Numerical modeling of rough contact interfaces with trapped compressive liquid pockets
Bibliographic record
Abstract
We introduce a novel numerical model that integrates a Boundary Element Method (BEM) code in Fourier space to solve the problem of lubricated frictional contact between rough surfaces. This model accounts for scenarios where the lubricant quantity is significant yet discontinuous, leading to the formation of trapped, compressible lubricant pockets at the contact interface. Additionally, it incorporates the plastic behavior of solid surfaces through a simple plastic saturation method, enabling comprehensive analysis of contact area, pressure distribution, and variations in the friction coefficient across a wide range of conditions, such as lubricant type, density, and surface roughness. Comparison with experimental strip-drawing tests shows that, despite its simplicity, the model successfully captures the observed trend of a decreasing friction coefficient with increasing normal pressure in a mixed-lubrication regime. Notably, the study reveals that when the amount of lubricant is insufficient to fully fill the interfacial gap, even minor adjustments in its distribution can significantly influence the friction behavior of aluminum during forming processes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".