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Record W7116133011 · doi:10.82417/mead-j940

Opportunities of high temperature heat pump integration in various industrial subsectors

2025· other· en· W7116133011 on OpenAlexfundaboutno aff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNatural Resources CanadaOffice of Energy Research and DevelopmentGovernment of Canada
KeywordsElectrificationWaste heatBoiler (water heating)ElectricityWaste heat recovery unitHeat pumpFossil fuelNatural gasCoal

Abstract

fetched live from OpenAlex

Industrial electrification is an important step on achieving net-zero in industry. For several industrial subsectors in Canada, a significant portion of the energy input is consumed in fossil fuel boilers. An interesting solution is the replacement of the boiler with a high temperature heat pump (HTHP) capable of delivering the required process heat. The efficiency of a HTHP being closely dependent on the waste heat temperature levels, this effect is also studied. The results show that electrification of boilers by HTHPs being supplied with waste heat at 29°C leads to energy savings of 11%, 14% and 38% in the petroleum refining, pulp and paper and food and beverage subsectors respectively. These numbers can significantly increase when part of the heat can be obtained through heat recovery alone and/or heat pumping from higher-temperature waste heat, which is expected to always be the case, although in proportions that are site-specific. One challenge in making HTHP projects cost-effective is the higher electricity cost compared to fossil fuels. This issue is partly addressed through carbon pricing mechanisms and a high coefficient of performance (COP).

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.032
GPT teacher head0.255
Teacher spread0.224 · 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
GenreOther

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
Published2025
Admission routes2
Has abstractyes

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