Evaluation criteria of the constitutive law formulation for the metal-cutting process
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modelling of the cutting process is necessary to predict cutting forces, residual stresses, and burr formation. A major difficulty in this modelling process is the description of the material behaviour in the primary and the secondary deformation zones, which is characterized by severe plastic deformation at high temperatures and strain rates. The description of the material behaviour requires correct formulation of the constitutive law. Although a number of formulations have been proposed to capture the flow stress behaviour, the assessment of these formulations for the cutting process is still a very difficult task owing to the lack of direct measurements of the high strains, strain rates, and temperatures encountered in the cutting process. This paper presents novel evaluation criteria to assess the degree of accuracy of the constitutive equation under machining conditions. Different existing constitutive laws are identified for Inconel 718, and then evaluated using the proposed criteria. To better describe the plastic behaviour of Inconel 718, new constitutive relationships are formulated and evaluated. From the evaluation results, an accurate description of the constitutive relationship for Inconel 718 is established. This constitutive law is further validated using high-speed split Hopkinson pressure bar (SHPB) tests and orthogonal cutting tests in conjunction with finite element simulations.
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.
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 | 0.002 | 0.002 |
| 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 | 0.001 | 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 it