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Record W4403649665 · doi:10.3390/su16219151

Energy Distribution and Working Characteristics of PIPVT Dual-Energy Module

2024· article· en· W4403649665 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

VenueSustainability · 2024
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of Ottawa
FundersChang'an University
KeywordsDual (grammatical number)Energy (signal processing)Distribution (mathematics)Energy distributionEnvironmental sciencePhysicsMathematicsAtomic physicsArtMathematical analysis

Abstract

fetched live from OpenAlex

The pavement integrated photovoltaic/thermal (PIPVT) system can comprehensively use solar energy to generate electricity and heat, which is an effective way to use new energy. In this study, we couple heat conduction and convection from the Optics, Electrics, and Solids Modules in the COMSOL Multiphysics Module to build a PIPVT element model to fully understand the energy distribution within the dual-energy module. The simulation results show that when circulating water is introduced into the photovoltaic panels, the temperature on the back of the photovoltaic panels is reduced by 30 °C, and the temperature of the entire dual-energy module board is reduced by 10–15 °C. The introduction of a thermal collector module (T module) can effectively dissipate heat to extend the life of PV modules, and also improve their work efficiency. PIPVT’s solar energy utilization rate is 39.4%, which is a significant improvement compared to the 14.3% solar energy utilization rate of the photovoltaic module (PV module) alone and the 18.7% solar energy utilization rate of the T module. It shows that the dual-energy module has a synergistic effect.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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