Signature of coupling of potentials in non-linear energy harvesters with enhanced figure of merit
Bibliographic record
Abstract
This paper reports electromagnetically transduced multistable non-linear vibrational energy harvesters to exploit the combined dynamical effects of monostable and bistable non-linear potential energies in a single system, by utilizing the stretching of specially designed cascaded tapered spring topology along with repulsive magnetic levitation. Using comprehensive (analytical and numerical) simulations and experimental validations, we reveal the signature of coupling and its key characteristics present in multimodal non-linear wideband energy harvesters. Here, a dynamical root-tracking technique is employed to trace stable, unstable, and hidden solution branches systematically, which enables predictive configuring of physical experimental parameters to realize previously inaccessible high response dynamical regimes along with a higher normalized power integral density metric. Thus, by tuning the powerful interplay between the numerical continuation framework and available physical parameters, we offer a robust technique for optimizing design and output performances in all such types of energy harvesting systems (independent of the scale and transduction) for their enhanced figure of merit.
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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".