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Record W2922018934 · doi:10.1016/j.egypro.2018.12.019

Investigation of viability of seasonal waste heat storage in rock piles for remote communities in cold climates

2019· article· en· W2922018934 on OpenAlexaffabout
Seyed Ali Ghoreishi‐Madiseh, Amir Safari, Leyla Amiri, Durjoy Baidya, Marco Antonio Rodrigues de Brito, Ali Fahrettin Kuyuk

Bibliographic record

VenueEnergy Procedia · 2019
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental scienceWaste heatThermal energy storagePileWaste managementEnvironmental engineeringEngineeringGeotechnical engineeringHeat exchanger

Abstract

fetched live from OpenAlex

Communities situated in distant areas are deemed as 'remote' and have either very limited or no access to power grid lines. Therefore, most of these communities greatly depend on diesel-burning for power and heat provision at all times. Nonetheless, nearly 30% of the energy associated with the diesel burning and power generation process is dissipated as heat through the exhaust streams of diesel generators. The waste heat in the exhaust stream is usually recovered during the winter season and directly used as a heat source when the communal heat demand is peaked. However, recovery of this energy potential is usually discarded during the summer period due to the low demand. Seasonal thermal storage on rock piles is a developing concept that can be a low-cost solution to resolve this issue. This paper proposes utilization of the heat wasted through the exhaust stream of diesel generators on rock piles as temporary storage during low demand times. In this sense, a remote cold climate community, such as those of Canada and Norway, is selected and potentiality of the seasonal rock pile thermal storage is investigated and presented.

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 score0.184
Threshold uncertainty score0.984

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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

Citations17
Published2019
Admission routes2
Has abstractyes

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