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
Aim of this article is to introduce and present advantages and possibilities of using simulation tools to calculate energy flows of tractive vehicle in all phases of its ride. The focus is on the braking phase, especially on the braking energy recuperation that offers the highest energy saving potential.Energetic simulation was carried out as a part of a current railway reconstruction study, which is a good example of possible energetic calculation use. Energetic calculation in the simulation are performed using so called "exact method" developed at the Faculty of Transportation. The advantage of the method is that it provides a high degree of accuracy. Due to the simulation calculation being performed in real-time, the user can enter the calculation even during the simulation. Crucial part ofevery simulation are quality input data, such as vehicle braking characteristic (including all working points below the envelope line together with the efficiency characteristics of the power train parts (engine, transmission, convertor and others)). Also, sufficiently precise (with a precision of 1 meter) railway track details (detailed geometrical and other information on the current and reconstructed railway track or on the railway track proposal.To present savings during the ride, the railway track section on the track Montreál-Sherbrooke was chosen. On this track, (especially electrification and partial reconstruction of the superstructure) is planned. Reconstruction level will be dependant on the local economical and social conditions. However, in the most optimistic case, total electrification of the track will be undertaken, or lower level of the reconstruction when the vehicles that have very similar characteristics. The railway track section is located between the cities of Montreál and Sherbrooke, that are 160 km apart. To compare the current, and possible future, state, comparison of energy consumption of the vehicle was conducted on the same track with the same geometrical characteristics.We can assume that the overall energy intensity of the ride on the newly reconstructed track (eg. with greater radius of the arches) will be lower than the overall energy intensity of the ride on the track before reconstruction. Current data on energetic consumption are not available, therefore they were obtained by simulation and verified by calculations and considered sufficiently accurate.Presumably, the input simulation parameters required for the simulation will not always be delivered in the sufficient quality or will be partly missing completely. In these cases they will be substituted by various algorithms, that can be machine-processed and that are part of the simulation calculations. One of the crucial algorithms is so called "moment efficiency". Its machine processingis not entirely developed and therefore, this simulation will be conducted without its usage. For financial reasons, simulation calculation was verified only by the theoretical physical calculation method. Based on several partial results, emergent computing tool is functional and sufficiently accurate. The simulation program is supposed to be experimentally verified after its finishing.The outcomes presented in this article are calculated by simulated computation and were not confronted with the real situation in any way. However, relevant calculation algorithms, processes and theoretical background of the simulation were already verified on the older software versions. Therefore, the simulated outcomes are supposed to be at least sufficiently accurate to provide preliminary study for the railway reconstruction. Presented calculations were executed by using author’s simulation software.Part of the methodology was taken from the previous, already verified, versions of the software for vehicle ride simulation.
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 | 0.001 |
| 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