On Local and Global Species Conservation Errors for Nonlinear Ecological Models and Chemical Reacting Flows

Advection-controlled and diffusion-controlled oscillatory chemical reactions appear in various areas of life sciences, hydrogeological systems, and contaminant transport. In this conference paper, we analyze whether the existing numerical formulations and commercial packages provide physically meaningful values for concentration of the chemical species for two popular oscillatory chemical kinetic schemes. The first one corresponds to the chlorine dioxide-iodine-malonic acid reaction while the second one is a simplified version of Belousov-Zhabotinsky reaction of a non-linear chemical oscillator. The governing equations for species balance are presented based on the theory of interacting continua. This results in a set of coupled non-linear partial differential equations. Obtaining analytical solutions is not practically viable. Moreover, it is well-known in literature that if the local dynamics becomes complex, the range of possible dynamic behavior in the presence of diffusion and advection becomes practically unlimited. We resort to numerical solutions, which are obtained using two popular stabilized formulations: Streamline Upwind/Petrov Galerkin and Galerkin/Least Squares. In order to make the computational analysis tractable, an estimate on the range of system-dependent parameters is obtained based on model reduction performed on the strong-form of the governing equations. Finally, we quantify the errors in satisfying the local and global species balance for various realistic benchmark problems. Through these representative numerical examples, we shall demonstrate the need and importance of developing locally conservative non-negative numerical formulations for chaotic and oscillatory chemically reacting systems.Copyright © 2015 by ASME

[1]  D. Sorensen,et al.  A Survey of Model Reduction Methods for Large-Scale Systems , 2000 .

[2]  Maruti Kumar Mudunuru,et al.  On mesh restrictions to satisfy comparison principles, maximum principles, and the non-negative constraint: Recent developments and new results , 2015, ArXiv.

[3]  J. Huisman,et al.  Biodiversity of plankton by species oscillations and chaos , 1999, Nature.

[4]  Valery Petrov,et al.  Controlling chaos in the Belousov—Zhabotinsky reaction , 1993, Nature.

[5]  W. D. Evans,et al.  PARTIAL DIFFERENTIAL EQUATIONS , 1941 .

[6]  R. M. Bowen Part I – Theory of Mixtures , 1976 .

[7]  M. Menzinger,et al.  The myth of the well-stirred CSTR in chemical instability experiments: the chlorite/iodide reaction , 1990 .

[8]  Volker John,et al.  On spurious oscillations at layers diminishing (SOLD) methods for convection–diffusion equations: Part I – A review , 2007 .

[9]  Zoltán Noszticzius,et al.  Hydrodynamic turbulence and diffusion-controlled reactions. Simulation of the effect of stirring on the oscillating Belousov-Zhabotinsky reaction with the radicalator model , 1991 .

[10]  Harsha Nagarajan,et al.  Enforcing the non‐negativity constraint and maximum principles for diffusion with decay on general computational grids , 2010, ArXiv.

[11]  Maruti Kumar Mudunuru,et al.  A numerical framework for diffusion-controlled bimolecular-reactive systems to enforce maximum principles and the non-negative constraint , 2012, J. Comput. Phys..

[12]  W. L. Wood Practical Time-Stepping Schemes , 1990 .

[13]  Nonlinearities in the gas phase chemistry of the troposphere: Oscillating concentrations in a simplified mechanism , 1996 .

[14]  Yoshiki Kuramoto,et al.  Chemical Oscillations, Waves, and Turbulence , 1984, Springer Series in Synergetics.

[15]  Dima Grigoriev,et al.  Detection of Hopf bifurcations in chemical reaction networks using convex coordinates , 2015, J. Comput. Phys..