Maximum spreading of droplet-particle collision covering a low Weber number regime and data-driven prediction model

In the present study, maximum spreading diameter of a droplet impacting with spherical particle is numerically studied for wide range impact conditions: Weber number (We) 0–110, Ohnesorge (Oh) 0.001 3–0.786 9, equilibrium contact angle ( ? eqi ) 20°–160°, and droplet-to-particle size ratio (?) 1/10–1/2. A total 2600 collision cases are simulated to enable systematic analysis prepare large dataset training data-driven prediction model. The effects four parameters (We, Oh, , ?) on ? * max comprehensively analyzed, particular attention paid difference between low high regimes. universal model as function We, ?, also proposed based deep neural network. It shown that our can predict well, showing an excellent agreement existing experimental results well simulation within deviation ±10%.