Energy Distribution and Working Characteristics of PIPVT Dual-Energy Module
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".