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Record W2334933696 · doi:10.1139/tcsme-2013-0040

A MODIFIED Z-MAP COMPUTATIONAL INTERPOLATION ALGORITHM FOR SURFACE MACHINING SIMULATION

2013· article· en· W2334933696 on OpenAlexvenueno aff
Jo‐Peng Tsai

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMachiningAlgorithmInterpolation (computer graphics)ComputationComputer scienceSurface (topology)Boundary (topology)Tool pathMathematicsGeometryEngineeringMechanical engineeringComputer visionMathematical analysis

Abstract

fetched live from OpenAlex

The Z-Map algorithm is one of the most simplistic methods for NC code simulation in obtaining the machined working surface information; therefore, it is often being applied in NC simulation. In this paper, a modified Z-Map computational algorithm was proposed to calculate mesh position and Z coordinates of tool scanning surface according to tool path and initial tool scanning boundary in reducing the long computation time. The proposed algorithm not only can be used to derive straight line and arc machining tool path, but also can be adopted for helical and spline curves. There is no need to simplify the non-linear curves beforehand. The method proposed in this paper provides a feasible reference for decision about the reliability and suitability of each machining step.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.010
GPT teacher head0.230
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicAdvanced Numerical Analysis TechniquesFrench-language works237,207