Hello,
I am currently conducting EDEM simulations involving very small particles. Given the high computational cost, scaling up the particle size is an essential step in my workflow to maintain simulation efficiency.
As many of you are aware, increasing the particle size in EDEM often leads to discrepancies between the simulated results and actual physical behavior. I am looking for an AI-driven tool or methodology compatible with EDEM to bridge this gap. Specifically:
- Automated Calibration: Are there AI or machine learning tools that can automatically optimize EDEM's physical coefficients (e.g., static/rolling friction, coefficient of restitution) for a scaled-up model so that it accurately reflects the real-world bulk behavior?
- Predictive Modeling: Is there an AI solution capable of taking EDEM's large-scale simulation data and predicting how the system would behave at its original, smaller scale?
If such tools exist—whether integrated within EDEM or as a third-party plugin—I would greatly appreciate information on how to access and implement them in my research.
Thank you in advance for your insights!
