The Experts below are selected from a list of 188832 Experts worldwide ranked by ideXlab platform

Lu Zhiming - One of the best experts on this subject based on the ideXlab platform.

  • Bivariate Taylor-series expansion Method of Moment for particle population balance equation in Brownian Coagulation
    Journal of Aerosol Science, 2017
    Co-Authors: Jiang Zhi, Shen Jie, Lu Zhiming
    Abstract:

    Abstract In this study, we extend the Taylor-series expansion Method of Moment to two-component aggregation problem undergoing Brownian coagulation with kernels that are independent of composition. A set of closed particle population balance equation for lower-order Moments is then derived. Numerical results and its asymptotic solutions are validated by comparing with Monte Carlo simulation Method both in free molecular regime and continuum regime. It is shown that three dimensionless particle Moments M C 1 , M C 2 , M C 3 almost approach to a same value over large evolution time. The normalized variance of excess component A decreases as 1 / v ¯ and it tends to zero over large evolution time.

Martin Seipenbusch - One of the best experts on this subject based on the ideXlab platform.

Jiang Zhi - One of the best experts on this subject based on the ideXlab platform.

  • Bivariate Taylor-series expansion Method of Moment for particle population balance equation in Brownian Coagulation
    Journal of Aerosol Science, 2017
    Co-Authors: Jiang Zhi, Shen Jie, Lu Zhiming
    Abstract:

    Abstract In this study, we extend the Taylor-series expansion Method of Moment to two-component aggregation problem undergoing Brownian coagulation with kernels that are independent of composition. A set of closed particle population balance equation for lower-order Moments is then derived. Numerical results and its asymptotic solutions are validated by comparing with Monte Carlo simulation Method both in free molecular regime and continuum regime. It is shown that three dimensionless particle Moments M C 1 , M C 2 , M C 3 almost approach to a same value over large evolution time. The normalized variance of excess component A decreases as 1 / v ¯ and it tends to zero over large evolution time.

Xiaotong Zhang - One of the best experts on this subject based on the ideXlab platform.

Jyh-horng Chen - One of the best experts on this subject based on the ideXlab platform.