Numerical and Experimental Investigation of Ribbon Floating Bridges
Bibliographic record
Abstract
Floating bridges are temporary or permanent structures that utilize the buoyancy of water to resist loads imposed by traversing vehicles and can be used for emergency water crossings or during war.Due to the advent of heavier and faster vehicles, coupled with the dearth of analysis and design information on ribbon floating bridges, it is important to investigate the behaviour of these bridges under various vehicle crossing conditions.This study examines the dynamic behaviour and potential to increase the vehicle-crossing capacity of a hinge-connected ribbon floating bridge.A finite element program was developed to simulate the vertical displacement response of the floating bridge when subjected to single or multiple vehicles of varying weight, speed, and inter-vehicle spacing.A 1/25-scale experimental model was constructed to physically investigate bridge behaviour and to validate the developed finite element program for further parametric analyses.For two-vehicle crossings, the experimental and numerical results showed that the magnitude of the first peak vertical midpoint displacement of the ribbon floating bridge primarily depended on vehicle speed, with the displacement value equal to that caused by a single vehicle if the inter-vehicle spacing was greater than one-half the bridge length.The second peak depended on both vehicle speed and spacing and was influenced by the free vibration of the bridge after passage of the first vehicle.To study the relationship between maximum midpoint displacement and vehicle weight, a Speed Ratio was defined which relates the frequency of vehicle induced loads to the natural frequency of vibration of the floating bridge.The maximum midpoint
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".