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Record W4385454490 · doi:10.32920/23811243

Applications of Active Hollow Core Slabs and Insulated Concrete Foam Walls as Thermal Storage in Cold Climate Residential Buildings

2023· preprint· en· W4385454490 on OpenAlexafffund
Navid Ekrami, Raghad Sabah Kamel, Anais Garat, Afarin Amirirad, Alan S. Fung

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsBuilding-integrated photovoltaicsSlabThermalThermal energy storageFluentThermal comfortEnvironmental scienceStructural engineeringPhotovoltaic systemNuclear engineeringMechanical engineeringMaterials scienceEngineeringComputational fluid dynamicsAerospace engineeringMeteorologyElectrical engineering

Abstract

fetched live from OpenAlex

A test facility is designed and is under construction to experimentally verify the effect of thermal energy storage systems in overall performance of a coupled Building Integrated PhotoVoltaic / Thermal (BIPV/T) and Air Source Heat Pump (ASHP). This study shows how the loads for the test facility were adjusted by a regular size single family residential building. Moreover, the article explains different unique options of storing thermal energy in the test facility using the thermal mass of the building itself. Numerical models of Insulated Concrete Form (ICF) wall and Ventilated Concrete Slab (VCS) were developed using SolidWorks software’ Flow Simulation module and ANSYS Fluent software.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.244
Teacher spread0.228 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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