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Record W7000061734

Dynamic Modelling of Building Envelope on Energy Usage

2021· article· en· W7000061734 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsBuilding envelopeEnvelope (radar)Building scienceSoftwareThermal massThermalEnergy (signal processing)Heat transferBuilding modelBoundary (topology)
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the influence of the building envelope on the energy usage of a chosen building using the simulation program TRNSYS. The building located at Carleton University, Ottawa, Canada is a small building retroffited as part of the Natural Resources Canada’s Prefabricated Exterior Energy Retrofit (PEER) project. The project's aim is to develop prefabricated technologies to be used for retroffiting existing building envelopes of homes in Canada. The thermal resistance (RSI) of the existing walls were improved from 1.80 m2K/W to about 6.40 m2K/W after installation of the prefarbricated retrofit wall system. Analytical verification of the whole building performance simulation software is performed using a solitary heat transfer mechanism under simplified boundary conditions with known analytical solution. The warm-up period necessary to ensure heat is distributed in the building thermal mass at the start of the simulation is quantified. The thermal performance of the whole building envelope is quantified using the time-lag effect and decrement factor and energy requirement for heating and cooling.

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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.016
GPT teacher head0.185
Teacher spread0.170 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueScholarship at UWindsor (University of Windsor)→Same topicBuilding Energy and Comfort Optimization→French-language works237,207→