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Record W2905836283 · doi:10.13044/j.sdewes.d6.0255

Building Integrating Phase Change Materials: A Dynamic Hygrothermal Simulation Model for System Analysis

2019· article· en· W2905836283 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.

Bibliographic record

VenueJournal of Sustainable Development of Energy Water and Environment Systems · 2019
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhase changePhase-change materialPhase (matter)Computer scienceMaterials scienceSystems engineeringEngineeringEngineering physicsPhysics

Abstract

fetched live from OpenAlex

Phase change materials are considered a very promising technology to reduce energy consumption for space heating and cooling purposes in buildings. In this framework, this paper presents a comprehensive energy performance analysis of building envelopes integrating phase change materials to provide suitable selection and design criteria of such technology. To this aim, an in-house dynamic simulation model implemented in a computer code, and validated by means of experimental data, has been used. The performance of phase change materials embedded in building enclosures and their optimal configuration (i.e., positions with respect to the construction layers) are evaluated. The results obtained by applying the code to suitable case studies (several climate zones and buildings are investigated) return that the energy saving percentage potentials per cubic meter of phase change materials range from 1.9%/m 3 to 18.8%/m 3 . Finally, interesting design criteria for their adoption in buildings are provided.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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