An Integrated Virtual Validation System for Parallel Kinematic Machine Analysis Design
Bibliographic record
Abstract
Selecting a configuration for a machine tool that will best suit the needs of a forecast set of requirements can be a difficulty and costly exercise. This problem can now be addressed using an integrated virtual validation system. The system includes kinematic/dynamic analysis, kinetostatic model, CAD module, FEM module, CAM module, optimization module and visual environment for simulation and collision detection of the machining and deburring. It is an integration of the parallel kinematic machines (PKM) design, analysis, optimization and simulation. In this paper, the integrated virtual system is described in a detail, a prototype of a 3-dof PKM is modeled, analyzed, optimized and remote controlled with the proposed system. Some results and simulations are also given. Its effectiveness is shown with the results obtained by NRC-IMTI during the design of the 3-dof NRC PKM.
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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".