Analytical models for machine tool motion behavior assessment bench mark subjected to great earthquake
Bibliographic record
Abstract
Three large earthquakes hit japan in the last few years continuously. It affected country's economy and hard to recover specially the manufacturing sector. For avoiding such impacts in the future, lessons were studied and actions were taken. This study therefore was conducted to assess the basic minimum machine tool motion behavior criteria by utilizing the existing seismic data. Particularly, the japan real earthquake data (The 2004 chetsu and the great hanshin earthquakes as well as the 2011 Thoku earthquake) and mathematical models that mimic the movement of machine tools with screw jack mounting during seismic occurrence were considered and developed. For the validity, both mathematical analysis and experimental performances of a previously developed small mock-up structure of a machine tool were conducted. The study concludes that (1) the possible motion behavior of a machine tool was able to be defined and calculated; (2) using the existing real seismic data able to predict the motion behaviour of a machine tool; and (3) it was observed that up-to approximately 60 % accuracy obtained when using the real earthquake data and the developed mathematical models for analysing machine tool motion behavior.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".