MétaCan
Menu
Back to cohort
Record W2189130328 · doi:10.1139/tcsme-2009-0006

DISTRICT HEATING SYSTEM DESIGN FOR RURAL NOVA SCOTIAN COMMUNITIES USING BUILDING SIMULATION AND ENERGY USAGE DATABASES

2009· article· en· W2189130328 on OpenAlexaffvenueabout
Jaspreet S. Nijjar, Alan S. Fung, Larry Hughes, Hessam Taherian

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsDalhousie UniversityToronto Metropolitan UniversityHydro One (Canada)
Fundersnot available
KeywordsHeating systemNova scotiaEnvironmental scienceEnergy systemDatabaseGreenhouse gasArchetypeEnergy (signal processing)Architectural engineeringNova (rocket)Civil engineeringComputer scienceEngineeringGeographyMechanical engineeringArchaeology

Abstract

fetched live from OpenAlex

There are several benefits to district heating systems. The system design requires knowledge of community peak heating load and annual heating energy requirements. For this purpose, a residential energy model was developed using several energy usage databases. Hourly, peak, and annual heating demands were estimated by simulating 15 archetype houses using an hour-by-hour building simulation program, ENERPASS. Estimated heating profiles from model houses were used to design a district heating system for a hypothetical rural community in Nova Scotia. The findings show that building simulation is a very flexible and valuable tool in identifying the required peak and hourly energy demand of a community for the design of district energy system, and biomass district heating system can reduce community greenhouse gas emissions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.608
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.237
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), 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

Citations18
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicIntegrated Energy Systems OptimizationFrench-language works237,207