Stationary states in gas networks

  • Pipeline networks for gas transportation often contain circles. For such networks it is more difficult to determine the stationary states than for networks without circles. We present a method that allows to compute the stationary states for subsonic pipe flow governed by the isothermal Euler equations for certain pipeline networks that contain circles. We also show that suitably chosen boundary data determine the stationary states uniquely. The construction is based upon novel explicit representations of the stationary states on single pipes for the cases with zero slope and with nonzero slope. In the case with zero slope, the state can be represented using the Lambert--W function.

    Citation: Martin Gugat, Falk M. Hante, Markus Hirsch-Dick, Günter Leugering. Stationary states in gas networks[J]. Networks and Heterogeneous Media, 2015, 10(2): 295-320. doi: 10.3934/nhm.2015.10.295

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  • Pipeline networks for gas transportation often contain circles. For such networks it is more difficult to determine the stationary states than for networks without circles. We present a method that allows to compute the stationary states for subsonic pipe flow governed by the isothermal Euler equations for certain pipeline networks that contain circles. We also show that suitably chosen boundary data determine the stationary states uniquely. The construction is based upon novel explicit representations of the stationary states on single pipes for the cases with zero slope and with nonzero slope. In the case with zero slope, the state can be represented using the Lambert--W function.


    Domestic pigs originated from the Eurasian wild boar (Sus scrofa), which first appeared about 9000 years ago [1]. They are essential for the transmission of swine influenza. Human beings raise domestic pigs, and then slaughter them for pork [2]. Domestic pigs grow in the food and environment provided by human beings, while human beings get the necessary nutrients by eating them. Consequently, in the breeding process, the swine flu virus is transmitted to human beings through domestic pig-human contact [2,3]. According to this process, a new breed-slaughter model with swine influenza transmission can be proposed as a model (1.1).

    $ {S1(x,t)t=D12S1(x,t)x2+(B12N2(x,t)ω0N1(x,t))N1(x,t)s0S1(x,t)                 β11I1(x,t)S1(x,t)+γ1I1(x,t),xR,t>0,I1(x,t)t=D12I1(x,t)x2+β11I1(x,t)S1(x,t)(s0+γ1)I1(x,t),xR,t>0,S2(x,t)t=D22S2(x,t)x2+(b2r2N2(x,t)K2+B21N1(x,t))N2(x,t)d2S2(x,t)                  2j=1β2jIj(x,t)S2(x,t)+γ2I2(x,t),xR,t>0,I2(x,t)t=D22I2(x,t)x2+2j=1β2jIj(x,t)S2(x,t)[e2+γ2+d2]I2(x,t),xR,t>0,Ni(x,t)=Si(x,t)+Ii(x,t),i=1,2,xR,t>0.
    $
    (1.1)

    Domestic pig population $ N_1(x, t) $ and human population $ N_2(x, t) $ are assumed to be divided into 2 epidemiological compartments: susceptibles ($ S_i(x, t) $) and infectives ($ I_i(x, t) $) at time $ t $ and location $ x $, $ i = 1, 2 $. Susceptibles can become infected by means of intra-species or inter-species transmission and then recover as new susceptibles. The notation $ B_{12} $ represents the human breeding parameter for the population growth of domestic pigs, while $ B_{21} $ represents the nutrients from eating domestic pigs to increase the birth rate of human beings. The notation $ s_0 $ represents the slaughter rate of domestic pigs. It's noteworthy that domestic pigs cannot survive independently without human beings, but human beings can still survive well without the supply of pork [2]. Restrictions on the development of human population mainly come from intra-species competition.

    For humans, the notation $ r_2 = b_2-d_2 $ is the intrinsic growth rate of humans, where $ b_2 $ and $ d_2 $ represents the natural natality rate and mortality rate, respectively. $ K_2 $ is the environmental carrying capacity of human population without domestic pig supply. $ e_2 $ is the additional mortality rate of humans caused by swine flu. For domestic pigs, $ \omega_0 $ represents the intraspecific competition. During the spread of swine flu, the parameters $ \beta_{ij} $ represent the per capita incidence rate from species $ j $ to species $ i $, where $ i, j = 1, 2 $. $ \gamma_i $ denote the recovery rate for domestic animals and humans, $ i = 1, 2 $. $ D_1 $ and $ D_2 $ are the diffusion coefficients for domestic animals and humans. It is noteworthy that all parameters mentioned above is positive.

    The main purpose of this paper is to propose a new breed-slaughter model with swine influenza transmission, and study the dynamic behavior of it. And then, we focus on the invasion process of infected domestic animals into the habitat of humans. Under certain conditions as in Theorem 2, we construct a propagating terrace linking human habitat to animal-human coexistent habitat, then to swine flu natural foci, which is divided by spreading speeds. Firstly, we calculate the equilibrium points of the model without spatial heterogeneity as a model (1.2) and analyze the existence of them by the persistence theory. Secondly, we discuss their stability by the basic reproduction number. Thirdly, we use these equilibrium points to construct a propagating terrace linking them by spreading speeds.

    $ {dS1(t)dt=(B12N2(t)ω0N1(t))N1(t)s0S1(t)β11I1(t)S1(t)+γ1I1(t),dI1(t)dt=β11I1(t)S1(t)(s0+γ1)I1(t),dS2(t)dt=(b2r2N2(t)K2+B21N1(t))N2(t)d2S2(t)2j=1β2jIj(t)S2(t)+γ2I2(t),dI2(t)dt=2j=1β2jIj(t)S2(t)[e2+γ2+d2]I2(t),Ni(t)=Si(t)+Ii(t),i=1,2.
    $
    (1.2)

    In model (1.2), domestic pig population $ N_1(t) $ and human population $ N_2(t) $ are assumed to be divided into 2 epidemiological compartments: susceptibles ($ S_i(t) $) and infectives ($ I_i(t) $) at time $ t $, $ i = 1, 2 $. Other parameters are the same with model (1.1).

    At first, we focus on the breed-slaughter system without swine flu transmission and spatial heterogeneity.

    If $ I_1(0) = I_2(0) = 0 $, $ N_1(0) > 0 $ and $ N_2(0) > 0 $, model (1.2) turns to a new breed-slaughter system without swine influenza transmission as model (2.1).

    $ {dN1(t)dt=(B12N2(t)ω0N1(t))N1(t)s0N1(t),dN2(t)dt=r2(1N2(t)K2)N2(t)+B21N1(t)N2(t),N1(0)>0,N2(0)>0,
    $
    (2.1)

    Similar to the competition system in [4], breed-slaughter system also has abundant dynamic results. For the positive equilibrium point

    $ E^* = (N^*_1, N^*_2) = ( \frac{{r_2 }(s_0 - B_{12} K_2)}{B_{12} B_{21} K_2 - \omega_0 r_2}, \frac{K_2 (s_0 B_{21} - \omega_0 r_2)}{B_{12} B_{21} K_2 - \omega_0 r_2}) $

    of model (2.1), we have three cases:

    (a). If $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \} $, the positive equilibrium point $ E^* $ of model (2.1) is stable (Figure 2(a)).

    Figure 1.  Swine flu transmission route from pig to human.
    Figure 2.  Phase diagram of $ E^* $.

    (b). If $ B_{12} B_{21} > \frac{\omega_0 r_2}{K_2} $ and $ s_0 > \max \{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \} $, the positive equilibrium point $ E^* $ of model (2.1) is unstable (Figure 2(b)).

    (c). Other than the condition as (a) or (b), the positive equilibrium point $ E^* $ of model (2.1) does not exist.

    In order to reflect the effect of interspecific interaction on swine influenza transmission during breeding process as model (1.2), we suppose that $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $ to guarantee the existence and the stability of the boundary equilibrium point

    $ E_3 = ( \frac{{r_2 }(s_0 - B_{12} K_2)}{B_{12} B_{21} K_2 - \omega_0 r_2}, 0, \frac{K_2 (s_0 B_{21} - \omega_0 r_2)}{B_{12} B_{21} K_2 - \omega_0 r_2}, 0) $

    with $ I_1(0) = I_2(0) = 0 $ in model (1.2).

    After calculation, we summarize that there are at most 6 equilibrium points in $ {\mathbb{R}}_+^4 $ of the system (1.2): $ E_0 = (0, 0, 0, 0) $, $ E_1 = (0, 0, K_2, 0) $, $ E_2 = (0, 0, \overline{S_2}, \overline{I_2}) $, $ E_3 = (N^*_1, 0, N^*_2, 0) $, $ E_4 = (N'_1, 0, S'_2, I'_2) $, $ E_5 = (S^*_1, I^*_1, S^*_2, I^*_2) $, where $ \overline{S_2} = \frac{e_2+\gamma_2+d_2}{\beta_{22}} $, $ \overline{I_2} = \frac{\beta_{22} K_2-(e_2+\gamma_2+d_2)}{\beta_{22}} $, $ N^*_1 = N'_1 = \frac{{r_2 }(s_0 - B_{12} K_2)}{B_{12} B_{21} K_2 - \omega_0 r_2} $, $ N^*_2 = \frac{K_2 (s_0 B_{21} - \omega_0 r_2)}{B_{12} B_{21} K_2 - \omega_0 r_2} $, $ S'_2 = \frac{e_2+\gamma_2+d_2}{\beta_{22}} $, $ I'_2 = \frac{\beta_{22} K_2(1+\frac{s_0B_{21}-B_{12}B_{21}K_2}{B_{12}B_{21}K_2-\omega_0r_2})-(e_2+\gamma_2+d_2)}{\beta_{22}} $. The exact expression of $ E_5 $ is unknown. However, under certain conditions as in Theorem 2, we can obtain its existence by persistence theory [5,6,7].

    If there is no domestic pigs participation, namely $ N_1(0) = S_1(0) = I_1(0) = 0 $, The persistence and the stability of boundary equilibrium $ E_2 = (0, 0, \overline{S}_2, \overline{I}_2) $ has been proved in [8]. Similarly, we define $ R_0 = \frac{\beta _{22} K_1}{b_2 + e_2 + \gamma _2 } $. And then, we can get the following lemma.

    Lemma 1. If $ N_1(0) = S_1(0) = I_1(0) = 0 $ and $ I_2(0) > 0 $, $ \{ 0 \} \times \{ 0 \} \times {\mathbb{R}}_+^2 $ is a invariant set of system (1.2). The trivial equilibrium point $ E_0 $ in model (1.2) is unstable, and we have following two cases:

    (a) If $ R_0 \leq 1 $, the disease-free equilibrium point $ E_1 $ of model (1.2) is stable;

    (b) If $ R_0 > 1 $, model (1.2) has a unique equilibrium point $ E_2 $ in the interior of $ \{ 0 \} \times \{ 0 \} \times {\mathbb{R}}_+^2 $, which is stable, and $ E_1 $ is unstable.

    Furthermore, we consider the transmission process of human influenza with domestic pigs participating, but not infected from them. Namely $ I_1(0) = 0 $, $ I_2(0) > 0 $ and $ N_i(0) > 0 $, $ i = 1, 2 $. The persistence and the stability of boundary equilibrium $ E_4 = (N'_1, 0, S'_2, I'_2) $ is similar to Lemma 1. Taking $ E_3 $ as the original point by coordinate translation, we can get the following lemma by the persistence theory [5,9,10], when $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $.

    According to the definition of basic reproduction number in a single population as [5,11,12], we define $ R_1 = \frac{\beta _{1} N^*_1}{s_0 + \gamma _1 } $ as the basic reproduction number of swine flu transmission in demotic pig population and $ R_2 = \frac{\beta _{22} N^*_2}{e_2+\gamma_2+d_2} $ as the basic reproduction number of swine flu transmission in human population.

    Lemma 2. If $ N_1(0) = S_1(0) > 0 $, $ I_1(0) = 0 $ and $ I_2(0) > 0 $, $ {\mathbb{R}}_+ \times \{ 0 \} \times {\mathbb{R}}_+^2 $ is a invariant set of system (1.2). The trivial equilibrium point $ E_0 $ and the boundary equilibrium point $ E_1 $, $ E_2 $ in model (1.2) are unstable when $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $, and we have following two cases:

    (a) If $ R_2 \leq 1 $, the disease-free equilibrium point $ E_3 $ of model (1.2) is stable;

    (b) If $ R_2 > 1 $, model (1.2) has a unique equilibrium point $ E_4 $ in the interior of $ {\mathbb{R}}_+ \times \{ 0 \} \times {\mathbb{R}}_+^2 $, which is stable, and $ E_3 $ is unstable.

    Next we focus on the discussion about the existence and the stability of the positive equilibrium point $ E_5 = (S^*_1, I^*_1, S^*_2, I^*_2) $. At first, we define $ R_s = \max \{R_1, R_2 \} $. Then, we get the theorem as the following.

    Theorem 1. If $ N_i(0) > 0 $ and $ I_i(0) > 0 $, $ i = 1, 2 $, $ {\mathbb{R}}_+^4 $ is a invariant set of system (1.2). The trivial equilibrium point $ E_0 $ and the boundary equilibrium point $ E_1 $, $ E_2 $ in model (1.2) are unstable when $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $, and we have following three cases:

    (a) If $ R_s \leq 1 $, the disease-free equilibrium point $ E_3 $ of model (1.2) is stable;

    (b) If $ R_s > 1 $, $ R_1 < R_2 $ and $ R_1 \leq 1 $, model (1.2) has a unique equilibrium point $ E_4 $ except for $ E_0 $, $ E_1 $, $ E_2 $ and $ E_3 $, which is stable, and $ E_3 $ is unstable;

    (c) If $ R_s > 1 $ and $ R_1 \geq R_2 $ (or $ R_2 > R_1 > 1 $) model (1.2) has a unique equilibrium point $ E_5 $ in the interior of $ {\mathbb{R}}_+^4 $, which is stable, and $ E_3 $ and $ E_4 $ are unstable.

    Proof. If $ R_s \leq 1 $, $ E_4 $ and $ E_5 $ do not exist. Similar to the results of Lemma 2 (a), the disease-free equilibrium point $ E_3 $ of model (1.2) is stable.

    Then we consider the results of system (1.2) when $ R_s > 1 $ and $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $. At first, we define

    $ D = \{(S_1, I_1, S_2, I_2)\left|0\leq I_i\leq S_i+I_i \leq N^*_i, i = 1, 2 \right \}, $
    $ D_1 = \{(S_1, I_1, S_2, I_2 )\left|I_1 = 0\ or\ I_2 = 0\ , 0 \leq S_i + I_i \leq N^*_i , i = 1, 2\right\}, $
    $ D_2 = D \backslash D_1, {\widetilde{D}}_2 = \{(S_1 , I_1, S_2, I_2)\left|0 \lt I_i \leq S_i + I_i \leq N^*_i, i = 1, 2\right.\}. $

    $ D_2 $ and $ {\widetilde{D}}_2 $ are forward invariant.

    Let $ \Omega^\ast $ consists of equilibria $ E_0 $, $ E_1 $, $ E_2 $, $ E_3 $ and $ E_4 $. These equilibria cannot be chained to each other in $ D_1 $. By analyzing the flow in neighborhood of each equilibrium, it is easy to see that $ \Omega^\ast $ is isolated in $ D $ and $ D_1 $ is a uniform strong repeller for $ {\widetilde{D}}_2 $.

    If $ x(t) = (S_1(t), I_1(t), S_2(t), I_2(t)) $ stays close to $ E_2 $, we have two cases: if $ I_1(0) = I_2(0) = 0 $, then $ I_1(t) = I_2(t) = 0 $; if $ I_1(0) > 0 $ or $ I_2(0) > 0 $, then $ I_2(t) > 0 $. Therefore, $ E_2 $ is isolated in D. Similarly, we can prove that $ E_0 $, $ E_1 $ and $ E_3 $ are isolated in $ D $.

    For $ E_4 $ and $ E_5 $, we have two cases: (A). $ R_1 < R_2 $ and $ R_1 \leq 1 $; (B). $ R_1 \geq R_2 $ or $ R_2 > R_1 > 1 $.

    (A). $ R_1 < R_2 $ and $ R_1 \leq 1 $

    If $ R_1 < R_2 $ and $ R_1 \leq 1 $, $ E_5 $ do not exist. Similar to the results of Lemma 2 (b), the boundary equilibrium point $ E_4 $ of model (1.2) is stable.

    (B). $ R_1 \geq R_2 $ or $ R_2 > R_1 > 1 $

    If $ x(t) = (S_1(t), I_1(t), S_2(t), I_2(t)) $ stays close to $ E_4 $, we have two cases: if $ I_1(0) = 0 $, then $ I_1(t) = 0 $; if $ I_1(0) > 0 $, then $ I_1(t) > 0 $. Since $ (S_1(t), I_1(t), S_2(t), I_2(t)) $ satisfying system (1.2) has no invariant subset other than $ E_4 $ in its neighborhood. $ E_4 $ is isolated in $ D $ and a uniform weak repeller for $ {\widetilde{D}}_2 $. Therefore, we can prove that $ E_0 $, $ E_1 $, $ E_2 $, $ E_3 $ and $ E_4 $ are isolated in $ D $.

    Using Proposition 4.3 in [5], we can prove that $ D_1 $ is a uniform weak repeller for $ {\widetilde{D}}_2 $; and using Theorem 4.5 in [5], we can prove that $ D_1 $ is a uniform strong repeller for $ {\widetilde{D}}_2 $.

    Then we get that there exists an $ \epsilon > 0 $ such that

    $ \lim inf_{t\rightarrow\infty} {min\{I_1(t), I_2(t)\}} \gt \epsilon, $

    with $ N_i(0) > 0 $ and $ I_i(0) > 0 $, $ i = 1, 2 $.

    Therefore, if $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $, $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $ and $ R_1 \geq R_2 $ ($ R_2 > R_1 > 1 $), there exists at least one internal equilibrium of system (1.2) [9,10,13].

    Next, we use Theorem 2 in [11] to discuss the basic reproduction number of system (1.2).

    The Jacobian matrix of $ (I_1, I_2) $ is

    $ J = \left(β11S1(s0+γ1)0β21S2β22S2(e2+γ2+d2)
    \right), $

    Let $ J = F-V $, $ F $ be the rate of appearance of new infections in compartment $ I $, $ V $ be the rate of transfer of individuals out of compartment $ I $. Then, we get

    $ F = \left(β11S10β21S2β22S2
    \right), $
    $ V = \ diag\left(s0+γ1e2+γ2+d2
    \right). $

    We call $ FV^{-1} $ be the next generation matrix for the model (1.2) and set $ R_s = \rho (FV^{-1} \big|_{E_3}) $, where $ \rho(A $) denotes the spectral radius of a matrix $ A $.

    Then we get

    $ R_s = \max \left\{ \frac{\beta _{11} N^*_1}{s_0 + \gamma _1 }, \frac{\beta _{22} N^*_2}{e_2+\gamma_2+d_2} \right\}. $

    Finally, using Theorem 2 in [11], we can prove Theorem 1.

    The basic reproduction number is an important threshold value in the research of the epidemic mathematical model, which determines the disease to break out or not. However, it is not sufficient to discuss the breed-slaughter model with interspecific interaction. The main purpose of this paper is to investigate invasion process of infected domestic animal into human habitat. And we construct a propagating terrace linking human habitat $ E_1 $ to animal-human coexistent habitat $ E_3 $, then to swine flu natural foci $ E_4 $ (or $ E_5 $), which is divided by certain spreading speeds. The propagating terrace can describe the spatio-temporal continuous change of the transmission of swine flu.

    Based on the heterogeneity of the population structure and the temporal and spatial continuity of the mammal movement, the population's spatial factor is considered in the spread of swine flu. If the swine flu host populations are distributed differently in space, the diffusion term may change their local population structure, thus change the swine flu epidemic. In order to describe the population invasion process, we set the initial value is zero in the area $ x \in (-\infty, - x_0) \cup (x_0, \infty) $. The area of $ (- x_0, x_0) $ is the original habitat of $ N $, and $ N $ will invade to the area of $ x \in (-\infty, - x_0) \cup (x_0, \infty) $ at the spreading speed $ s $ [14].

    The definition of spreading speed of a single population is the positive value $ s $ satisfied with the conditions as follows,

    $ \lim\limits_{t \to+\infty} \{\sup\limits_{\left| x \right| \gt ct} N(x, t)\} = 0, \forall c \gt s $

    and

    $ \lim\limits_{t \to+\infty} \inf \{\inf\limits_{\left| x \right| \lt ct} N(x, t)\} \gt 0, \forall c \lt s, $

    in the model [4.1]

    $ {N(x,t)t=D2N(x,t)x2+rN(x,t)(1N(x,t)K),xR,t>0,N(x,0)=N0>0,x[x0,x0],N(x,0)=0,x(,x0)(x0,).
    $
    (4.1)

    The biological description of spreading speed $ s $ has been shown in the third figure of Figure 3. The value of $ s $ approximates the inverse of the slope of the color lines. It is easy to see that the co-effect of diffusion and reproduction leads to the population territory expansion, in which the local diffusion rate $ D $ guarantees the population spatial invasion to new areas and the reproduction rate $ r $ guarantees its development on occupied areas. The spreading speed of a single population in the model [4.1] is expressed by $ s: = 2\sqrt{D r} $ by [14]. However, it is not enough to study the swine flu with more than one host species [15,16,17,18,19,20]. We redefine the spreading speeds at the human-animal interface, as shown below.

    $ s_1: = 2 \sqrt{D_1 (B_{12} K_2-s_0)}, $
    $ s_2: = \max \left\{ 2 \sqrt{D_1 (\beta_{11} N^*_1 - s_0-\gamma_1)}, 2 \sqrt{D_2 (\beta_{22} N^*_2 - e_2-\gamma_2-d_2)} \right\} . $
    Figure 3.  Effect of $ r $ and $ D $ on the local diffusion of a single population.

    Due to the participation of two populations, some notations need to be redefined. The notations $ s $ and $ x_0 $ are replaced by $ s_i $, $ x_i $, with $ i = 1, 2 $, corresponding to the two swine flu host populations.

    Then we construct a propagating terrace linking human habitat $ E_1 $ to animal-human coexistent habitat $ E_3 $, then to swine flu natural foci $ E_4 $ (or $ E_5 $), which is divided by certain spreading speeds. The propagating terrace can describe the spatio-temporal continuous change of the transmission of swine flu, which can be show in Theorem 2.

    Theorem 2. For system (1.1), if $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $, $ B_{21} N^*_1 < r_2 $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $, the initial conditions satisfy that $ 0 < S_1(x, 0) < N^*_1 $, $ x\in[-x_1, x_1] $; $ S_1(x, 0) = 0 $, $ x\in(-\infty, x_1)\cup(x_1, \infty) $, for some $ x_1 > 0 $; $ 0 < I_1(x, 0) < N^*_1 $, $ x\in[-x_2, x_2] $; $ I_1(x, 0) = 0 $, $ x\in(-\infty, x_2)\cup(x_2, \infty) $, for some $ x_2 > 0 $; $ S_2(x, 0) = K_2 $, $ I_2(x, 0) = 0 $, $ x\in {\mathbb{R}} $.

    We set

    $ s_1: = 2 \sqrt{D_1 (B_{12} K_2-s_0)}, s_2: = \max \left\{ 2 \sqrt{D_1 (\beta_{11} N^*_1 - s_0-\gamma_1)}, 2 \sqrt{D_2 (\beta_{22} N^*_2 - e_2-\gamma_2-d_2)} \right\} . $

    Suppose that $ s_1 > s_2 $, $ x_1 > x_2 $, then there are three cases about the invasion process as following:

    (a) $ R_s \leq 1 $,

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct} \left\{ \left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \lt s_1. $

    The system (1.1) forms a propagating terrace, linking $ E_1 $ to $ E_3 $.

    (b) If $ R_s > 1 $, $ R_1 < R_2 $ and $ R_1 \leq 1 $,

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{c_2 t \lt \left| x \right| \lt c_1 t } \left\{\left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall s_2 \lt c_2 \lt c_1 \lt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct} \left\{\left| {S_1 (x, t)-N'_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-S'_2} \right| + \left| {I_2 (x, t)-I'_2} \right| \right\} = 0, \ \ \forall c \lt s_2. $

    The system (1.1) forms a propagating terrace, linking $ E_1 $ to $ E_3 $, then to $ E_4 $.

    (c) If $ R_s > 1 $ and $ R_1 \geq R_2 $ (or $ R_2 > R_1 > 1 $),

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{c_2 t \lt \left| x \right| \lt c_1 t} \left\{\left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall s_2 \lt c_2 \lt c_1 \lt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct} \left\{\left| {S_1 (x, t)-S^*_1} \right| +\left| {I_1 (x, t)-I^*_1} \right| +\left| {S_2 (x, t)-S^*_2} \right| + \left| {I_2 (x, t)-I^*_2} \right| \right\} = 0, \ \ \forall c \lt s_2. $

    The system (1.1) forms a propagating terrace, linking $ E_1 $ to $ E_3 $, then to $ E_5 $.

    Proof. The epidemic of swine flu originates in the interaction between humans and domestic animals in the breeding process, so the breaking out of swine flu would lag behind this process. Therefore, we first confirm the propagating terrace linking $ E_1 $ and $ E_3 $.

    The breed-slaughter system without swine flu transmission can be transferred to model (4.2).

    $ {N1(x,t)t=D12N1(x,t)t2+(B12N2(x,t)ω0N1(x,t))N1(x,t)s0N1(x,t),N2(x,t)t=D22N2(x,t)t2+r2(1N2(x,t)K2)N2(t)+B21N1(x,t)N2(x,t).
    $
    (4.2)

    Let $ (N_1, N_2) $ be a solution to system (4.2) with the initial condition $ 0 < N_1(x, 0) < N^*_1 $, $ x\in[-x_1, x_1] $; $ N_1(x, 0) = 0 $, $ x\in(-\infty, x_1)\cup(x_1, \infty) $, for some $ x_1 > 0 $; $ N_2(x, 0) = K_2 $, $ x\in {\mathbb{R}} $.

    If $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $, we claim that $ (N_1(x, t), N_2(x, t)) \in \Sigma $, $ \forall x \in {\mathbb{R}}, t \in [0, \infty) $, where

    $ \Sigma: = \{ (N_1, N_2) \in [0, N^*_1] \times [0, N^*_2]: B_{12} N_2 (x, t) - \omega_0 N_1 (x, t) - s_0 \geq 0, r_2 (1- \frac{N_2 (x, t)}{K_2} )+ B_{21} N_1(x, t)\geq0 \}. $

    By the strong maximum principle, $ N_1\geq0 $ for $ t > 0 $. Then we get

    $ \frac{\partial N_2(x, t)}{\partial t} \geq D_2 \frac{\partial^2 N_2(x, t)}{\partial t^2} + r_2 (1- \frac{N_2 (x, t)}{K_2} ) N_2(x, t) . $

    By a comparison, $ N_2\geq X $, where $ X $ is the solution to

    $ {X(x,t)t=D22X(x,t)t2+r2(1X(x,t)K2)X(x,t),X(x,0)=N2(x,0).
    $
    (4.3)

    Then we get the result

    $ {\lim\limits_{t \to+ \infty } \inf {N_2 (x, t)}} \geq {\lim\limits_{t \to+ \infty } \inf {X (x, t)}} = K_2. $

    Set $ u: = N_1 $ and $ v: = N_2-K_2 $. Then $ \frac{\partial N_2(x, t)}{\partial t} $ can be rewritten as

    $ \frac{\partial v(x, t)}{\partial t} = D_2 \frac{\partial^2 v(x, t)}{\partial t^2} - r_2 \frac{v (x, t)}{K_2} (v(x, t)+K_2) + B_{21} u(x, t) (v (x, t)+K_2). $

    Due to $ u = N_1 \in [0, N^*_1] $ and $ v = N_2-K_2 \geq 0 $ then

    $ \frac{\partial v(x, t)}{\partial t} \leq D_2 \frac{\partial^2 v(x, t)}{\partial t^2} - (r_2 - B_{21} N^*_1 ) v (x, t) + B_{21} K_2 u(x, t). $

    By the strong maximum principle, if follows that $ v \leq Y $ in $ {\mathbb{R}} \times [0, \infty) $, where $ Y $ is the solution to

    $ {Y(x,t)t=D22Y(x,t)t2(r2B21N1)Y(x,t)+B21K2u(x,t),X(x,0)=0,xR.
    $
    (4.4)

    Then we have

    $ Y(x, t) = B_{21} K_2 \int_{0}^{t} \left\{ e^{-(r_2- B_{21} N^*_1) (t-s)} \int_{{\mathbb{R}}} e^{-(x-y)^2 / [ 4 (t-s) ]} u(y, s) dy \right\} ds. $

    Given $ \epsilon > 0 $, we choose $ \delta > 0 $ small enough such that $ 2 \sqrt{D_1 (B_{12} K_2-s_0+B_{12} \delta)} < s_1 + \epsilon $.

    For this $ \delta $, we claim that there is $ \tau \gg 1 $ such that $ Y(x, t) < \delta+ M u(x, t) $, $ \forall x \in {\mathbb{R}} $, $ t\geq \tau $, for some positive constant $ M $. Then it follows that $ N_1 $ satisfies

    $ \frac{\partial N_1(x, t)}{\partial t} \leq D_1 \frac{\partial^2 N_1(x, t)}{\partial t^2} + (B_{12} K_1 -s_0 + B_{12} \delta- (B_{12}M+\omega_0) N_1 (x, t)) N_1(x, t). $

    Therefore, according to the comparison principle and the definition of spreading speed [14,15,16,19,21], for any $ c \in (2 \sqrt{D_1 (B_{12} K_2-s_0+B_{12} \delta)}, s_1 + \epsilon) $, it follows that $ {\lim_{t \to+ \infty } \sup_{\left| x \right| > ct} {N_1 (x, t)}} = 0 $, and then $ {\lim_{t \to+ \infty } \sup_{\left| x \right| > ct} {N_2 (x, t)}} = K_2 $.

    Because of the arbitrariness of $ \epsilon $, we get

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct} \left\{\left| {N_1 (x, t)} \right| +\left| {N_2 (x, t)-K_2} \right| \right\} = 0, \forall c \gt s_1. $

    Thus, if the swine flu does not break out, namely $ R_s \leq 1 $, for system (1.1),

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1. $

    Then we set $ U: = N^*_1-N_1 $ and $ V: = N^*_2-N_2 $. Similar to the proof before, we can get

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct} \left\{\left| {N_1 (x, t)-N^*_1} \right| +\left| {N_2 (x, t)-N^*_2} \right| \right\} = 0, \ \ \forall c \lt s_1. $

    If $ R_s \leq 1 $, for system (1.1),

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct} \left\{ \left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \lt s_1. $

    Next we consider the propagating terrace linking $ E_3 $ to ($ E_4 $ or $ E_5 $). Let $ (S_1, I_1, S_2, I_2) $ be a solution to system (1.1) with the initial condition $ S_1(x, 0) = N^*_1 $, $ S_2(x, 0) = N^*_2 $, $ I_2(x, 0) = 0 $, $ x\in {\mathbb{R}} $. $ I_1(x, 0) > 0 $, $ x\in[-x_2, x_2] $; $ I_1(x, 0) = 0 $, $ x\in(-\infty, x_2)\cup(x_2, \infty) $, for some $ x_2 > 0 $.

    If $ B_{12} B_{21} < \frac{\omega_0 r_2}{K_2} $ and $ s_0 < \min \left\{ \frac{\omega_0 r_2}{B_{21}}, B_{12} K_2 \right\} $, we claim that $ (S_1(x, t)+I_1(x, t), S_2(x, t)+I_2(x, t)) \in \Sigma $, $ \forall x \in {\mathbb{R}}, t \in [0, \infty) $.

    For the spreading speed when $ R_s > 1 $, comparison principle and strong maximum principle are no longer applicable due to the complexity of system (1.1). However, we can calculate the minimum wave speed from largest eigenvalue of its linearized system at $ E_3 $ as [22] to link $ E_3 $ and $ E_4 $ (or $ E_5 $).

    For the following eigenvalue problem

    $ \frac{1}{\lambda} A_\lambda \eta_\lambda = c \eta_\lambda, $

    where

    $ A_\lambda = diag (D_i \lambda^2) +J \big|_{E_3}. $

    J is the jacobian matrix,

    $ J = \left(B12N22ω0N1s0β11I1β11S1+γ1B12N10β11I1β11S1(s0+γ1)00B12N2β21S2r2(12N2K2)+B21N1(β21I1+β22I2)β22S2+γ20β21S2β21I1+β22I2β22S2(e2+γ2+d2)
    \right). $

    For $ \lambda \geq 0 $, the eigenvalues of the matrix

    $ A_\lambda = \left(D1λ2ω0N1β11N1+γ1B12N100D1λ2+β11N1(s0+γ1)00B12N2β21N2D2λ2r2N2K2β22N2+γ20β21N20D2λ2+β22N2(e2+γ2+d2)
    \right). $

    are $ D_1 \lambda^2 + \beta_{11} N^*_1-(s_1+\gamma_1) $, $ D_2 \lambda^2 +\beta_{22}N^*_2-(e_2+\gamma_2+d_2) $ and other two impossible results, which cannot define positive wave speed.

    Thus, the minimum wave speed can be defined as follows, which can be divided the propagating terrace, linking $ E_3 $ to $ E_4 $ (or $ E_5 $).

    $ s2=max{infλ>0D1λ2+β11N1(s0+γ1)λ,infλ>0D2λ2+β22N2(e2+γ2+d2)λ}=max{2D1(β11N1s0γ1),2D2(β22N2e2γ2d2)}.
    $

    If $ R_s > 1 $, there are two cases: (A). $ R_1 < R_2 $ and $ R_1 \leq 1 $; (B). $ R_1 \geq R_2 $ or $ R_2 > R_1 > 1 $.

    (A). If $ R_1 < R_2 $ and $ R_1 \leq 1 $, then $ E_5 $ does not exist. $ s_2 = 2 \sqrt{D_2 (\beta_{22} N^*_2 - e_2-\gamma_2-d_2)} $, then we get

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt c_2 t + x_2} \left\{\left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_2, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct+x_2} \left\{\left| {S_1 (x, t)-N'_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-S'_2} \right| + \left| {I_2 (x, t)-I'_2} \right| \right\} = 0, \ \ \forall c \lt s_2. $

    Combining the results before, linking $ E_1 $ to $ E_3 $, then

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct+x_1} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{c_2 t+x_2 \lt \left| x \right| \lt c_1 t + x_1} \left\{\left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall s_2 \lt c_2 \lt c_1 \lt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct+x_2} \left\{\left| {S_1 (x, t)-N'_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-S'_2} \right| + \left| {I_2 (x, t)-I'_2} \right| \right\} = 0, \ \ \forall c \lt s_2. $

    The system (1.1) forms a propagating terrace, linking $ E_1 $ to $ E_3 $, then to $ E_4 $.

    (B). If $ R_1 \geq R_2 $ or $ R_2 > R_1 > 1 $, set $ s_2 = \max \left\{ 2 \sqrt{D_1 (\beta_{11} N^*_1 - s_0-\gamma_1)}, 2 \sqrt{D_2 (\beta_{22} N^*_2 - e_2-\gamma_2-d_2)} \right\} $. then we get

    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \gt ct+x_1} \left\{\left| {S_1 (x, t)} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-K_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall c \gt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{c_2 t+x_2 \lt \left| x \right| \lt c_1 t+x_1} \left\{\left| {S_1 (x, t)-N^*_1} \right| +\left| {I_1 (x, t)} \right| +\left| {S_2 (x, t)-N^*_2} \right| + \left| {I_2 (x, t)} \right| \right\} = 0, \ \ \forall s_2 \lt c_2 \lt c_1 \lt s_1, $
    $ \lim\limits_{t \to+ \infty } \sup\limits_{\left| x \right| \lt ct+x_2} \left\{\left| {S_1 (x, t)-S^*_1} \right| +\left| {I_1 (x, t)-I^*_1} \right| +\left| {S_2 (x, t)-S^*_2} \right| + \left| {I_2 (x, t)-I^*_2} \right| \right\} = 0, \ \ \forall c \lt s_2. $

    The system (1.1) forms a propagating terrace, linking $ E_1 $ to $ E_3 $, then to $ E_5 $.

    If $ s_1 > s_2 $, $ x_1 > x_2 $ and $ R_s > 1 $, $ R_1 > R_2 > 1 $, then in Figure 4, the blue area represents the original habitat area of humans at the population size of $ E_1 $. After domesticating pigs, the red part will be shared with the two species at $ E_3 $. While after swine flu transmitting between domestic pigs and humans, the internal red part will be shared again with two populations at $ E_5 $ with swine flu transmission. It is a biological description of propagating terrace of humans with swine flu transmission, which is the local spacial variation of the population.

    Figure 4.  If $ R_s > 1 $, $ R_1 > R_2 > 1 $, the propagating terrace from $ E_1 $ to $ E_3 $, then to $ E_5 $. (a): The simulation of $ N_2 $; (b): Contour line of $ N_2 $.

    If $ s_1 > s_2, x_1 > x_2 $ and $ R_s \leq 1 $, then in Figure 5, the blue area represents the original habitat area of humans at the population size of $ E_1 $. After domesticating pigs, the red part will be shared with the two species at $ E_3 $. Because $ R_s \leq 1 $, there is no swine flu transmission during the breed and slaughter process. Then the propagating terrace links unstable equilibrium $ E_1 $ and stable equilibrium $ E_2 $.

    Figure 5.  If $ R_s \leq 1 $, the propagating terrace from $ E_1 $ to $ E_3 $. (a): The simulation of $ N_2 $; (b): Contour line of $ N_2 $.

    We establish a new swine flu mathematical model to reflect the dynamic process of swine flu transmission with interspecific action between domestic pigs and humans, in which the roles of different species will no longer be at the same level. Domestic pigs cannot survive independently without human beings, but human beings can still survive well without the supply of pork. By our new swine flu model, we find that the human-animal interface has promoted the cross-species transmission of swine flu and resulted in the prevalence of flu in humans. In addition, the threshold values of population development and disease transmission are also discussed in order to provide a scientific basis for future health decision makers in swine flu prevention and control. We propose the zoonotic basic reproduction number $ R_s $, which is more applicable to the study of swine flu transmission. Then, it is analyzed that the spreading speed of different species forming propagating terraces is influenced by the intrinsic growth rate $ r $ and diffusion rate $ D $.

    In this paper, the equilibrium points of the model are calculated and we analyze the existence of the equilibrium points by the persistence theory. Then we discuss their stability by the basic reproduction number. In addition, after redefining the spreading speed, we divide the propagating terrace with two populations, which is an unprecedented task. We concern with the invasion process of infected domestic animals into the habitat of humans. Under certain conditions as in Theorem 2, we construct a propagating terrace linking human habitat to animal-human coexistent habitat, then to swine flu natural foci, which is divided by spreading speeds.

    This work is supported by the National Natural Science Foundation of China, 11771044.

    The authors declared that they have no conflicts of interest to this work.

    [1] M. K. Banda, M. Herty and A. Klar, Coupling conditions for gas networks governed by the isothermal Euler equations, Networks and Heterogenous Media, 1 (2006), 295-314. doi: 10.3934/nhm.2006.1.295
    [2] A. Bressan, S. Canic, M. Garavello, M. Herty and B. Piccoli, Flows on networks: recent results and perspectives, EMS Reviews in Mathematical Sciences, 1 (2014), 47-111. doi: 10.4171/EMSS/2
    [3] R. Carvalho, L. Buzna, F. Bono, M. Masera, D. K. Arrowsmith and D. Helbing, Resilience of natural gas networks during conflicts, crises and disruptions, PLOS ONE, 9 (2014), e0090265. doi: 10.1371/journal.pone.0090265
    [4] F. Chapeau-Blondeau, Numerical evaluation of the lambert W function and application to generation of generalized Gaussian noise with exponent 1/2, IEEE Transactions on Signal Processing, 50 (2002), 2160-2165. doi: 10.1109/TSP.2002.801912
    [5] R. M. Colombo and F. Marcellini, Smooth and discontinuous junctions in the p-system, Journal of Mathematical Analysis and Applications, 361 (2010), 440-456. doi: 10.1016/j.jmaa.2009.07.022
    [6] R. M. Colombo, G. Guerra, M. Herty and V. Schleper, Optimal control in networks of pipes and canals, SIAM J. Control Optim., 48 (2009), 2032-2050. doi: 10.1137/080716372
    [7] R. M. Corless, G. H. Gonnet, D. E. G. Hare, D. J. Jeffrey and D. E. Knuth, On the Lambert W function, Adv. Comp. Math., 5 (1996), 329-359. doi: 10.1007/BF02124750
    [8] J.-M. Coron, B. d'Andrea-Novel and G. Bastin, A strict Lyapunov function for boundary control of hyperbolic systems of conservation laws, IEEE Trans. Automat. Control, 52 (2007), 2-11. doi: 10.1109/TAC.2006.887903
    [9] M. Dick, M. Gugat and G. Leugering, Classical solutions and feedback stabilization for the gas flow in a sequence of pipes, Networks and Heterogeneous Media, 5 (2010), 691-709. doi: 10.3934/nhm.2010.5.691
    [10] M. Garavello and B. Piccoli, Conservation laws on complex networks, Annales de l'Institut Henri Poincare (C) Non Linear Analysis, 26 (2009), 1925-1951. doi: 10.1016/j.anihpc.2009.04.001
    [11] M. Gugat, M. Dick and G. Leugering, Gas flow in fan-shaped networks: Classical solutions and feedback stabilization, SIAM Journal on Control and Optimization, 49 (2011), 2101-2117. doi: 10.1137/100799824
    [12] M. Gugat and M. Herty, Existence of classical solutions and feedback stabilization for the flow in gas networks, ESAIM: Control, Optimisation and Calculus of Variations, 17 (2011), 28-51. doi: 10.1051/cocv/2009035
    [13] M. Gugat, M. Herty and V. Schleper, Flow control in gas networks: Exact controllability to a given demand, Mathematical Methods in the Applied Sciences, 34 (2011), 745-757. doi: 10.1002/mma.1394
    [14] M. Herty, Modeling, simulation and optimization of gas networks with compressors, Networks and Heterogeneous Media, 2 (2007), 81-97. doi: 10.3934/nhm.2007.2.81
    [15] J. H. Lambert, Observationes variae in mathesin puram, Acta Helvetica, physico-mathematico-anatomico-botanico-medica, 3 (1758), 128-168.
    [16] T. Li, B. Rao and Z. Wang, Exact boundary controllability and observability for first order quasilinear hyperbolic systems with a kind of nonlocal boundary conditions, Discrete Contin. Dyn. Syst., 28 (2010), 243-257. doi: 10.3934/dcds.2010.28.243
    [17] A. Martin, M. Möller and S. Moritz, Mixed integer models for the stationary case of gas network optimization, Mathematical Programming, 105 (2005), 563-582. doi: 10.1007/s10107-005-0665-5
    [18] G. A. Reigstad, Numerical network models and entropy principles for isothermal junction flow, Networks and Heterogeneous Media, 9 (2014), 65-95. doi: 10.3934/nhm.2014.9.65
    [19] V. Schleper, M. Gugat, M. Herty, A. Klar and G. Leugering, Well-posedness of networked hyperbolic systems of balance laws, in Constrained Optimization and Optimal Control for Partial Differential Equations, International Series of Numerical Mathematics, 160, Birkhäuser/Springer Basel AG, Basel, 2012, 123-146. doi: 10.1007/978-3-0348-0133-1_7
    [20] arXiv:1003.1628
    [21] G. P. Zou, N. Cheraghi and F. Taheri, Fluid-induced vibration of composite natural gas pipelines, International Journal of Solids and Structures, 42 (2005), 1253-1268. doi: 10.1016/j.ijsolstr.2004.07.001
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