A particle number conserving Lagrangian method for mixingdriven reactive transport

نویسندگان

  • Diogo Bolster
  • Amir Paster
  • David A. Benson
چکیده

The purely Lagrangian algorithm for chemical reactions introduced by Benson and Meerschaert (2008) suffers from a low-concentration resolution problem. We alleviate the problem by redefining the probabilistic collision/reaction (birth/death) stochastic process as a mass-reduction operation. Theoretically, this corresponds to replacing an on/off particle with a large number of ‘‘subparticles’’ and tracking the number fraction. The new particle reaction process maintains the original particle numbers but adjusts each particle’s mass upon reaction. Several simulations show the veracity as well as the gains in low-concentration resolution offered by the algorithm. We also compare the results to those obtained by a traditional finite difference model with suitably defined initial condition, demonstrating that the Lagrangian models match these.

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تاریخ انتشار 2016