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Record W6979824740

Alternative heating systems for northern remote communities : techno-economic analysis of ground-source heat pumps in Kuujjuaq, Nunavik, Canada

2019· dissertation· en· W6979824740 on OpenAlexfundaboutno aff

Bibliographic record

VenueSkemman · 2019
Typedissertation
Languageen
FieldArts and Humanities
TopicLinguistics and Education Research
Canadian institutionsnot available
FundersInstitut national de la recherche scientifique
KeywordsGeothermal gradientHeat pumpHeat exchangerWork (physics)Geothermal energyBoreholeDiesel fuelHeating system
DOInot available

Abstract

fetched live from OpenAlex

Geothermal energy, through the utilisation of ground source heat pump (GSHP) has been proposed as a heating alternative to the low efficiency and environmentally adverse diesel furnaces currently being used to meet residential heating demand in Nunavik, a cold and remote region covering the northern third of Québec, Canada. This study describes the application of the G.POT method, developed by Casasso and Sethi (2016) to create maps of the shallow geothermal potential in Kuujjuaq, the largest village in Nunavik. Resulting maps show a relatively high potential for such cold region, ranging between 5.8 MWh/year and 22.9 MWh/year for borehole heat exchanger lengths of 100 m to 300 m. 50-years life-cycle cost analyses of such geothermal systems reveal that compression GSHP with electricity derived from solar photovoltaic panels costs as low as CAD$0.15/kWh and forms the most economically attractive heating option in Kuujjuaq as compared to the diesel furnace heating currently used at CAD$0.21/kWh. Studies focusing on the applications of GSHP in subarctic conditions are currently limited and hence, this work is expected to fill in this gap.

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 score0.053
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.038
GPT teacher head0.294
Teacher spread0.256 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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