Research article

An asymptotic-preserving scheme for isentropic flow in pipe networks

  • Published: 25 March 2025
  • We considered the simulation of isentropic flow in pipelines and pipe networks. Standard operating conditions in pipe networks suggested an emphasis to simulate low Mach and high friction regimes—however, the system was stiff in these regimes and conventional explicit approximation techniques proved quite costly and often impractical. To combat these inefficiencies, we developed a novel asymptotic-preserving scheme that was uniformly consistent and stable for all Mach regimes. The proposed method for a single pipeline followed the flux splitting suggested in Haack et al., in which the flux was separated into stiff and non-stiff portions then discretized in time using an implicit-explicit approach. The non-stiff part was advanced in time by an explicit hyperbolic solver; we opted for the second-order central-upwind finite volume scheme. The stiff portion is advanced in time implicitly using an approach based on Rosenbrock-type Runge-Kutta methods, which ultimately reduced this implicit stage to a discretization of a linear elliptic equation. To extend to full pipe networks, the scheme on a single pipeline was paired with coupling conditions defined at pipe-to-pipe intersections to ensure a mathematically well-posed problem. We showed that the coupling conditions remained well-posed at the low Mach/high friction limit—which, when used to define the ghost cells of each pipeline, resulted in a method that was accurate across these intersections in all regimes. The proposed method was tested on several numerical examples and produced accurate, non-oscillatory results with run times independent of the Mach number.

    Citation: Michael T. Redle, Michael Herty. An asymptotic-preserving scheme for isentropic flow in pipe networks[J]. Networks and Heterogeneous Media, 2025, 20(1): 254-285. doi: 10.3934/nhm.2025013

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  • We considered the simulation of isentropic flow in pipelines and pipe networks. Standard operating conditions in pipe networks suggested an emphasis to simulate low Mach and high friction regimes—however, the system was stiff in these regimes and conventional explicit approximation techniques proved quite costly and often impractical. To combat these inefficiencies, we developed a novel asymptotic-preserving scheme that was uniformly consistent and stable for all Mach regimes. The proposed method for a single pipeline followed the flux splitting suggested in Haack et al., in which the flux was separated into stiff and non-stiff portions then discretized in time using an implicit-explicit approach. The non-stiff part was advanced in time by an explicit hyperbolic solver; we opted for the second-order central-upwind finite volume scheme. The stiff portion is advanced in time implicitly using an approach based on Rosenbrock-type Runge-Kutta methods, which ultimately reduced this implicit stage to a discretization of a linear elliptic equation. To extend to full pipe networks, the scheme on a single pipeline was paired with coupling conditions defined at pipe-to-pipe intersections to ensure a mathematically well-posed problem. We showed that the coupling conditions remained well-posed at the low Mach/high friction limit—which, when used to define the ghost cells of each pipeline, resulted in a method that was accurate across these intersections in all regimes. The proposed method was tested on several numerical examples and produced accurate, non-oscillatory results with run times independent of the Mach number.



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    [1] A. Osiadacz, Simulation and analysis of gas networks, 1987. Available from: https://www.osti.gov/biblio/5141539.
    [2] A. Bressan, S. Čanić, M. Garavello, M. Herty, B. Piccoli, Flows on networks: Recent results and perspectives, EMS Surv. Math. Sci., 1 (2014), 47–111. https://doi.org/10.4171/emss/2 doi: 10.4171/emss/2
    [3] J. Brouwer, I. Gasser, M. Herty, Gas pipeline models revisited: Model hierarchies, nonisothermal models, and simulations of networks, Multiscale Model. Simul., 9 (2011), 601–623. https://doi.org/10.1137/100813580 doi: 10.1137/100813580
    [4] H. Guillard, C. Viozat, On the behaviour of upwind schemes in the low Mach number limit, Comput. Fluids, 28 (1999), 63–86. https://doi.org/10.1016/S0045-7930(98)00017-6 doi: 10.1016/S0045-7930(98)00017-6
    [5] H. Guillard, A. Murrone, On the behavior of upwind schemes in the low Mach number limit: Ⅱ. Godunov type schemes, Comput. Fluids, 33 (2004), 655–675. https://doi.org/10.1016/j.compfluid.2003.07.001 doi: 10.1016/j.compfluid.2003.07.001
    [6] F. Rieper, On the dissipation mechanism of upwind-schemes in the low Mach number regime: A comparison between roe and hll, J. Comput. Phys., 229 (2010), 221–232. https://doi.org/10.1016/j.jcp.2009.09.043 doi: 10.1016/j.jcp.2009.09.043
    [7] S. Jin, Runge-Kutta methods for hyperbolic conservation laws with stiff relaxation terms, J. Comput. Phys., 122 (1995), 51–67. https://doi.org/10.1006/jcph.1995.1196 doi: 10.1006/jcph.1995.1196
    [8] S. Jin, Efficient asymptotic-preserving (AP) schemes for some multiscale kinetic equations, SIAM J. Sci. Comput., 21 (1999), 441–454. https://doi.org/10.1137/S1064827598334599 doi: 10.1137/S1064827598334599
    [9] J. Hu, S. Jin, Q. Li, Asymptotic-preserving schemes for multiscale hyperbolic and kinetic equations, In: Handbook of Numerical Analysis, Elsevier, 18 (2007), 103–129. https://doi.org/10.1016/bs.hna.2016.09.001
    [10] J. Hu, R. Shu, X. Zhang, Asymptotic-preserving and positivity-preserving implicit-explicit schemes for the stiff BGK equation, SIAM J. Numer. Anal., 56 (2018), 942–973. https://doi.org/10.1137/17M1144362 doi: 10.1137/17M1144362
    [11] S. Jin, L. Pareschi, G. Toscani, Uniformly accurate diffusive relaxation schemes for multiscale transport equations, SIAM J. Numer. Anal., 38 (2000), 913–936. https://doi.org/10.1137/S0036142998347978 doi: 10.1137/S0036142998347978
    [12] S. Jin, Asymptotic preserving (AP) schemes for multiscale kinetic and hyperbolic equations: A review, Riv. Math. Univ. Parma (N.S.), 3 (2012), 177–216.
    [13] S. Jin, Asymptotic-preserving schemes for multiscale physical problems, Acta Numer., 31 (2022), 415–489. https://doi.org/10.1017/S0962492922000010 doi: 10.1017/S0962492922000010
    [14] W. Ren, H. Liu, S. Jin, An asymptotic-preserving Monte Carlo method for the Boltzmann equation, J. Comput. Phys., 276 (2014), 380–404. https://doi.org/10.1016/j.jcp.2014.07.029 doi: 10.1016/j.jcp.2014.07.029
    [15] B. Zhang, H. Liu, S. Jin, An asymptotic preserving Monte Carlo method for the multispecies Boltzmann equation, J. Comput. Phys., 305 (2016), 575–588. https://doi.org/10.1016/j.jcp.2015.11.006 doi: 10.1016/j.jcp.2015.11.006
    [16] F. Fei, A time-relaxed Monte Carlo method preserving the Navier-Stokes asymptotics, J. Comput. Phys., 486 (2023), 112128. https://doi.org/10.1016/j.jcp.2023.112128 doi: 10.1016/j.jcp.2023.112128
    [17] F. Fei, A Navier-Stokes asymptotic preserving Direct Simulation Monte Carlo method for multi-species gas flows, arXiv preprint arXiv: 2410.20322, 2024.
    [18] S. Jin, Z. Ma, K. Wu, Asymptotic-preserving neural networks for multiscale time-dependent linear transport equations, J. Sci. Comput., 94 (2023), 57. https://doi.org/10.1007/s10915-023-02100-0 doi: 10.1007/s10915-023-02100-0
    [19] S. Jin, Z. Ma, K. Wu, Asymptotic-preserving neural networks for multiscale kinetic equations, Commun. Comput. Phys., 35 (2024), 693–723. https://doi.org/10.4208/cicp.oa-2023-0211 doi: 10.4208/cicp.oa-2023-0211
    [20] K. R. Arun, S. Samantaray, An asymptotic preserving time integrator for low Mach number limits of the Euler equations with gravity, arXiv preprint arXiv: 1902.00221, 2019.
    [21] K. R. Arun, S. Samantaray, Asymptotic preserving low Mach number accurate IMEX finite volume schemes for the isentropic Euler equations, J. Sci. Comput., 82 (2020), 1–32. https://doi.org/10.1007/s10915-020-01138-8 doi: 10.1007/s10915-020-01138-8
    [22] S. Boscarino, J. M. Qiu, G. Russo, T. Xiong, A high order semi-implicit IMEX WENO scheme for the all-Mach isentropic Euler system, J. Comput. Phys., 392 (2019), 594–618. https://doi.org/10.1016/j.jcp.2019.04.057 doi: 10.1016/j.jcp.2019.04.057
    [23] P. Degond, M. Tang, All speed scheme for the low Mach number limit of the isentropic Euler equations, Commun. Comput. Phys., 10 (2011), 1–31. https://doi.org/10.4208/cicp.210709.210610a doi: 10.4208/cicp.210709.210610a
    [24] G. Dimarco, R. Loubère, M. H. Vignal, Study of a new asymptotic preserving scheme for the Euler system in the low Mach number limit, SIAM J. Sci. Comput., 39 (2017), A2099–A2128. https://doi.org/10.1137/16M1069274 doi: 10.1137/16M1069274
    [25] G. Dimarco, R. Loubère, V. Michel-Dansac, M. H. Vignal, Second-order implicit-explicit total variation diminishing schemes for the Euler system in the low Mach regime, J. Comput. Phys., 372 (2018), 178–201. https://doi.org/10.1016/j.jcp.2018.06.022 doi: 10.1016/j.jcp.2018.06.022
    [26] J. Haack, S. Jin, J. G. Liu, An all-speed asymptotic-preserving method for the isentropic Euler and Navier-Stokes equations, Commun. Comput. Phys., 12 (2012), 955–980. https://doi.org/10.4208/cicp.250910.131011a doi: 10.4208/cicp.250910.131011a
    [27] S. Samantaray, Asymptotic preserving linearly implicit additive IMEX-RK finite volume schemes for low Mach number isentropic Euler equations, arXiv preprint arXiv: 2409.05854, 2024.
    [28] S. Avgerinos, F. Bernard, A. Iollo, G. Russo, Linearly implicit all Mach number shock capturing schemes for the Euler equations, J. Comput. Phys., 393 (2019), 278–312. https://doi.org/10.1016/j.jcp.2019.04.020 doi: 10.1016/j.jcp.2019.04.020
    [29] G. Bispen, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, L. Yelash, Asymptotic preserving IMEX finite volume schemes for low Mach number Euler equations with gravitation, J. Comput. Phys., 335 (2017), 222–248. https://doi.org/10.1016/j.jcp.2017.01.020 doi: 10.1016/j.jcp.2017.01.020
    [30] R. Klein, Semi-implicit extension of a Godunov-type scheme based on low Mach number asymptotics Ⅰ: One-dimensional flow, J. Comput. Phys., 121 (1995), 213–237. https://doi.org/10.1016/S0021-9991(95)90034-9 doi: 10.1016/S0021-9991(95)90034-9
    [31] V. Kučera, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, S. Noelle, J. Schütz, Asymptotic properties of a class of linearly implicit schemes for weakly compressible Euler equations, Numer. Math., 150 (2022), 79–103. https://doi.org/10.1007/s00211-021-01240-5 doi: 10.1007/s00211-021-01240-5
    [32] S. Noelle, G. Bispen, K. R. Arun, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, C. D. Munz, A weakly asymptotic preserving low Mach number scheme for the Euler equations of gas dynamics, SIAM J. Sci. Comput., 36 (2014), B989–B1024. https://doi.org/10.1137/120895627 doi: 10.1137/120895627
    [33] J. Zeifang, J. Schütz, K. Kaiser, A. Beck, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, S. Noelle, A novel full-Euler low Mach number IMEX splitting, Commun. Comput. Phys., 27 (2020), 292–320. https://doi.org/10.4208/cicp.oa-2018-0270 doi: 10.4208/cicp.oa-2018-0270
    [34] W. Boscheri, M. Dumbser, M. Ioriatti, I. Peshkov, E. Romenski, A structure-preserving staggered semi-implicit finite volume scheme for continuum mechanics, J. Comput. Phys., 424 (2021), 109866. https://doi.org/10.1016/j.jcp.2020.109866 doi: 10.1016/j.jcp.2020.109866
    [35] F. Cordier, P. Degond, A. Kumbaro, An asymptotic-preserving all-speed scheme for the Euler and Navier-Stokes equations, J. Comput. Phys., 231 (2012), 5685–5704. https://doi.org/10.1016/j.jcp.2012.04.025 doi: 10.1016/j.jcp.2012.04.025
    [36] M. Dumbser, V. Casulli, A conservative, weakly nonlinear semi-implicit finite volume scheme for the compressible Navier-Stokes equations with general equation of state, Appl. Math. Comput., 272 (2016), 479–497. https://doi.org/10.1016/j.amc.2015.08.042 doi: 10.1016/j.amc.2015.08.042
    [37] I. Peshkov, M. Dumbser, W. Boscheri, E. Romenski, S. Chiocchetti, M. Ioriatti, Simulation of non-Newtonian viscoplastic flows with a unified first order hyperbolic model and a structure-preserving semi-implicit scheme, Comput. Fluids, 224 (2021), 104963. https://doi.org/10.1016/j.compfluid.2021.104963 doi: 10.1016/j.compfluid.2021.104963
    [38] G. Bispen, K. R. Arun, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, S. Noelle, IMEX large time step finite volume methods for low Froude number shallow water flows, Commun. Comput. Phys., 16 (2014), 307–347. http://doi.org/10.4208/cicp.040413.160114a doi: 10.4208/cicp.040413.160114a
    [39] W. Boscheri, M. Tavelli, C. E. Castro, An all Froude high order IMEX scheme for the shallow water equations on unstructured Voronoi meshes, Appl. Numer. Math., 185 (2023), 311–335. https://doi.org/10.1016/j.apnum.2022.11.022 doi: 10.1016/j.apnum.2022.11.022
    [40] G. Huang, Y. Xing, T. Xiong, High order well-balanced asymptotic preserving finite difference WENO schemes for the shallow water equations in all Froude numbers, J. Comput. Phys., 463 (2022), 111255. https://doi.org/10.1016/j.jcp.2022.111255 doi: 10.1016/j.jcp.2022.111255
    [41] S. Vater, R. Klein, A semi-implicit multiscale scheme for shallow water flows at low Froude number, Commun. Appl. Math. Comput. Sci., 13 (2018), 303–336. https://doi.org/10.2140/camcos.2018.13.303 doi: 10.2140/camcos.2018.13.303
    [42] X. Xie, H. Dong, M. Li, High order well-balanced asymptotic preserving IMEX RKDG schemes for the two-dimensional nonlinear shallow water equations, J. Comput. Phys., 510 (2024), 113092. https://doi.org/10.1016/j.jcp.2024.113092 doi: 10.1016/j.jcp.2024.113092
    [43] H. Zakerzadeh, The RS-IMEX scheme for the rotating shallow water equations with the Coriolis force, In: Finite volumes for complex applications Ⅷ—Hyperbolic, Elliptic and Parabolic Problems, Cham: Springer, 200 (2017), 199–207. https://doi.org/10.1007/978-3-319-57394-6-22
    [44] S. Busto, M. Dumbser, A staggered semi-implicit hybrid finite volume / finite element scheme for the shallow water equations at all Froude numbers, Appl. Numer. Math., 175 (2022), 108–132. https://doi.org/10.1016/j.apnum.2022.02.005 doi: 10.1016/j.apnum.2022.02.005
    [45] A. Duran, F. Marche, R. Turpault, C. Berthon, Asymptotic preserving scheme for the shallow water equations with source terms on unstructured meshes, J. Comput. Phys., 287 (2015), 184–206. https://doi.org/10.1016/j.jcp.2015.02.007 doi: 10.1016/j.jcp.2015.02.007
    [46] A. Kurganov, Y. Liu, M. Lukáčová-Medvi$\check{{\text{d}}}$ová, A well-balanced asymptotic preserving scheme for the two-dimensional rotating shallow water equations with nonflat bottom topography, SIAM J. Sci. Comput., 44 (2022), A1655–A1680. https://doi.org/10.1137/21M141573X doi: 10.1137/21M141573X
    [47] X. Liu, A. Chertock, A. Kurganov, An asymptotic preserving scheme for the two-dimensional shallow water equations with Coriolis forces, J. Comput. Phys., 391 (2019), 259–279. https://doi.org/10.1016/j.jcp.2019.04.035 doi: 10.1016/j.jcp.2019.04.035
    [48] H. Egger, J. Giesselmann, T. Kunkel, N. Philippi, An asymptotic-preserving discretization scheme for gas transport in pipe networks, IMA J. Numer. Anal., 43 (2023), 2137–2168. https://doi.org/10.1093/imanum/drac032 doi: 10.1093/imanum/drac032
    [49] H. Egger, N. Philippi, An asymptotic preserving hybrid-dG method for convection-diffusion equations on pipe networks, arXiv preprint arXiv: 2209.04238, 2022. https://doi.org/10.48550/arXiv.2209.04238
    [50] A. Kurganov, S. Noelle, G. Petrova, Semidiscrete central-upwind schemes for hyperbolic conservation laws and Hamilton-Jacobi equations, SIAM J. Sci. Comput., 23 (2001), 707–740. https://doi.org/10.1137/S1064827500373413 doi: 10.1137/S1064827500373413
    [51] A. Kurganov, E. Tadmor, Solution of two-dimensional Riemann problems for gas dynamics without Riemann problem solvers, Numer. Methods Partial Differ. Equations, 18 (2002), 584–608. https://doi.org/10.1002/num.10025 doi: 10.1002/num.10025
    [52] G. Wanner, E. Hairer, Solving Ordinary Differential Equations II, New York: Springer Berlin Heidelberg, 1996.
    [53] X. Zhong, Additive semi-implicit Runge-Kutta methods for computing high-speed nonequilibrium reactive flows, J. Comput. Phys., 128 (1996), 19–31. https://doi.org/10.1006/jcph.1996.0193 doi: 10.1006/jcph.1996.0193
    [54] M. K. Banda, M. Herty, A. Klar, Gas flow in pipeline networks, Netw. Heterog. Media, 1 (2006), 41–56. https://doi.org/10.3934/nhm.2006.1.41 doi: 10.3934/nhm.2006.1.41
    [55] H. Egger, J. Giesselmann, Stability and asymptotic analysis for instationary gas transport via relative energy estimates, Numer. Math., 153 (2023), 701–728. https://doi.org/10.1007/s00211-023-01349-9 doi: 10.1007/s00211-023-01349-9
    [56] K. Ehrhardt, M. C. Steinbach, Nonlinear optimization in gas networks, In: Modeling, Simulation and Optimization of Complex Processes, Berlin Heidelberg: Springer, 2005,139–148. https://doi.org/10.1007/3-540-27170-8-11
    [57] M. Herty, N. Izem, M. Seaid, Fast and accurate simulations of shallow water equations in large networks, Comput. Math. Appl., 78 (2019), 2107–2126. https://doi.org/10.1016/j.camwa.2019.03.049 doi: 10.1016/j.camwa.2019.03.049
    [58] J. Caputo, D. Dutykh, B. Gleyse, Coupling conditions for water waves at forks, Symmetry, 11 (2019), 434. https://www.mdpi.com/2073-8994/11/3/434
    [59] R. M. Colombo, M. Garavello, A well posed Riemann problem for the $p$-system at a junction, Netw. Heterog. Media, 1 (2006), 495–511. https://doi.org/10.3934/nhm.2006.1.495 doi: 10.3934/nhm.2006.1.495
    [60] F. M. White, H. Xue, Fluid Mechanics, New York: McGraw-hill, 2003.
    [61] A. Ambroso, C. Chalons, F. Coquel, E. Godlewski, F. Lagoutière, P. A. Raviart, et al., Coupling of general Lagrangian systems, Math. Comp., 77 (2008), 909–941. https://doi.org/10.1090/S0025-5718-07-02064-9 doi: 10.1090/S0025-5718-07-02064-9
    [62] R. Borsche, Numerical schemes for networks of hyperbolic conservation laws, Appl. Numer. Math., 108 (2016), 157–170. https://doi.org/10.1016/j.apnum.2016.01.006 doi: 10.1016/j.apnum.2016.01.006
    [63] G. Bretti, R. Natalini, B. Piccoli, Fast algorithms for the approximation of a traffic flow model on networks, Discrete Contin. Dyn. Syst. Ser. B, 6 (2006), 427–448. https://doi.org/10.3934/dcdsb.2006.6.427 doi: 10.3934/dcdsb.2006.6.427
    [64] C. Chalons, P. A. Raviart, N. Seguin, The interface coupling of the gas dynamics equations, Quart. Appl. Math., 66 (2008), 659–705. https://doi.org/10.1090/S0033-569X-08-01087-X doi: 10.1090/S0033-569X-08-01087-X
    [65] F. Dubois, P. LeFloch, Boundary conditions for nonlinear hyperbolic systems of conservation laws, J. Differ. Equations, 71 (1988), 93–122. https://doi.org/10.1016/0022-0396(88)90040-X doi: 10.1016/0022-0396(88)90040-X
    [66] E. Godlewski, P. A. Raviart, The numerical interface coupling of nonlinear hyperbolic systems of conservation laws: Ⅰ. The scalar case, Numer. Math., 97 (2004), 81–130. http://link.springer.com/10.1007/s00211-002-0438-5 doi: 10.1007/s00211-002-0438-5
    [67] E. Godlewski, P. A. Raviart, A method of coupling non-linear hyperbolic systems: Examples in CFD and plasma physics, Int. J. Numer. Methods Fluids, 47 (2005), 1035–1041. https://doi.org/10.1002/fld.856 doi: 10.1002/fld.856
    [68] H. Holden, N. H. Risebro, A mathematical model of traffic flow on a network of unidirectional roads, SIAM J. Math. Anal., 26 (1995), 999–1017. https://doi.org/10.1137/S0036141093243289 doi: 10.1137/S0036141093243289
    [69] L. O. Müller, P. J. Blanco, A high order approximation of hyperbolic conservation laws in networks: Application to one-dimensional blood flow, J. Comput. Phys., 300 (2015), 423–437. https://doi.org/10.1016/j.jcp.2015.07.056 doi: 10.1016/j.jcp.2015.07.056
    [70] A. Harten, P. D. Lax, B. van Leer, On upstream differencing and Godunov-type schemes for hyperbolic conservation laws, SIAM Rev., 25 (1983), 35–61. https://doi.org/10.1137/1025002 doi: 10.1137/1025002
    [71] K. A. Lie, S. Noelle, On the artificial compression method for second-order nonoscillatory central difference schemes for systems of conservation laws, SIAM J. Sci. Comput., 24 (2003), 1157–1174. https://doi.org/10.1137/S1064827501392880 doi: 10.1137/S1064827501392880
    [72] H. Nessyahu, E. Tadmor, Nonoscillatory central differencing for hyperbolic conservation laws, J. Comput. Phys., 87 (1990), 408–463. https://doi.org/10.1016/0021-9991(90)90260-8 doi: 10.1016/0021-9991(90)90260-8
    [73] P. K. Sweby, High resolution schemes using flux limiters for hyperbolic conservation laws, SIAM J. Numer. Anal., 21 (1984), 995–1011. https://doi.org/10.1137/0721062 doi: 10.1137/0721062
    [74] M. Garavello, K. Han, B. Piccoli, Models for Vehicular Traffic on Networks, American Institute of Mathematical Sciences, 2016.
    [75] O. Kolb, J. Lang, P. Bales, An implicit box scheme for subsonic compressible flow with dissipative source term, Numer. Algor., 53 (2010), 293–307. https://doi.org/10.1007/s11075-009-9287-y doi: 10.1007/s11075-009-9287-y
    [76] H. Egger, A robust conservative mixed finite element method for isentropic compressible flow on pipe networks, SIAM J. Sci. Comput., 40 (2018), A108–A129. https://doi.org/10.1137/16M1094373 doi: 10.1137/16M1094373
    [77] J. G. Caputo, D. Dutykh, Nonlinear waves in networks: Model reduction for the sine-Gordon equation, Phys. Rev. E, 90 (2014), 022912. https://link.aps.org/doi/10.1103/PhysRevE.90.022912 doi: 10.1103/PhysRevE.90.022912
    [78] D. Dutykh, J. G. Caputo, Wave dynamics on networks: Method and application to the sine-Gordon equation, Appl. Numer. Math., 131 (2018), 54–71. https://doi.org/10.1016/j.apnum.2018.03.010 doi: 10.1016/j.apnum.2018.03.010
    [79] R. Borsche, J. Kall, ADER schemes and high order coupling on networks of hyperbolic conservation laws, J. Comput. Phys., 273 (2014), 658–670. https://doi.org/10.1016/j.jcp.2014.05.042 doi: 10.1016/j.jcp.2014.05.042
    [80] M. Herty, N. Kolbe, S. Müller, Central schemes for networked scalar conservation laws, Netw. Heterog. Media, 18 (2023), 310–340. https://doi.org/10.3934/nhm.2023012 doi: 10.3934/nhm.2023012
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