A Simulation Platform for Combined Rail/Road Transport in Multiyards Intermodal Terminals
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
With the rapid development of multiyards railway intermodal terminal (MYRIT) construction in China, performance evaluation has become an important issue for terminal design and management departments. Due to the complexity of the multiyards terminal and the associated rail network, the train moving process and related terminal operations have become more complicated compared with the traditional intermodal container terminal. However, in general simulation platforms, the train moving process is simplified and train route scheduling rules are not considered in existing simulation models. In order to provide an accurate and comprehensive quantitative evaluation tool for MYRIT, a simulation platform based on the Timed Petri Net model has been developed, which can offer decision support for terminal design and management departments. In this platform, a yards and facilities layout module has been created to give simulation users access to designing the railway network on this platform. And a train route dispatching simulation method has been integrated to provide an accurate simulation of the train moving process. Based on a real case of Qianchang railway intermodal terminal that is located in Fujian Province, China, the platform is thoroughly validated against historical data. And the test scenarios show that train routes arrangement and handling equipment configuration both have a significant influence on overall terminal performance, which need to be carefully considered during terminal design and management.
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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