3D-printed torsional mechanism demonstrating fundamentals of free vibrations
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
Commercially available turn-key systems are expensive and require substantial lab space, making it harder to accommodate many in vibrations laboratories. This study presents a low-cost, compact, and portable torsional mechanism incorporating multiple rotating disks and a long thin rod supported vertically with bearings and fixed supports at the top and bottom ends to study the modeling of systems using experimental data. The mechanism consisting of a rod, disks, bearing, and disk supports, and the base is built by 3D printing using thermoplastic PETG. The long, thin rod in this mechanism serves as a torsional spring. The equivalent stiffnesses of the 2 DOF system can be changed by adjusting the vertical position of the disks with respect to the ends, thereby shortening or lengthening the effective twist length of the thin rod. The overall dimensions of the mechanism are 6 inches in height, 5 inches in width, and 2 inches in depth, and the expected cost including the experimental setup is around USD$30 if an Arduino is used for data acquisition and $170 if equipped with a National Instruments external data acquisition card. Learning objectives of the lab course utilizing the proposed mechanism are identified. The free response data are collected for a single degree-of-freedom system using an external data acquisition card and potentiometer and unknown parameters of the system are determined by system identification. Mechanism unknown parameters are calculated using system identification and a theoretical model is compared with the experimental data.
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