Energy harvesting by piezo-tires and their life cycle assessment
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.
Bibliographic record
Abstract
Piezoelectric materials can convert mechanical energy into electrical energy. These materials have the potential to provide reliable and cost-effective replacements of energy sources. It can ultimately have the potential to reduce fuel costs in vehicles. The use of piezoelectric materials in pneumatic tires enables capturing the waste energy of cars because of deformations in tires. An experimental setup was designed and constructed to simulate the movement and pressure inside the tire of a car. Piezoelectric elements were attached to the external perimeter of the model tire. Based on the experimental results, this method produced 2.31 W for 56 piezo-elements comparable to 2.3 W for 160 piezo-elements found in the literature. The results showed that placing piezoelectric elements on the outer surface of tires has a higher potential in harvesting the waste energy in vehicle tires. The harvested energy has a direct relation with the compressive stress under the contact patch of the tire. In addition, the harvested energy increases by increasing the velocity and applied weight. In addition to the experimental study, the environmental effects of harvesting waste mechanical energy in tires by using piezoelectric materials bonded to tires were evaluated through a life cycle assessment. The results showed that in addition to harvesting some of the waste energy in cars, it contributes a slightly higher environmental load than ordinary tires. Further evaluation of the technology is required to measure the durability and the lifetime of piezoelectric materials.
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 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 | 0.000 | 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) | 0.000 | 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 it