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Record W2890815328 · doi:10.1002/ente.201800164

Energy Savings Potential of a Novel Radiative Cooling and Solar Thermal Collection Concept in Buildings for Various World Climates

2018· article· en· W2890815328 on OpenAlexaboutno aff
Sergi Vall, Albert Castell, Marc Medrano

Bibliographic record

VenueEnergy Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsnot available
FundersGeneralitat de Catalunya
KeywordsRadiative coolingRadiative transferCommon emitterEnvironmental scienceTemperate climateMeteorologySolar energyGreenhouse gasArchitectural engineeringEngineering physicsEngineeringGeographyPhysicsGeologyOpticsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract A novel radiative cooling and solar collection concept is presented, and the combination of these two technologies and its energy integration in residential and commercial buildings is evaluated. This innovative concept, herein named Radiative Collector and Emitter (RCE), allows for supplying both cooling and Domestic Hot Water (DHW) demands. First, the RCE concept is introduced by presenting its background, with special attention to the overlapping and switching between radiative cooling and solar thermal collection. Then the DHW and cooling demands for four building typologies, two residential and two commercial, are compared with the energy production of the RCE. The analysis is performed for representative cities of the world climates according to Köppen‐Geiger classification. The RCE concept showed suitability in some of the studied cities (San Francisco, Cape Town, Johannesburg, London, and Ottawa) with C (temperate) and D (continental) climates in residential and tertiary buildings.

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 score0.004

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 head0.005
GPT teacher head0.206
Teacher spread0.200 · 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

Citations30
Published2018
Admission routes1
Has abstractyes

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