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Record W3175090342 · doi:10.17794/rgn.2021.3.7

DEFINING GEOEXCHANGE EXTRACTION RATES IN THE SAME GEOLOGICAL ENVIRONMENT FOR DIFFERENT BOREHOLE GEOMETRY SETTINGS – PILOT RESULTS FROM THE HAPPEN - HORIZON 2020 PROJECT

2021· article· en· W3175090342 on OpenAlexaff
Tomislav Kurevija, Marija Macenić, Tea Sabolić, Dalibor Jovanović

Bibliographic record

VenueRudarsko-geološko-naftni zbornik · 2021
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsBoreholeHeat exchangerGeothermal gradientExtraction (chemistry)ThermalGeologySpiral (railway)HorizonGeotechnical engineeringPetroleum engineeringGeometryEngineeringChemistryMathematicsGeophysicsMechanical engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Kindergarten Grdelin in the city of Buzet, Istria, Croatia, was chosen to undergo a deep retrofit of the current thermotechnical system, as a part of the HORIZON 2020 HAPPEN project1. The existing shallow spiral heat exchanger field is insufficient to cover heating loads of the building. Therefore, additional BHEs were drilled and completed to determine optimal borehole heat exchanger type within the same geological environment. Four BHEs, either single U (1U) or double U (2U), with different geometrical setting and depth were tested: BHE-1 (50 m, 2U DN32 ribbed), BHE-2 (75 m, 2U DN40 ribbed), BHE-3 (100 m, 2U DN32 smooth) and BHE-4 (150 m, 1U DN45 ribbed). A thermal response test (TRT) was performed to obtain the ground thermal properties. Furthermore, synthetic TRT curves were calculated to describe temperature response in the case of different heat pulses. This was done to determine heat extraction rates and the capacity of each BHE type, according to EN14511 norm. It was established that the BHE-4 is the optimal design for heating and cooling purposes on the selected site due to positive impact of the geothermal gradient, higher initial borehole temperature and a positive effect of the ribbed inner wall.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.262
Teacher spread0.234 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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