Optimization of a roller coaster bogie considering fatigue life
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
This study explores the effectiveness of fatigue-life constrained topology optimization in roller coaster engineering, a previously unexplored field. Emphasizing the importance of fatigue life considerations, the research focuses on key components of roller coasters: the wheel assemblies. By integrating stress–life fatigue constraints, such an approach can lead to longer lasting and more efficiently designed roller coaster components. Multiaxial fatigue topology optimization using the method of moving asymptotes gradient-based optimization is examined to address the complex loading experienced by these bogies given a substantial load-time history in the high-cycle fatigue region. Using a validated optimization methodology, this study aims to reduce the bogie volume in selected domains while ensuring structural integrity and potentially extending service life. The optimization process successfully reduces the number of designable elements, resulting in decreased global volume and mass, and the results quantifiably demonstrate the impact of applying high-cycle fatigue constraints on the bogie’s performance.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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