MétaCan
Menu
Back to cohort
Record W1968877095 · doi:10.1177/0957650912460182

Investigation of a hybrid renewable– microgeneration energy system for power and thermal generation with reduced emissions

2012· article· en· W1968877095 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Thermodynamic Systems and Engines
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsCogenerationRenewable energyStirling engineNatural gasEnvironmental scienceHybrid systemGreenhouse gasProcess engineeringFossil fuelAutomotive engineeringThermalWaste managementElectricity generationEnvironmental engineeringEngineeringPower (physics)Computer scienceMechanical engineeringElectrical engineeringMeteorologyThermodynamics

Abstract

fetched live from OpenAlex

A conceptual study is described into the hybridization of Stirling engine-based residential cogeneration systems with solar thermal systems. Simulation results of four hybrid system configurations applied in various locations in Canada are presented and compared to Base Case systems without solar input. Additional optimization cases are discussed. Adding solar collectors to a residential cogeneration system has a clear potential to reduce natural gas consumption and greenhouse gas emissions. The simulated cases showed a 10%–15% decrease in the consumption of natural gas, which corresponds to a greenhouse gas emission reduction of approximately 700–1200 kg/house/year (depending on configuration and location). Hybrid systems are complex and highly integrated systems. A full system optimization was therefore not possible in this study. Recommendations are given for further optimization of this type of systems.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.384

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 head0.010
GPT teacher head0.187
Teacher spread0.178 · 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