Streamlined numerical modeling of solid particle impacts and erosion using a fully eulerian technique: An experimentally validated comparison to Lagrangian and meshfree methods
Bibliographic record
Abstract
Solid particle erosion modeling is a highly demanding task that, despite the enormous growth in global computing power in recent decades, often requires significant time and geometric scaling compared to real-world phenomena to achieve reasonable execution times. This study considered the simulation of solid angular particle impacts against AA6061-T6 and oxygen free high conductivity (OFHC) copper targets, and multi-particle erosion by 150 μm diameter alumina powder in AA6061-T6, using conventional Lagrangian finite element method (FEM), smoothed particle hydrodynamics (SPH) and fully Eulerian models. The simulations were compared based on their computational efficiency and validated using published experimental data from Papini's research group. The Eulerian models predicted crater profiles and rebound kinematics for planar impacts, up to 88 m/s, with a 12.1 % average relative error compared to 15.9 % and 21.3 % for the SPH and FEM models, respectively. The Eulerian models also accurately predicted surface chipping despite the omission of a material failure algorithm. For the multi-particle simulations, crater size and volume distributions from 372 randomized impacts and steady-state erosion rates imparted by 1.5 g/min, 117 m/s incident alumina powder jets were predicted within 15 % of experimental values for the Eulerian and SPH models. The execution times were, on average, 2.2 times faster for the Eulerian models than the complementary SPH models and 6.5 times faster than conventional FEM. These findings highlight opportunities for the development of numerical models of erosion phenomena with more realistic physical domains, and greater accessibility to professionals with limited computational resources.
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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".