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A particle number conserving L agrangian method for mixing‐driven reactive transport
Author(s) -
Bolster Diogo,
Paster Amir,
Benson David A.
Publication year - 2016
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr018310
Subject(s) - particle (ecology) , lagrangian , probabilistic logic , particle number , tracking (education) , reduction (mathematics) , collision , resolution (logic) , process (computing) , mixing (physics) , fraction (chemistry) , lagrangian particle tracking , mechanics , statistical physics , physics , mathematics , mathematical optimization , computer science , chemistry , statistics , chromatography , thermodynamics , geometry , quantum mechanics , geology , artificial intelligence , pedagogy , computer security , oceanography , volume (thermodynamics) , operating system , psychology
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.