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Record W2918819366 · doi:10.3390/inventions4010014

Ground-Coupled Natural Circulating Devices (Thermosiphons): A Review of Modeling, Experimental and Development Studies

2019· review· en· W2918819366 on OpenAlexaff
Messaoud Badache, Zine Aidoun, Parham Eslami-Nejad, Daniela Blessent

Bibliographic record

VenueInventions · 2019
Typereview
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsNatural (archaeology)Environmental scienceComputer scienceGeology

Abstract

fetched live from OpenAlex

Compared to conventional ground heat exchangers that require a separate pump or other mechanical devices to circulate the heat transfer fluid, ground coupled thermosiphons or naturally circulating ground heat exchangers do not require additional equipment for fluid circulation in the loop. This might lead to a better overall efficiency and much simpler operation. This paper provides a review of the current published literature on the different types of existing ground coupled thermosiphons for use in applications requiring moderate and low temperatures. Effort has been focused on their classification according to type, configurations, major designs, and chronological year of apparition. Important technological findings and characteristics are provided in summary tables. Advances are identified in terms of the latest device developments and innovative concepts of thermosiphon technology used for the heat transfer to and from the soil. Applications are presented in a novel, well-defined classification in which major ground coupled thermosiphon applications are categorized in terms of medium and low temperature technologies. Finally, performance evaluation is meticulously discussed in terms of modeling, simulations, parametric, and experimental studies.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.142
GPT teacher head0.368
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2019
Admission routes1
Has abstractyes

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