Virtualios apatinės valdymo svirties statinė analizė nustatant poslinkius, įtempius ir deformacijas
Bibliographic record
Abstract
Straipsnyje pateikiami virtualios apatinės valdymo svirties modaliniame vaizde, naudojant Craig Brampton CMS Altair‘s Optistruct metodą ir tokiu būdu sukurtas jos lankstus korpusas. Sukurti lankstūs kūnai turi 39 režimus ir susijusius dažnius. Dviguba pakabos pakabos sistema yra iš „Motion View“ bibliotekos pakeitus tvirtas apatines valdymo svirtis lanksčiomis apatinėmis valdymo svirtimis. Nustatyta galutinė sąranka atlikti statinės važiavimo analizę virtualioje bandymo platformoje, kuri 100 mm pasislenka į priekį ir grįžta, siekiant nustatyti įtempius, deformacijas ir poslinkius. Gauti rezultatai parodė, kad spyruoklėje maksimalūs įtempiai ir deformacijos, spyruoklinės sijos sąsaja ir maksimalūs poslinkiai buvo mazguose. Virtualiam prototipų sudarymui nereikia daugelio fizinių prototipų kūrimo, o visus reikalingus bandymų rezultatus kompiuteryje galima gauti efektyviau ir greičiau, kad būtų užtikrinta mašinos, operatorių ir darbo vietos saugumas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.016 |
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 source (direct Gemma or distilled Codex), 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".