STOCHASTIC SIMULATIONS AS A BENCHMARK FOR MATHEMATICAL-METHODS SOLVING THE COALESCENCE EQUATION

Common mathematical methods for the treatment of droplet coalescence a ttempt to approximate the coalescence equation in various manners. Som e of these methods may yield different results when applied to realist ic coalescence processes with complicated kernels. Thus, independent a ccuracy checks are desired. In this paper a modification of Gillespie' s stochastic simulation algorithm is presented which yields reliable r esults at the price of an extensive CPU-time consumption. This algorit hm is recommended to perform benchmark calculations to test the qualit y of faster methods for the numerical approximation of the coalescence equation. As examples for these approximation techniques a slightly m odified discrete method of Kovetz and Olund and the integration scheme of Berry and Reinhardt are examined. Simulations carried out by the s tochastic algorithm reveal that the integration scheme of Berry and Re inhardt is more accurate than the discrete method.