Bibliographic record
Abstract
<p>Engineering understanding of interaction between the moving train, track and bridge is necessary to successfully design rail bridges. Besides non-linear static behaviour guided by UIC 774-3 leaflet a complex dynamics vibrations due to the train movement, centrifugal forces and imperfections occurs in the interaction structure which includes bridge, track and train. Checking of the passenger comfort criteria requires sophisticated dynamic numerical analysis including the modelling of train/track/bridge interaction.</p><p>In this paper the numerical simulation of dynamic interaction between the moving monorail train and the bridge frame for the new line known as Expresso Tiradentes, which will serve as an extension of the São Paulo Metro Line 2 in Brazil, is presented. Checking of passenger comfort criteria is executed for most critical straight and curved frame bridge on the line. Bombardier Transportation, train manufacture from Canada, is a designer of Monorail 300 system for this line.</p><p>As a first step the detailed 3d modelling of the train is done including the car bodies, bogies and guiding tires in typical 7 cars multi-body mechanical system. Damping and spring systems are taken into account in lateral, vertical and longitudinal directions. The passenger masses are taken into account in dynamics analysis. As different variants of the train exist, numerical simulation is repeated for several train configurations</p><p>In the second step the calibration of the train mechanical model is done; natural modes and frequencies of the train are compared and validated against references provided by Bombardier Transportation.</p><p>The bridge frames are modelled including superstructure and substructure in third step. Special care is given to the realistic modelling of the transverse behaviour as the train path is fully eccentric to the bridge centreline.</p><p>Finally, the full interaction between the train and bridge is modelled. The coupling between moving multi-body train and bridge is taken fully into account applying the novel procedure which is presented in this paper. Overview of numerical parameters and calibration procedure of the modelling of interaction are presented together with relevant results.</p>
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Numerical simulation of train-bridge dynamic interaction; civil engineering.
It models train-bridge dynamics for engineering design rather than studying research.
Dynamic train–bridge interaction modelling for a metro monorail; civil engineering.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".