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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 OpenAlexaff
Cesare Forzano, Paolo Baggio, Annamaria Buonomano, Adolfo Palombo

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.

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: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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

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

Citations25
Published2019
Admission routes1
Has abstractyes

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Same venueJournal of Sustainable Development of Energy Water and Environment SystemsSame topicPhase Change Materials ResearchFrench-language works237,207