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Record W2782909448 · doi:10.1115/imece2017-72177

Thermal Energy Recovery From Small Sewage Treatment Plants in Northern Canadian Communities

2017· article· en· W2782909448 on OpenAlexaffabout
Xili Duan, Isa R. Haque, Aloysius Ducey

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEnvironmental scienceHeat pumpSewageThermal energyEnvironmental engineeringWaste heatHeat transferWaste managementNuclear engineeringProcess engineeringMechanical engineeringEngineeringThermodynamicsHeat exchangerPhysics

Abstract

fetched live from OpenAlex

This paper presents feasibility study and concept design of a thermal energy recovery system with an adsorption heat pump integrated with a small sewage treatment plant in northern Newfoundland communities. Treated fluids from the sewage treatment systems are quite warm even in winter. For example measured fluids temperature is averaged at 17 °C when air temperature is at −10 °C in the town of Whitbourne. This provides an attractive heat source particularly for winter seasons. Four heat pump concepts, i.e., vapour compression, absorption, adsorption and chemical heat pumps, were reviewed and compared. The results show that the adsorption system best fits the sewage treatment plants with minimum power requirements. Thermal fluidic parameters of the key components were designed with fluid flow and heat transfer analysis. A brief economic and environmental analysis showed that the integrated energy recovery unit would lead to a net reduction of CO2 emission and feasible payback time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.347

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 head0.025
GPT teacher head0.193
Teacher spread0.168 · 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 designObservational
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

Citations1
Published2017
Admission routes2
Has abstractyes

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