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October  2021, 14(5): 847-866. doi: 10.3934/krm.2021026

A criterion for asymptotic preserving schemes of kinetic equations to be uniformly stationary preserving

1. 

Sorbonne University, UPMC Univ Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris, France

2. 

University of Würzburg, Germany

3. 

Department of Mathematics and Institute of Natural Sciences, Jiao Tong Univ., Shanghai, China

* Corresponding author: Farah Kanbar

Received  July 2020 Revised  May 2021 Published  October 2021 Early access  August 2021

Fund Project: The second author is supported by the National Council for Scientific Research of Lebanon (CNRS-L). The second and third authors are supported by Bayerisches Hochschulzentrum for China

In this work we are interested in the stationary preserving property of asymptotic preserving (AP) schemes for kinetic models. We introduce a criterion for AP schemes for kinetic equations to be uniformly stationary preserving (SP). Our key observation is that as long as the Maxwellian of the distribution function can be updated explicitly, such AP schemes are also SP. To illustrate our observation, three different AP schemes for three different kinetic models are considered. Their SP property is proved analytically and tested numerically, which confirms our observations.

Citation: Casimir Emako, Farah Kanbar, Christian Klingenberg, Min Tang. A criterion for asymptotic preserving schemes of kinetic equations to be uniformly stationary preserving. Kinetic & Related Models, 2021, 14 (5) : 847-866. doi: 10.3934/krm.2021026
References:
[1]

M. Adams, Discontinuous finite element transport solutions in thick diffusive problems, Nuclear Science and Engineering, 137 (2001), 298-333.  doi: 10.13182/NSE00-41.  Google Scholar

[2]

W. Alt, Biased random walk models for chemotaxis and related diffusion approximations, J. Math. Biol., 9 (1980), 147-177.  doi: 10.1007/BF00275919.  Google Scholar

[3]

S. Boscarino and L. Pareschi, On the asymptotic properties of IMEX Runge–Kutta schemes for hyperbolic balance laws, J. Comput. Appl. Math., 316 (2017), 60-73.  doi: 10.1016/j.cam.2016.08.027.  Google Scholar

[4]

R. Botchorishvili, B. Perthame and A. Vasseur, Equilibrium schemes for scalar conservation laws with stiff sources, Math. Comp., 72 (2003), 131–157 (electronic). doi: 10.1090/S0025-5718-01-01371-0.  Google Scholar

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J. A. Carrillo and B. Yan, An asymptotic preserving scheme for the diffusive limit of kinetic systems for chemotaxis, Multiscale Model. Simul., 11 (2013), 336-361.  doi: 10.1137/110851687.  Google Scholar

[6]

C. Cercignani, The Boltzmann equation and its applications, Springer, 1988. doi: 10.1007/978-1-4612-1039-9.  Google Scholar

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F. A. C. C. ChalubP. A. MarkowichB. Perthame and C. Schmeiser, Kinetic models for chemotaxis and their drift-diffusion limits, Monatsh. Math., 142 (2004), 123-141.  doi: 10.1007/s00605-004-0234-7.  Google Scholar

[8]

A. ChertockA. KurganovM. Lukáčová-Medvid'ová and S.N. Özcan, An asymptotic preserving scheme for kinetic chemotaxis models in two space dimensions, Kinet. Relat. Models, 12 (2019), 195-216.  doi: 10.3934/krm.2019009.  Google Scholar

[9]

G. Dimarco and L. Pareschi, Implicit-explicit linear multistep methods for stiff kinetic equations, SIAM J. Numer. Anal., 55 (2017), 664-690.  doi: 10.1137/16M1063824.  Google Scholar

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F. Filbet and S. Jin, A class of asymptotic-preserving schemes for kinetic equations and related problems with stiff sources, Journal of Computational Physics, 229 (2010), 7625-7648.  doi: 10.1016/j.jcp.2010.06.017.  Google Scholar

[11]

F. FilbetC. Mouhot and L. Pareschi, Solving the Boltzmann equation in $n\log_2n$, SIAM Journal of Scientific Computation, 28 (2006), 1029-1053.   Google Scholar

[12]

L. Gosse, A well-balanced scheme for kinetic models of chemotaxis derived from one-dimensional local forward-backward problems, Math. Biosci., 242 (2013), 117-128.  doi: 10.1016/j.mbs.2012.12.009.  Google Scholar

[13]

L. Gosse and G. Toscani, An asymptotic-preserving well-balanced scheme for the hyperbolic heat equations, C. R. Math. Acad. Sci. Paris, 334 (2002), 337-342.  doi: 10.1016/S1631-073X(02)02257-4.  Google Scholar

[14]

L. Gosse and G. Toscani, Space localization and well-balanced schemes for discrete kinetic models in diffusive regimes, SIAM J. Numer. Anal., 41 (2003), 641-658.  doi: 10.1137/S0036142901399392.  Google Scholar

[15]

L. Gosse and G. Toscani, Asymptotic-preserving & well-balanced schemes for radiative transfer and the rosseland approximation, Numer. Math., 98 (2004), 223-250.  doi: 10.1007/s00211-004-0533-x.  Google Scholar

[16]

S. Guisset, S. Brull, E. D'Humières and B. Dubroca, Asymptotic-preserving well-balanced scheme for the electronic $M_1$ model in the diffusive limit: Particular cases, ESAIM Math. Model. Numer. Anal., 51 (2017), 1805-1826. doi: 10.1051/m2an/2016079.  Google Scholar

[17]

B. Howard, E. Coli in Motion, Biological and Medical Physics, Biomedical Engineering, Springer, 2004. Google Scholar

[18]

J. Hu and L. Ying, A fast spectral algorithm for the quantum Boltzmann collision operator, Commun. Math. Sci., 10 (2012), 989-999.  doi: 10.4310/CMS.2012.v10.n3.a13.  Google Scholar

[19]

H. J. HwangK. Kang and A. Stevens, Drift-diffusion limits of kinetic models for chemotaxis: a generalization, Discrete Contin. Dyn. Syst. Ser. B, 5 (2005), 319-334.  doi: 10.3934/dcdsb.2005.5.319.  Google Scholar

[20]

S. Jin, Asymptotic preserving (AP) schemes for multiscale kinetic and hyperbolic equations: A review, Riv. Math. Univ. Parma (N.S.), 3 (2012), 177-216.   Google Scholar

[21]

S. JinL. Pareschi and G. Toscani, Uniformly accurate diffusive relaxation schemes for multiscale transport equations, SIAM J. Numer. Anal., 38 (2000), 913-936.  doi: 10.1137/S0036142998347978.  Google Scholar

[22]

S. JinM. Tang and H. Han, A uniformly second order numerical method for the one-dimensional discrete-ordinate transport equation and its diffusion limit with interface, Netw. Heterog. Media, 4 (2009), 35-65.  doi: 10.3934/nhm.2009.4.35.  Google Scholar

[23]

E. W. Larsen and J. E. Morel, Asymptotic solutions of numerical transport problems in optically thick, diffusive regimes II, J. Comput. Phys., 83 (1989), 212-236.  doi: 10.1016/0021-9991(89)90229-5.  Google Scholar

[24]

E. W. LarsenJ. E. Morel and W. F. Jr Miller, Asymptotic solutions of numerical transport problems in optically thick, diffusive regimes, J. Comput. Phys., 69 (1987), 283-324.  doi: 10.1016/0021-9991(87)90170-7.  Google Scholar

[25]

L. Mieussens, On the asymptotic preserving property of the unified gas kinetic scheme for the diffusion limit of linear kinetic models, J. Comput. Phys., 253 (2013), 138-156.  doi: 10.1016/j.jcp.2013.07.002.  Google Scholar

[26]

H. G. OthmerS. R. Dunbar and W. Alt, Models of dispersal in biological systems, J. Math. Biol., 26 (1988), 263-298.  doi: 10.1007/BF00277392.  Google Scholar

[27]

H. G. Othmer and T. Hillen, The diffusion limit of transport equations. II. Chemotaxis equations, SIAM J. Appl. Math., 62 (2002), 1222-1250.  doi: 10.1137/S0036139900382772.  Google Scholar

[28]

J. Saragosti, V. Calvez, N. Bournaveas, A. Buguin, P. Silberzan and B. Perthame, Mathematical description of bacterial traveling pulses, PLoS Comput. Biol., 6 (2010), e1000890, 12 pp. doi: 10.1371/journal. pcbi. 1000890.  Google Scholar

[29]

J. SaragostiV. CalvezN. BournaveasB. PerthameA. Buguin and P. Silberzan, Directional persistence of chemotactic bacteria in a traveling concentration wave, Proceedings of the National Academy of Sciences, 108 (2011), 16235-16240.  doi: 10.1073/pnas.1101996108.  Google Scholar

[30]

K. Xu, A gas-kinetic BGK scheme for the Navier-Stokes equations and its connection with artificial dissipation and Godunov method, J. Comput. Phys., 171 (2001), 289-335.  doi: 10.1006/jcph.2001.6790.  Google Scholar

[31]

K. Xu and J.-C. Huang, A unified gas-kinetic scheme for continuum and rarefied flows, J. Comput. Phys., 229 (2010), 7747-7764.  doi: 10.1016/j.jcp.2010.06.032.  Google Scholar

show all references

References:
[1]

M. Adams, Discontinuous finite element transport solutions in thick diffusive problems, Nuclear Science and Engineering, 137 (2001), 298-333.  doi: 10.13182/NSE00-41.  Google Scholar

[2]

W. Alt, Biased random walk models for chemotaxis and related diffusion approximations, J. Math. Biol., 9 (1980), 147-177.  doi: 10.1007/BF00275919.  Google Scholar

[3]

S. Boscarino and L. Pareschi, On the asymptotic properties of IMEX Runge–Kutta schemes for hyperbolic balance laws, J. Comput. Appl. Math., 316 (2017), 60-73.  doi: 10.1016/j.cam.2016.08.027.  Google Scholar

[4]

R. Botchorishvili, B. Perthame and A. Vasseur, Equilibrium schemes for scalar conservation laws with stiff sources, Math. Comp., 72 (2003), 131–157 (electronic). doi: 10.1090/S0025-5718-01-01371-0.  Google Scholar

[5]

J. A. Carrillo and B. Yan, An asymptotic preserving scheme for the diffusive limit of kinetic systems for chemotaxis, Multiscale Model. Simul., 11 (2013), 336-361.  doi: 10.1137/110851687.  Google Scholar

[6]

C. Cercignani, The Boltzmann equation and its applications, Springer, 1988. doi: 10.1007/978-1-4612-1039-9.  Google Scholar

[7]

F. A. C. C. ChalubP. A. MarkowichB. Perthame and C. Schmeiser, Kinetic models for chemotaxis and their drift-diffusion limits, Monatsh. Math., 142 (2004), 123-141.  doi: 10.1007/s00605-004-0234-7.  Google Scholar

[8]

A. ChertockA. KurganovM. Lukáčová-Medvid'ová and S.N. Özcan, An asymptotic preserving scheme for kinetic chemotaxis models in two space dimensions, Kinet. Relat. Models, 12 (2019), 195-216.  doi: 10.3934/krm.2019009.  Google Scholar

[9]

G. Dimarco and L. Pareschi, Implicit-explicit linear multistep methods for stiff kinetic equations, SIAM J. Numer. Anal., 55 (2017), 664-690.  doi: 10.1137/16M1063824.  Google Scholar

[10]

F. Filbet and S. Jin, A class of asymptotic-preserving schemes for kinetic equations and related problems with stiff sources, Journal of Computational Physics, 229 (2010), 7625-7648.  doi: 10.1016/j.jcp.2010.06.017.  Google Scholar

[11]

F. FilbetC. Mouhot and L. Pareschi, Solving the Boltzmann equation in $n\log_2n$, SIAM Journal of Scientific Computation, 28 (2006), 1029-1053.   Google Scholar

[12]

L. Gosse, A well-balanced scheme for kinetic models of chemotaxis derived from one-dimensional local forward-backward problems, Math. Biosci., 242 (2013), 117-128.  doi: 10.1016/j.mbs.2012.12.009.  Google Scholar

[13]

L. Gosse and G. Toscani, An asymptotic-preserving well-balanced scheme for the hyperbolic heat equations, C. R. Math. Acad. Sci. Paris, 334 (2002), 337-342.  doi: 10.1016/S1631-073X(02)02257-4.  Google Scholar

[14]

L. Gosse and G. Toscani, Space localization and well-balanced schemes for discrete kinetic models in diffusive regimes, SIAM J. Numer. Anal., 41 (2003), 641-658.  doi: 10.1137/S0036142901399392.  Google Scholar

[15]

L. Gosse and G. Toscani, Asymptotic-preserving & well-balanced schemes for radiative transfer and the rosseland approximation, Numer. Math., 98 (2004), 223-250.  doi: 10.1007/s00211-004-0533-x.  Google Scholar

[16]

S. Guisset, S. Brull, E. D'Humières and B. Dubroca, Asymptotic-preserving well-balanced scheme for the electronic $M_1$ model in the diffusive limit: Particular cases, ESAIM Math. Model. Numer. Anal., 51 (2017), 1805-1826. doi: 10.1051/m2an/2016079.  Google Scholar

[17]

B. Howard, E. Coli in Motion, Biological and Medical Physics, Biomedical Engineering, Springer, 2004. Google Scholar

[18]

J. Hu and L. Ying, A fast spectral algorithm for the quantum Boltzmann collision operator, Commun. Math. Sci., 10 (2012), 989-999.  doi: 10.4310/CMS.2012.v10.n3.a13.  Google Scholar

[19]

H. J. HwangK. Kang and A. Stevens, Drift-diffusion limits of kinetic models for chemotaxis: a generalization, Discrete Contin. Dyn. Syst. Ser. B, 5 (2005), 319-334.  doi: 10.3934/dcdsb.2005.5.319.  Google Scholar

[20]

S. Jin, Asymptotic preserving (AP) schemes for multiscale kinetic and hyperbolic equations: A review, Riv. Math. Univ. Parma (N.S.), 3 (2012), 177-216.   Google Scholar

[21]

S. JinL. Pareschi and G. Toscani, Uniformly accurate diffusive relaxation schemes for multiscale transport equations, SIAM J. Numer. Anal., 38 (2000), 913-936.  doi: 10.1137/S0036142998347978.  Google Scholar

[22]

S. JinM. Tang and H. Han, A uniformly second order numerical method for the one-dimensional discrete-ordinate transport equation and its diffusion limit with interface, Netw. Heterog. Media, 4 (2009), 35-65.  doi: 10.3934/nhm.2009.4.35.  Google Scholar

[23]

E. W. Larsen and J. E. Morel, Asymptotic solutions of numerical transport problems in optically thick, diffusive regimes II, J. Comput. Phys., 83 (1989), 212-236.  doi: 10.1016/0021-9991(89)90229-5.  Google Scholar

[24]

E. W. LarsenJ. E. Morel and W. F. Jr Miller, Asymptotic solutions of numerical transport problems in optically thick, diffusive regimes, J. Comput. Phys., 69 (1987), 283-324.  doi: 10.1016/0021-9991(87)90170-7.  Google Scholar

[25]

L. Mieussens, On the asymptotic preserving property of the unified gas kinetic scheme for the diffusion limit of linear kinetic models, J. Comput. Phys., 253 (2013), 138-156.  doi: 10.1016/j.jcp.2013.07.002.  Google Scholar

[26]

H. G. OthmerS. R. Dunbar and W. Alt, Models of dispersal in biological systems, J. Math. Biol., 26 (1988), 263-298.  doi: 10.1007/BF00277392.  Google Scholar

[27]

H. G. Othmer and T. Hillen, The diffusion limit of transport equations. II. Chemotaxis equations, SIAM J. Appl. Math., 62 (2002), 1222-1250.  doi: 10.1137/S0036139900382772.  Google Scholar

[28]

J. Saragosti, V. Calvez, N. Bournaveas, A. Buguin, P. Silberzan and B. Perthame, Mathematical description of bacterial traveling pulses, PLoS Comput. Biol., 6 (2010), e1000890, 12 pp. doi: 10.1371/journal. pcbi. 1000890.  Google Scholar

[29]

J. SaragostiV. CalvezN. BournaveasB. PerthameA. Buguin and P. Silberzan, Directional persistence of chemotactic bacteria in a traveling concentration wave, Proceedings of the National Academy of Sciences, 108 (2011), 16235-16240.  doi: 10.1073/pnas.1101996108.  Google Scholar

[30]

K. Xu, A gas-kinetic BGK scheme for the Navier-Stokes equations and its connection with artificial dissipation and Godunov method, J. Comput. Phys., 171 (2001), 289-335.  doi: 10.1006/jcph.2001.6790.  Google Scholar

[31]

K. Xu and J.-C. Huang, A unified gas-kinetic scheme for continuum and rarefied flows, J. Comput. Phys., 229 (2010), 7747-7764.  doi: 10.1016/j.jcp.2010.06.032.  Google Scholar

Figure 1.  Neutron Transport. Left: The density $ \rho_{r} $ at time $ t = 0.05 $ for $ \varepsilon = 10^{-2} $, $ \varepsilon = 10^{-3} $, $ \varepsilon = 10^{-6} $ and the solution of the diffusion limit equation; right: a zoomed part of the left plot
Figure 2.  Neutron Transport: Time evolution of the $ L^\infty $-norm of the difference between the solution and the stationary solution in the time interval [0, 8] for $ \varepsilon = 10^{-8} $
Figure 3.  Verification of the AP property of the UGKS for the chemotaxis kinetic model. Left: The density $ \rho $ at time $ t = 1 $ for $ \varepsilon = 10^{-2},10^{-3},10^{-4},10^{-5},10^{-6} $; right: a zoomed part of the left plot
Figure 4.  Boltzmann: cross section of the distribution function for different values of $ \varepsilon $(left) and a zoomed part of the plot(right)
Figure 5.  Boltzmann: contours of the 2D distribution function (left) and the contour lines of the difference between the distribution function and its equilibrium (right) at the final time $ t = 200 $
Figure 6.  Boltzmann: Time evolution of the $ L^\infty $-norm of the difference between the distribution function $ f $ and its equilibrium in the time interval [0, 200]
Table 1.  A list of kinetic models together with their corresponding schemes
Section Kinetic Model Scheme Reference
2 Neutron transport equation Parity-equations based [20]
3 Chemotaxis kinetic model UGKS [25, 30, 31]
4 Boltzmann equation IMEX Penalization method [10]
Section Kinetic Model Scheme Reference
2 Neutron transport equation Parity-equations based [20]
3 Chemotaxis kinetic model UGKS [25, 30, 31]
4 Boltzmann equation IMEX Penalization method [10]
Table 2.  Neutron Transport: $ L^\infty $-norm of the difference between the solution and the stationary solution in the time interval [0, 8] for $ \varepsilon = 10^{-2} $ (top) and $ \varepsilon = 10^{-8} $ (bottom)
T 0 2 4 6 8
$ L^\infty $ 0.995 $ 1.051\times 10^{-3} $ $ 1.683\times 10^{-6} $ $ 2.696\times 10^{-9} $ $ 4.120\times 10^{-12} $
T 0 2 4 6 8
$ L^\infty $ 1 $ 9.111\times 10^{-4} $ $ 1.263\times 10^{-6} $ $ 1.752\times 10^{-9} $ $ 2.176\times 10^{-12} $
T 0 2 4 6 8
$ L^\infty $ 0.995 $ 1.051\times 10^{-3} $ $ 1.683\times 10^{-6} $ $ 2.696\times 10^{-9} $ $ 4.120\times 10^{-12} $
T 0 2 4 6 8
$ L^\infty $ 1 $ 9.111\times 10^{-4} $ $ 1.263\times 10^{-6} $ $ 1.752\times 10^{-9} $ $ 2.176\times 10^{-12} $
Table 3.  Chemotaxis: $ L^\infty $-norm of the difference between the solution and the stationary solution in the time interval [0, 100] for $ \varepsilon = 1 $ (top) and $ \varepsilon = 10^{-3} $ (bottom)
T 0 30 60 65 100
$ L^\infty $ 0.9064 $ 8.260\times 10^{-7} $ $ 3.767\times 10^{-11} $ $ 7.474\times 10^{-12} $ $ 1.662\times 10^{-12} $
T 0 5 10 50 100
$ L^\infty $ 0.6493 $ 3.024\times 10^{-7} $ $ 2.064\times 10^{-9} $ $ 2.199\times 10^{-10} $ $ 1.476\times 10^{-10} $
T 0 30 60 65 100
$ L^\infty $ 0.9064 $ 8.260\times 10^{-7} $ $ 3.767\times 10^{-11} $ $ 7.474\times 10^{-12} $ $ 1.662\times 10^{-12} $
T 0 5 10 50 100
$ L^\infty $ 0.6493 $ 3.024\times 10^{-7} $ $ 2.064\times 10^{-9} $ $ 2.199\times 10^{-10} $ $ 1.476\times 10^{-10} $
Table 4.  Boltzmann: $ L^\infty $-norm of the difference between $ f $ and its equilibrium starting from t = 0 till the final time t = 200 for $ \varepsilon = 1 $
T 0 20 50 100 150 200
$ L^\infty $ 0.5453 $ 1.2\times 10^{-3} $ $ 6.581\times 10^{-7} $ $ 3.495\times 10^{-12} $ 7.619 $ \times 10^{-13} $ 5.623$ \times 10^{-13} $
T 0 20 50 100 150 200
$ L^\infty $ 0.5453 $ 1.2\times 10^{-3} $ $ 6.581\times 10^{-7} $ $ 3.495\times 10^{-12} $ 7.619 $ \times 10^{-13} $ 5.623$ \times 10^{-13} $
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