Crashing analysis and multi-objective optimisation of duplex energy-absorbing structure for subway vehicle
Why this work is in the frame
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Bibliographic record
Abstract
The emphasis of the study is to investigate the impact performance of the duplex energy-absorbing structure through experiments and numerical simulations. First, a finite element (FE) model of the energy-absorbing structure was established and validated by corresponding experiments. Based on the validated FE model, the effects of the strength of honeycomb on the impact performance of the energy-absorbing structure were evaluated. The results showed that the initial peak force and the average impact force increase with the increasing strength of honeycomb, and the energy absorption also follows the same trend in a certain range of combined strength. Then, to optimise the crashworthiness of the energy-absorbing structure, the multi-objective optimisation, the non-dominated sorting genetic algorithm (NSGA-II) and the polynomial response surface method were adopted, The optima were given in the form of Pareto fronts and the most satisfactory solution was determined by the minimum distance between ‘utopia point’ and knee point. The results showed that whether the best optima can be obtained has nothing to do with the accuracy of the surrogate models. And the structure possesses the best crash performance (EA = 200.8 kJ, Fp = 903.2 kN) when the strengths of honeycombs A and B are 5.23 and 4.00 MPa, respectively.
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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