured mesh is used to solve the governing equations numerically. The performance of the ground-coupled heat exchanger system is assessed based on the rate of energy extraction and the outlet fluid temperature. The effects of hydraulic conductivity of the heat exchange medium and seasonal variations of heat load on the heat transfer phenomenon are studied. The results are evaluated by comparing them against the results of existing conduction-based heat transfer models. The influence of natural convection on the sustainable rate of heat extraction from a geothermal resource is underlined and interpreted.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.208
Teacher spread0.199 · 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 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

Citations33
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Renewable and Sustainable EnergySame topicGeothermal Energy Systems and ApplicationsFrench-language works237,207