Band gap generation in cantilever beams through periodic material removal
Bibliographic record
Abstract
Traditional methods for generating band gaps in beams usually involve adding periodic elements like tuned mass dampers or masses, or applying complex geometrical changes. This research suggests a subtraction-based method achieved by removing material in the thickness direction through straightforward machining operations, thus forming periodic cells. The numerical studies start with band gap analysis, using periodic theory to assess different periodic cell configurations. This is followed by numerical and experimental studies on cantilever beams, each containing a set number of these periodic cells. Non-contact vibration measurements are conducted on one plain and six machined aluminum beams using a multipoint laser vibrometer and an automated impact hammer. The experimental findings corroborate the band gaps predicted by the numerical model, confirming the effectiveness of this approach. The study notes that the optimal periodicity of the cells and the contrast in thickness vary with the beam’s dimensions, and that the thickness contrast markedly affects the quantity, width, and intensity of the resulting band gaps. These results indicate that (1) periodic material removal in beam-like structures allows improved vibration reduction while mass is reduced, and (2) manufacturing can play a key role in vibration control in simple structures.
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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 | 0.000 | 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 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".