The Use of Photovoltaic Solar Panels to Reduce Temperature-Induced Bridge Deformations
Bibliographic record
Abstract
Abstract Civil infrastructure such as bridges undergo deformations such as displacement and strain due to environmental temperature variations. Temperature causes deformations equal to or larger than that due to traffic load on bridges. This research evaluates whether the deformations due to temperature load on bridges can be minimised by incorporating photovoltaic solar panels on the bridge surface. The panels can be attached to the bridge truss, piers, and the periphery of the deck excluding the pavement, i.e., excluding bridge superstructure elements under direct traffic load to avoid wear and tear of the solar panels. The hypothesis is that solar panels will generate electricity from solar radiation and the bridge elements underneath the panels will experience less temperature load. The truss will experience smaller deformations and thereby increasing its lifespan. This hypothesis is tested with a laboratory experiment on a bridge truss. A combination of solar panels is attached to the surface of an Aluminium truss. The truss is subjected to 1-h heating and cooling cycles created using infrared lamps. The truss is monitored with linear variable differential transformers and thermocouples. Displacements and surface temperature of the truss are recorded. Results have shown a 34.0% reduction in displacement due to the installation of solar panels. The temperature of the truss has been also reduced by 15–25.6%. This research shows the benefit of integrating renewable energy means in infrastructure such as bridges to reduce temperature-induced structural deformations. Such integration can enhance the bridge lifespan along with generating green energy to electrify the bridge or the local area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".