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Convexity and starshapedness of feasible sets in stationary flow networks

  • Received: 01 January 2019 Revised: 01 October 2019 Published: 01 June 2020
  • Primary: 90C15; Secondary: 93E20

  • In this paper, we consider a stationary model for the flow through a network. The flow is determined by the values at the boundary nodes of the network. We call these values the loads of the network. In the applications, the feasible loads must satisfy some box constraints. We analyze the structure of the set of feasible loads. Our analysis is motivated by gas pipeline flows, where the box constraints are pressure bounds.

    We present sufficient conditions that imply that the feasible set is star-shaped with respect to special points. Under stronger conditions, we prove the convexity of the set of feasible loads. All the results are given for passive networks with and without compressor stations.

    This analysis is motivated by the aim to use the spheric-radial decomposition for stochastic boundary data in this model. This paper can be used for simplifying the algorithmic use of the spheric-radial decomposition.

    Citation: Martin Gugat, Rüdiger Schultz, Michael Schuster. Convexity and starshapedness of feasible sets in stationary flow networks[J]. Networks and Heterogeneous Media, 2020, 15(2): 171-195. doi: 10.3934/nhm.2020008

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  • In this paper, we consider a stationary model for the flow through a network. The flow is determined by the values at the boundary nodes of the network. We call these values the loads of the network. In the applications, the feasible loads must satisfy some box constraints. We analyze the structure of the set of feasible loads. Our analysis is motivated by gas pipeline flows, where the box constraints are pressure bounds.

    We present sufficient conditions that imply that the feasible set is star-shaped with respect to special points. Under stronger conditions, we prove the convexity of the set of feasible loads. All the results are given for passive networks with and without compressor stations.

    This analysis is motivated by the aim to use the spheric-radial decomposition for stochastic boundary data in this model. This paper can be used for simplifying the algorithmic use of the spheric-radial decomposition.



    Fractional differential equations (FDEs) appeared as an excellent mathematical tool for, modeling of many physical phenomena appearing in various branches of science and engineering, such as viscoelasticity, statistical mechanics, dynamics of particles, etc. Fractional calculus is a recently developing work in mathematics which studies derivatives and integrals of functions of fractional order [26].

    The most used fractional derivatives are the Riemann-Liouville (RL) and Caputo derivatives. These derivatives contain a non-singular derivatives but still conserves the most important peculiarity of the fractional operators [1,2,10,11,23,24]. Atangana and Baleanu described a derivative with a generalized Mittag-leffler (ML) function. This derivative is often called the Atangana-Baleanu (AB) fractional derivative. The AB-derivative in the senses of Riemman-Liouville and Caputo are denoted by ABR-derivative and ABC-derivative, respectively.

    The AB fractional derivative is a nonlocal fractional derivative with nonsingular kernel which is connected with various applications [3,5,6,8,9,13,14,15,16]. Using the advantage of the non-singular ML kernal present in the AB fractional derivatives, operators, many authors from various branches of applied mathematics have developed and studied mathematical models involving AB fractional derivatives [18,22,29,30,31,32,35,36,37].

    Mohamed et al. [25] considered a system of multi-derivatives for Caputo FDEs with an initial value problem, examined the existence and uniqueness results and obtained numerical results. Sutar et al. [32,33] considered multi-derivative FDEs involving the ABR derivative and examined existence, uniqueness and dependence results. Kucche et al. [12,19,20,21,34] enlarged the work of multi-derivative fractional differential equations involving the Caputo fractional derivative and studied the existence, uniqueness and continuous dependence of the solution.

    Inspired by the preceding work, we perceive the multi-derivative nonlinear neutral fractional integro-differential equation with AB fractional derivative of the Riemann-Liouville sense of the problem:

    dVdȷ+0Dδȷ[V(ȷ)x(ȷ,y(ȷ))]=φ(ȷ,V(ȷ),ȷ0K(ȷ,θ,V(θ))dθ,T0χ(ȷ,θ,V(θ))dθ),ȷI (1.1)
    V(0)=V0R, (1.2)

    where 0Dδȷ denotes the ABR fractional derivative of order δ(0,1), and φC(I×R×R×R,R) is a non-linear function. Let P1V(ȷ)=ȷ0K(ȷ,θ,V(θ))dθ and P2V(ȷ)=T0χ(ȷ,θ,V(θ))dθ. Now, (1.1) becomes,

    dVdȷ+0Dδȷ[V(ȷ)x(ȷ,y(ȷ))]=φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ)),ȷI, (1.3)
    V(0)=V0R. (1.4)

    In this work, we derive a few supplemental results using the characteristics of the fractional integral operator εαδ,η,V;c+. The existence results are obtained by Krasnoselskii's fixed point theorem and the uniqueness and data dependence results are obtained by the Gronwall-Bellman inequality.

    Definition 2.1. [14] The Sobolev space Hq(X) is defined as Hq(X)={φL2(X):DβφL2(X),|β|q}. Let q[1,) and X be open, XR.

    Definition 2.2. [11,17] The generalized ML function Eαδ,β(u) for complex δ,β,α with Re(δ)>0 is defined by

    Eαδ,β(u)=t=0(α)tα(δt+β)utt!,

    and the Pochhammer symbol is (α)t, where (α)0=1,(α)t=α(α+1)...(α+t1), t=1,2...., and E1δ,β(u)=Eδ,β(u),E1δ,1(u)=Eδ(u).

    Definition 2.3. [4] The ABR fractional derivative of V of order δ is

    0Dδȷ[V(ȷ)x(ȷ,y(ȷ))]=B(δ)1δddȷȷ0Eδ[δ1δ(ȷθ)δ]V(θ)dθ,

    where VH1(0,1), δ(0,1), B(δ)>0. Here, Eδ is a one parameter ML function, which shows B(0)=B(1)=1.

    Definition 2.4. [4] The ABC fractional derivative of V of order δ is

    0Dδȷ[V(ȷ)x(ȷ,y(ȷ))]=B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ]V(θ)dθ,

    where VH1(0,1), δ(0,1), and B(δ)>0. Here, Eδ is a one parameter ML function, which shows B(0)=B(1)=1.

    Lemma 2.5. [4] If L{g(ȷ);b}=ˉG(b), then L{0Dδȷg(ȷ);b}=B(δ)1δbδˉG(b)bδ+δ1δ.

    Lemma 2.6. [26] L[ȷmδ+β1E(m)δ,β(±aȷδ);b]=m!bδβ(bδ±a)m+1,Em(ȷ)=dmdȷmE(ȷ).

    Definition 2.7. [17,27] The operator εαδ,η,V;c+ on class L(m,n) is

    (εαδ,η,V;c+)[V(ȷ)x(ȷ,y(ȷ))]=t0(ȷθ)α1Eαδ,η[V(ȷθ)δ]Θ(θ)dθ,ȷ[c,d],

    where δ,η,V,αC(Re(δ),Re(η)>0), and n>m.

    Lemma 2.8. [17,27] The operator εαδ,η,V;c+ is bounded on C[m,n], such that (εαδ,η,V;c+)[V(ȷ)x(ȷ,y(ȷ))]PΘ, where

    P=(nm)Re(η)t=0|(α)t||α(δt+η)|[Re(δ)t+Re(η)]|V(nm)Re(δ)|tt!.

    Here, δ,η,V,αC(Re(δ),Re(η)>0), and n>m.

    Lemma 2.9. [17,27] The operator εαδ,η,V;c+ is invertible in the space L(m,n) and φL(m,n) its left inversion is given by

    ([εαδ,η,V;c+]1)[V(ȷ)x(ȷ,y(ȷ))]=(Dη+ςc+εαδ,η,V;c+)[V(ȷ)x(ȷ,y(ȷ))],ȷ(m,n],

    where δ,η,V,αC(Re(δ),Re(η)>0), and n>m.

    Lemma 2.10. [17,27] Let δ,η,V,αC(Re(δ),Re(η)>0),n>m and suppose that the integral equation is

    ȷ0(ȷθ)α1Eαδ,η[V(ȷθ)δ]Θ(θ)dθ=φ(ȷ),ȷ(m,n],

    is solvable in the space L(m,n).Then, its unique solution Θ(ȷ) is given by

    Θ(ȷ)=(Dη+ςc+εαδ,η,V;c+)[V(ȷ)x(ȷ,y(ȷ))],ȷ(m,n].

    Lemma 2.11. [7] (Krasnoselskii's fixed point theorem) Let A be a Banach space and X be bounded, closed, convex subset of A. Let F1,F2 be maps of S into A such that F1V+F2φX V,φU. The equation F1V+F2V=V has a solution on S, and F1, F2 is a contraction and completely continuous.

    Lemma 2.12. [28] (Gronwall-Bellman inequality) Let V and φ be continuous and non-negative functions defined on I. Let V(ȷ)A+ȷaφ(θ)V(θ)dθ,ȷI; here, A is a non-negative constant.

    V(ȷ)Aexp(ȷaφ(θ)dθ),ȷI.

    In this part, we need some fixed-point-techniques-based hypotheses for the results:

    (H1) Let VC[0,T], function φ(C[0,T]×R×R×R,R) is a continuous function, and there exist +ve constants ζ1,ζ2 and ζ. φ(ȷ,V1,V2,V3)φ(ȷ,φ1,φ2,φ3)ζ1(V1φ1+V2φ2+V3φ3) for all V1,V2,V3,φ1,φ2,φ3 in Y, ζ2=maxVRf(ȷ,0,0,0), and ζ=max{ζ1,ζ2}.

    (H2) P1 is a continuous function, and there exist +ve constants C1,C2 and C. P1(ȷ,θ,V1)P1(ȷ,θ,φ1)C1(V1φ1)V1,φ1 in Y, C2=max(ȷ,θ)DP1(ȷ,θ,0), and C=max{C1,C2}.

    (H3) P2 is a continuous function and there are +ve constants D1,D2 and D. P2(ȷ,θ,V1)P2(ȷ,θ,φ1)D1(V1φ1) for all V1,φ1 in Y, D2=max(ȷ,θ)DP2(ȷ,θ,0) and D=max{D1,D2}.

    (H4) Let xc[0,I], function u(c[0,I]×R,R) is a continuous function, and there is a +ve constant k>0, such that u(ȷ,x)u(ȷ,y)kxy. Let Y=C[R,X] be the set of continuous functions on R with values in the Banach space X.

    Lemma 2.13. If (H2) and (H3) are satisfied the following estimates, P1V(ȷ)ȷ(C1V+C2),P1V(ȷ)P1φ(ȷ)CȷVφ, and P2V(ȷ)ȷ(D1V+D2),P2V(ȷ)P2φ(ȷ)DȷVφ.

    Theorem 3.1. The function φC(I×R×R×R,R) and VC(I) is a solution for the problem of Eqs (1.3) and (1.4), iff V is a solution of the fractional equation

    V(ȷ)=V0B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ+ȷ0φ(θ,V(θ),P1V(θ),P2V(θ))dθ,ȷI. (3.1)

    Proof. (1) By using Definition 2.3 and Eq (1.3), we get

    ddȷ(V(ȷ)+B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ)=φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ)).

    Integrating both sides of the above equation with limits 0 to ȷ, we get

    V(ȷ)+B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθV(0)=ȷ0φ(θ,V(θ),P1V(θ),P2V(θ))dθ,ȷI.

    Conversely, with differentiation on both sides of Eq (3.1) with respect to ȷ, we get

    dVdȷ+B(δ)1δddȷȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ=φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ)),ȷI.

    Using Definition 2.3, we get Eq (1.3) and substitute ȷ=0 in Eq (3.1), we get Eq (1.4).

    Proof. (2) In Equation (1.3), taking the Laplace Transform on both sides, we get

    L[V(ȷ);b]+L[0Dδȷ;b][V(ȷ)x(ȷ,y(ȷ))]=L[φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ));b].

    Now, using the Laplace Transform formula for the AB fractional derivative of the RL sense, as given in Lemma 2.5, we get

    bˉX(b)[V(ȷ)x(ȷ,y(ȷ))]V(0)+B(δ)1δbδˉX(b)bδ+δ1δ=ˉG(b),

    ˉX(b)=[V(ȷ);b] and ˉG(b)=L[φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ));b]. Using Eq (1.4), we get

    ˉX(b)=V01bB(δ)1δbδ1ˉX(b)bδ+δ1δ[V(ȷ)x(ȷ,y(ȷ))]+1bˉG(b). (3.2)

    In Eq (3.2) applying the inverse Laplace Transform on both sides using Lemma 2.6 and the convolution theorem, we get

    L1[ˉX(b);ȷ]=V0L1[1b;ȷ]B(δ)1δ(L1[bδ1bδ+δ1δ][V(ȷ)x(ȷ,y(ȷ))]L1[ˉX(b);ȷ])+L1[ˉG(b);ȷ]L1[1b;ȷ]=V0B(δ)1δ(Eδ[δ1δȷδ][V(ȷ)x(ȷ,y(ȷ))])+φ(ȷ,V(ȷ),P1V(ȷ),P2V(ȷ))=V0B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ+ȷ0φ(θ,V(θ),P1V(θ),P2V(θ))dθ.V(ȷ)=V0B(δ)1δȷ0Eδ[δ1δ(ȷθ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ+ȷ0φ(θ,V(θ),P1V(θ),P2V(θ))dθ. (3.3)

    Theorem 3.2. Let δ(0,1). Define the operator F on C(I):

    (FV)(ȷ)=V0B(δ)1δ(ε1δ,1,δ1δ;0+)[V(ȷ)x(ȷ,y(ȷ))],VC(I). (3.4)

    (A) F is a bounded linear operator on C(I).

    (B) F satisfying the hypotheses.

    (C) F(X) is equicontinuous, and X is a bounded subset of C(I).

    (D) F is invertible, function φC(I), and the operator equation FV=φ has a unique solution in C(I).

    Proof. (A) From Definition 2.7 and Lemma 2.8, the fractional integral operator ε1δ,1,δ1δ;0+ is a bounded linear operator on C(I), such that

    ε1δ,1,δ1δ;0+[V(ȷ)x(ȷ,y(ȷ))]PV,ȷI,where
    P=Tn=0(1)nα(δn+1)(δn+1)|δ1δTδ|nn!=Tn=0(δ1δ)nTδnα(δn+2)=TEδ,2(δ1δTδ),

    and we have

    FV=|B(δ)1δ|ε1δ,1,δ1δ;0+[V(ȷ)x(ȷ,y(ȷ))]PB(δ)1δV,VC(I). (3.5)

    Thus, FV=φ is a bounded linear operator on C(I).

    (B) We consider V,φC(I). By using linear operator F and bounded operator ε1δ,1,δ1δ;0+, for any ȷI,

    |(FV)(ȷ)(Fφ)(ȷ)|=|F(Vφ)[V(ȷ)x(ȷ,y(ȷ))]|B(δ)1δ(ε1δ,1,δ1δ;0+Vφ)[V(ȷ)x(ȷ,y(ȷ))]PB(δ)1δVφ.

    Where, P=TEδ,2(δ1δTδ), then the operator F is satisfied the hypotheses with constant PB(δ)1δ.

    (C) Let U={VC(I):VR} be a bounded and closed subset of C(I), VU, and ȷ1,ȷ2I with ȷ1ȷ2.

    |(FV)(ȷ1)(FV)(ȷ2)|=|B(δ)1δ(ε1δ,1,δ1δ;0+)[V(ȷ1)u(l1,x(l))]B(δ)1δ(ε1δ,1,δ1δ;0+)[V(ȷ2)u(l2,x(l))]|B(δ)1δ|ȷ10{Eδ[δ1δ(ȷ1θ)δ]Eδ[δ1δ(ȷ2θ)δ]}[V(ȷ)x(ȷ,y(ȷ))]dθ|+B(δ)1δ|ȷ2ȷ1Eδ[δ1δ(ȷ2θ)δ][V(ȷ)x(ȷ,y(ȷ))]dθ|B(δ)1δn=0|(δ1δ)n|1α(nδ+1)ȷ10|(ȷ1θ)nδ(ȷ2θ)nδ||[V(ȷ)x(ȷ,y(ȷ))]|dθ+B(δ)1δn=0|(δ1δ)n|1α(nδ+1)ȷ2ȷ1|(ȷ2θ)nδ||[V(ȷ)x(ȷ,y(ȷ))]|dθLB(δ)1δn=0(δ1δ)n1α(nδ+1)ȷ10(ȷ2θ)nδ(ȷ1θ)nδdθ+LB(δ)1δn=0(δ1δ)n1α(nδ+1)ȷ2ȷ1(ȷ2θ)nδdθRB(δ)1δn=0(δ1δ)n1α(nδ+1){(ȷ2ȷ1)nδ+1+ȷnδ+12ȷnδ+11+(ȷ2ȷ1)nδ+1}RB(δ)1δn=0(δ1δ)n1α(nδ+2){ȷnδ+12ȷnδ+11}|(FV)(ȷ1)(FV)(ȷ2)|RB(δ)1δn=0(δ1δ)n1α(nδ+2){ȷnδ+12ȷnδ+11}. (3.6)

    Hence, if |ȷ1ȷ2|0 then |(FV)(ȷ1)(FV)(ȷ2)|0.

    is equicontinuous on

    (D) By Lemmas 2.9 and 2.10, , and we get

    (3.7)

    By Eqs (3.4) and (3.5), we have

    where with . This shows is invertible on and

    has the unique solution,

    (3.8)

    Theorem 4.1. Let . Then, the ABR derivative , is solvable in ), and the solution in is

    (4.1)

    where , and .

    Proof. The corresponding fractional equation of the ABR derivative

    is given by

    Using operator of Eq (3.4), we get

    (4.2)

    Equations (3.7) and (4.2) are solvable, and we get

    (4.3)

    Theorem 4.2. Let satisfy with where , if . Then problem of (1.3) and (1.4) has a solution in provided

    (4.4)

    Proof. Define

    where Let . Consider and given as

    Let is the fractional Eq (3.1) to the problems (1.3) and (1.4).

    Hence, the operators and satisfy the Krasnoselskii's fixed point theorem.

    Step (ⅰ) is a contraction.

    By on , and ,

    (4.5)

    This gives,

    Step (ⅱ) is completely continuous. By using Theorem 3.3 and Ascoli-Arzela theorem, is completely continuous.

    Step (ⅲ) , for any , using Theorem 3.3, we obtain

    (4.6)

    By definition of , we get

    (4.7)

    Using the Eq (4.5) in (4.7), we get condition of Eq (4.4).

    (4.8)

    This gives, ,

    From Steps (ⅰ)–(ⅲ), all the conditions of Lemma 2.11 follow.

    Theorem 4.3. By Theorem 4.2, the Eqs (1.3) and (1.4) have a unique solution in

    Proof. (1) The problems (1.3) and (1.4) have an operator equation form as:

    (4.9)

    where,

    By Theorem 4.2, Eq (4.7) is solvable in , by Lemma 2.10 we get a unique solution of Eqs (1.3) and (1.4),

    Proof. (2) Let be solutions of Eqs (1.3) and (1.4). By fractional integral operators and we find, for any ,

    (4.10)

    Theorem 5.1. By Theorem 4.2, if is a solution of Eqs (1.3) and (1.4), then

    (5.1)

    where,

    Proof. If is a solution of Eqs (1.3) and (1.4), for all

    By Lemma 2.12, we get

    (5.2)

    We discuss data dependence results for the problem

    (6.1)
    (6.2)

    Theorem 6.1. Equation (4.2) holds, and where are real numbers such that,

    (6.3)

    is a solution of ABR fractional derivative Eqs (6.1) and (6.2), and is a solution of Eqs (1.3) and (1.4).

    Proof. Let are the solution of Eqs (1.3) and (1.4), (6.1) and (6.2) respectively. We find for any

    By Lemma 2.12, we get

    (6.4)

    Let any and

    (7.1)
    (7.2)
    (7.3)
    (7.4)

    Theorem 7.1. Let the function satisfy Theorem 4.2. Suppose there exists such that,

    If are the solutions of Eqs (7.1) and (7.3), then

    (7.5)

    where

    Proof. Let, for any ,

    By Lemma 2.12,

    (7.6)

    Consider a nonlinear ABR fractional derivative with neutral integro-differential equations of the form:

    (8.1)
    (8.2)

    is a continuous nonlinear function such that,

    and

    We observe that for all and

    (8.3)

    The function satisfies with constant . From Theorem 4.2, we have and T = 2 which is substitute in Eq (4.2), and we get

    (8.4)

    If the function satisfies Eq (8.4), then Eqs (8.1) and (8.2) have a unique solution.

    (8.5)

    In this research article, we explored multi-derivative nonlinear neutral fractional integro-differential equations involving the ABR fractional derivative. The elementary results of the existence, uniqueness and dependence solution on various data are based on the Prabhakar fractional integral operator involving a generalized ML function. The existence results are obtained by Krasnoselskii's fixed point theorem, and the uniqueness and data dependence results are obtained by the Gronwall-Bellman inequality with continuous functions.

    The research on Existence and data dependence results for neutral fractional order integro-differential equations by Khon Kaen University has received funding support from the National Science, Research and Innovation Fund.

    The authors declare no conflict of interest.



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