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Record W3210427794 · doi:10.3390/heritage4040215

Energy Efficiency Measures Applied to Heritage Retrofit Buildings: A Simulated Student Housing Case Study in Vienna

2021· article· en· W3210427794 on OpenAlexaff
Essam Elnagar, Simran Munde, Vincent Lemort

Bibliographic record

VenueHeritage · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRetrofittingArchitectural engineeringBuilding envelopePavilionRoofEfficient energy useEnergy engineeringCivil engineeringRenewable energyEnergy consumptionEngineeringTRNSYSEnergy (signal processing)GeographyStructural engineeringMeteorology

Abstract

fetched live from OpenAlex

One pavilion was selected for deep retrofitting from the Otto Wagner area situated in the west of Vienna. The retrofitting process involves sustainable and energy-efficient construction to improve the energy performance and energy production potential of the building while preserving the cultural heritage and significance. This four-story pavilion was re-designed according to the proposed regulations of a net positive energy university building to become a student residence. Architectural, building envelope, and engineering interventions along with various changes were simulated through the Sefaira tool in the SketchUp model. These included: optimization of the U-values of the roof, walls, and floor; the addition of different layers of sustainable energy-efficient insulation materials to decrease the overall energy demand. The specific energy demands for heating, cooling, and lighting were decreased in the proposed model to reduce the total energy use intensity from 248.9 kWh/(m2 year) to 54.3 kWh/(m2 year) resulting in a 78.2% reduction. The main goal of this study is to try and achieve a net positive energy status building as part of the Otto Wagner area by improving the building envelope and integrating renewable energies. A total of 22.5% of the annual energy consumption was generated by the designed PV system. The selected building achieved the passive house standards in Austria by optimizing the energy performance with the proposed energy efficiency measures.

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)
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 score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.239
Teacher spread0.226 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

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