Vibration-Based Techniques for Measuring the Elastic Properties of Ropes and the Added Mass of Submerged Objects
Bibliographic record
Abstract
The magnitude of peak tensions during the deployment of subsurface moorings is dependent on the elastic stretch of the mooring line and the added masses of the mooring buoyancy and instruments. Measured transient tensions, which are twice the mooring anchor weight, highlight the importance of being able to quantify these critical parameters so that these dynamic tensions can be predicted. In this paper, the theory of the mass-spring oscillator is applied in two simple experiments to demonstrate practical techniques for measuring the elastic properties of ropes and the added mass of submerged objects. In the first procedure, a known mass is suspended from a rope, and the tension is monitored when the “mass-spring” system is set into free longitudinal oscillation. The spring constant is calculated from the measured frequency of this oscillation. Trials with ¼" diameter synthetic and wire ropes demonstrate that satisfactory results are attainable with rope lengths of less than 2 m. Results using different rope lengths vary by less than 1%. The method is shown also to provide a means of measuring the internal friction of ropes using the rate of vibration decay. In a second experiment, the added mass of a sphere is determined by monitoring the line tension during the deployment of a subsurface oceanographic mooring that consists of a spherical float and a mooring line of known spring constant. The frequency of the observed oscillation in the tension record just after anchor impact is used to compute the added mass of the sphere. The value obtained is consistent with determinations made by other methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".