Spiral Tool Path Planning Using Eccentric Parameters
Bibliographic record
Abstract
Free-form surfaces can be machined continuously with minimum tool retractions and at the high speed by following a spiral tool path. This paper presents an improved planning method of the spiral tool path using eccentric parameters for machining free-form surfaces. The relationship between a 3D machined surface and the 2D circular region is established through the conformal mapping. In order to generate an even path, eccentric parameters are used in 2D parametric circular regions to optimize the path interval. The proposed method produces planar spiral segments as a diagonal curve between every two adjacent parametric tool paths. A 2D spiral tool path is gained by linking spiral segments in sequence. Inverse mapping of the 2D spiral tool path onto the machined surface generates the 3D spiral tool path. The main processes of the proposed method include reducing dimensions of free-form surfaces, calculating the eccentric parametric tool path, and generating the planar diagonal spiral tool path. Some applications are used to verify the proposed methods. The proposed method allows the start point to be arbitrary and generates more even tool paths than the existing methods by introducing the mapping distortion.
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.
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".