Abstract
We present a dissipative measure-valued (DMV)-strong uniqueness result for the compressible Navier–Stokes system with potential temperature transport. We show that strong solutions are stable in the class of DMV solutions. More precisely, we prove that a DMV solution coincides with a strong solution emanating from the same initial data as long as the strong solution exists. As an application of the DMV-strong uniqueness principle we derive a priori error estimates for a mixed finite element-finite volume method. The numerical solutions are computed on polyhedral domains that approximate a sufficiently a smooth bounded domain, where the exact solution exists.
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1 Introduction
In meteorological applications the following system of compressible Navier–Stokes equations governing the motion of viscous Newtonian fluid is often used, see, e.g., [1, 6, 12, 14],
where \(\varrho \ge 0\), \(\varvec{u}\), and \(\theta \ge 0\), denote the fluid density, velocity, and potential temperature, respectively. The viscous stress tensor \({\mathbb {S}}(\nabla _{\varvec{x}}\varvec{u})\) is determined by the stipulation
where d is the space dimension, here \(d=2,3\), and the viscosity constants \(\mu \) and \(\lambda \) satisfy \( \mu > 0 \) and \(\lambda \ge -\frac{2}{d}\,\mu \), respectively. The state equation for the pressure p reads
where \(\gamma >1\) is the so-called adiabatic index. System (1.1)–(1.3) is solved on \((0,T) \times \Omega \), where \(T>0\) is a given time and \(\Omega \subset {\mathbb {R}}^d\) a bounded domain. It is accompanied with the initial data
and no-slip boundary conditions
In the sequel, we shall call system (1.1)–(1.5) the Navier–Stokes system with potential temperature transport. For a brief overview of analytical results for this system we refer to our recent paper [15]. It is to be pointed out that the existence of global-in-time weak solutions to (1.1)–(1.5) is available in three space dimensions only for \(\gamma \ge 9/5\), see Maltese et al. [17, Theorem 1 with \({\mathcal {T}}(s)=s^\gamma \)]. However, physically relevant values of the adiabatic index \(\gamma \) lie in the interval (1, 5/3] for \(d=3\). This drawback motivated our recent paper [15], where we have identified a larger class of generalized solutions, dissipative measure-valued (DMV) solutions, to the Navier–Stokes system with potential temperature transport. Analyzing the convergence of a suitable numerical scheme, the mixed finite element–finite volume method, we have proved global-in-time existence of DMV solutions for all adiabatic indices \(\gamma > 1\) for \(d=2,3.\)
The first goal of the present paper is to show that the strong solutions to the Navier–Stokes system with potential temperature transport are stable in the class of DMV solutions. To this end we establish a DMV-strong uniqueness principle. This result states that the DMV and strong solutions emanating from the same initial data coincide. The key concept for the proof of this principle is the relative energy. This approach for proving weak-strong uniqueness is not new; see, e.g., [3], where DMV-strong uniqueness is proven for the Navier–Stokes system, and [7, Chapter 6], where DMV-strong uniqueness is proven for the barotropic Euler system, the complete Euler system, and the Navier–Stokes system. However, till now the weak-strong uniqueness principle was not available for the Navier–Stokes equations with potential temperature transport (1.1)–(1.5). The essential difficulty lies in the pressure law that only depends on the total potential temperature \(\varrho \theta \), without any independent control of the density \(\varrho \). To cure this problem, we will rewrite the pressure as a function of the density and total physical entropy. This allows us to separate the effects of the density and potential temperature in the derivation of the relative energy and finally to show the DMV-strong uniqueness principle.
The second goal is to derive a priori error estimates for the finite element–finite volume method proposed in [15]. To this end, we assume that the strong solution exists and apply a relative energy inequality and a consistency formulation for the numerical method. Such an approach has already been applied successfully to the compressible Navier–Stokes equations, see Kwon and Novotný [13], and to the compressible Euler system, see [16]. However, in those works, the approximation of a sufficiently smooth domain \(\Omega \subset {\mathbb {R}}^d\) by a sequence of polygonal approximations \(\Omega _h\subset {\mathbb {R}}^d\), \(h\downarrow 0\), was not considered. In the present paper, novel consistency estimates are presented that allow to compare a strong solution on a smooth domain \(\Omega \) with numerical solutions computed on polygonal domains \(\Omega _h\), \(\Omega \subset \Omega _h\). Here, we only assume that \(\textrm{dist}(\varvec{x},\partial \Omega )={\mathcal {O}}(h)\) for all \(\varvec{x}\in \partial \Omega _h,\) see also Feireisl et al. [4, 8] for related results for the compressible Navier–Stokes equations on general domains under slightly more restrictive assumptions.
The paper is organized as follows: In Sect. 2, we briefly repeat the relevant notation and our definition of DMV solutions to Navier–Stokes system with potential temperature transport proposed in [15]. Section 3 is devoted to the proof of the DMV-strong uniqueness principle. Further, the error estimates are derived in Sect. 4 where we also present some numerical results.
2 DMV Solutions
We start by introducing the pressure potential \(P:[0,\infty )\rightarrow {\mathbb {R}}\) as
In what follows we write \(\Omega _t = (0,t)\times \Omega \) whenever \(t>0.\) If \({\mathcal {V}}=\{{\mathcal {V}}_{(t,\varvec{x})}\}_{(t,\varvec{x})\,\in \,\Omega _T}\) is a space-time parametrized probability measure acting on \({\mathbb {R}}^{d+2}\), we write
whenever \(g\in C({\mathbb {R}}^{d+2})\). In particular, we tend to write out the function g in terms of the integration variables : if, for example, , then we also write
We recall the definition of dissipative measure-valued solutions to the Navier–Stokes system with potential temperature transport (1.1)–(1.5) from [15].
Definition 2.1
(DMV solutions, [15, Definition 2.1]). A parametrized probability measure \({\mathcal {V}}=\{{\mathcal {V}}_{(t,\varvec{x})}\}_{(t,\varvec{x})\,\in \,\Omega _T}\) that satisfies
Footnote 1and for which there exists a constant \(c_\star >0\) such that
is called a dissipative measure-valued (DMV) solution to the Navier–Stokes system with potential temperature transport (1.1)–(1.5) with initial and boundary conditions (1.6) and (1.7) if it satisfies:
-
Energy inequality
and the integral inequality
(2.3)holds for a.a. \(\tau \in (0,T)\) with the energy concentration defect
and the dissipation defect
$$\begin{aligned} {\mathfrak {D}}\in {\mathcal {M}}^+(\,\overline{\Omega _T})\,; \end{aligned}$$ -
Continuity equation
and the integral identity
(2.4)holds for all \(\tau \in [0,T]\) and all \(\varphi \in W^{1,\infty }(\Omega _T)\)Footnote 2;
-
Momentum equation
and the integral identity
(2.5)holds for all \(\tau \in [0,T]\) and all \(\varvec{\varphi }\in C^{1}(\,\overline{\Omega _T})^d\) satisfying \(\varvec{\varphi }|_{[0,T]\times \partial \Omega }=\varvec{0}\), where the Reynolds concentration defect fulfills
-
Potential temperature equation
and the integral identity
(2.6)holds for all \(\tau \in [0,T]\) and all \(\varphi \in W^{1,\infty }(\Omega _T)\);
-
Entropy inequality
and for any \(\psi \in W^{1,\infty }(\Omega _T)\), \(\psi \ge 0\), the integral inequality
(2.7)is satisfied for a.a. \(\tau \in (0,T)\);
-
Poincaré’s inequality
there exists a constant \(C_P>0\) such that
(2.8)
for a.a. .
Remark 2.2
As we shall see in the next section, the entropy inequality (2.7) and Poincaré’s inequality (2.8) included in the definition of DMV solutions to the Navier–Stokes system with potential temperature transport are fundamental to guarantee DMV-strong uniqueness.
3 DMV-Strong Uniqueness
The aim of this section is to derive a DMV-strong uniqueness principle for our measure-valued solutions. For this purpose, we rely on the concept of relative energy. We introduce the (physical) entropy S as
and realize that the pressure \(p=a(\varrho \theta )^\gamma \) can be rewritten with respect to \(\varrho \), S as
We proceed by defining the relative energy between a triplet of arbitrary functions \((\varrho ,\theta ,\varvec{u})\) belonging to a regularity class
and a DMV solution \({\mathcal {V}}\) to the Navier–Stokes system with potential temperature transport (1.1)–(1.5) as
where \(P(\varrho ,S)=\frac{1}{\gamma -1}\,p(\varrho ,S)\) is the pressure potential expressed in terms of \(\varrho \) and S, \(S=S(\varrho ,\theta )\), and .
Remark 3.1
We note that \(P=P(\varrho ,S)\) satisfies the following identity on \((0,\infty )\times {\mathbb {R}}\):
We further note that we only consider the case in which are bounded from below by some constant \(c>0\) (for \(\theta \) this is reflected by (3.3) and for by (2.2)). Consequently, (3.1) makes sense. In particular, \(S(\varrho ,\theta )\) and the composition \(p(\varrho ,S(\varrho ,\theta ))\) are continuous functions of \((\varrho ,\theta )\) on \([0,\infty )\times [c,\infty )\) for every \(c>0\). In addition, we shall always construe S and as functions of \(\varrho ,\theta \) and , respectively. Accordingly, for example, .
The relative energy inequality corresponding to (3.4) reads as follows.
Lemma 3.2
(Relative energy inequality). Let \((\varrho ,\theta ,\varvec{u})\) be a triplet of test functions, cf. (3.3), and \({\mathcal {V}}\) a DMV solution to (1.1)–(1.5) in the sense of Definition 2.1. Then the relative energy defined in (3.4) satisfies the inequality
for a.a. \(\tau \in (0,T)\). Here,
denotes the absolute temperature.
Proof
Using Gauss’s theorem we easily verify that
Next, using the definition of the absolute temperature, cf. (3.7), and (3.5) we deduce that
Combining (3.8) and (3.9) with (2.3)–(2.7), we obtain
In the next step, we carry out the partial derivatives on the right-hand side of the above inequality. In doing so, we take into account that (3.5) implies that for any \(w\in \{t,x_1,\dots ,x_d\}\),
where the last equality is due to (3.7). Consequently, we get
To finish the proof of Lemma 3.2, we add and subtract the following terms on the right-hand side of the above inequality
and regroup the resulting expressions adequately. \(\square \)
From the relative energy inequality we can deduce the DMV-strong uniqueness result.
Theorem 3.3
(DMV-strong uniqueness). Let \(\gamma >1\), \(\Omega \subset {\mathbb {R}}^d\), \(d\in \{2,3\}\), be a bounded domain of class \(C^3\). Further, let \(T^* > 0 \) and \((\varrho ,\theta ,\varvec{u})\) be a strong solution to system (1.1)–(1.5) on \(\Omega _{T^*}\) belonging to the regularity class (3.3). Let \({\mathcal {V}}\) be a DMV solution in the sense of Definition 2.1 emanating from the same initial data. Then
and the DMV and strong solutions coincide on \([0,T^*)\), i.e.
Proof
Plugging the strong solution \((\varrho ,\theta ,\varvec{u})\) into the relative energy inequality (3.6), we obtain
for a.a. \(\tau \in (0,T^*)\). To handle the last two integrals, we first observe that
Next, we set
and apply Lemma A.1 to find constants \(c_1,c_2,c_3>0\) that only depend on \({\underline{\varrho }}\), \({\overline{\varrho }}\), \({\underline{\theta }}\), \({\overline{\theta }}\), \(c_\star \), and \(\gamma \), and corresponding sets
such that
Seeing that
as well as
we may use (3.12) to deduce
We proceed by observing that
and
for all \(\alpha >0\), where here and in the sequel the constant hidden in “\(\lesssim \)” does not depend on \(\alpha \). Together with (3.12) and Poincaré’s inequality (2.8), these observations yield
Finally, combining (3.10), (3.11), (3.13), and (3.14), we arrive at
for a.a. \(\tau \in (0,T^*)\) and all \(\alpha >0\). In particular, there exists a constant \(C>0\) such that
for a.a. \(\tau \in (0,T^*)\). Consequently, the desired result follows from Gronwall’s lemma. \(\square \)
Remark 3.4
The local existence of strong solutions to (1.1)–(1.5) for the Cauchy problem (i.e. \(\Omega ={\mathbb {R}}^d\)) is guaranteed by [11, Theorem 2.9] and the global existence for small initial data by [11, Theorem 3.6]. These results apply to a class of systems of hyperbolic-parabolic composite type. The local existence result just mentioned was generalized in [19]. We expect that these results can be transferred to the initial-boundary value problem considered here provided \(\Omega \) is of class \(C^3\) and the initial data satisfy suitable compatibility conditions. This can be an interesting topic for future studies.
4 Error Estimates for a Numerical Scheme
In our recent paper [15], we have introduced a mixed finite element-finite volume (FE-FV) numerical method and showed that in a suitable (weak) sense its solutions converge to a DMV solution to the Navier–Stokes equations with potential temperature transport (1.1)–(1.5). Moreover, we proved that if a strong solution exists, then the numerical solutions converge strongly to this strong solution, cf. [15, Theorem 6.1].
The ultimate goal of this section is to strengthen the just mentioned result and derive a priori error estimates for the finite element-finite volume method applying the relative energy method.
The section is organized as follows: In Sect. 4.1, we formulate minimal regularity assumptions required for the strong solution and the initial data. Sections 4.2 and 4.3 are devoted to the recapitulation of the numerical scheme presented in [15] and its properties. In Sect. 4.4, we present a novel consistency formulation taking the approximation of a smooth domain \(\Omega \) by a sequence of polygonal computational domains \(\Omega _h\), \(h \downarrow 0,\) into account. The desired error estimates are presented in Sect. 4.5. We finish this section by presenting some numerical results illustrating the convergence of the scheme.
4.1 Regularity Class for the Strong Solution and the Initial Data
We will consider strong solutions \((\varrho ,\theta ,\varvec{u})\) to (1.1)–(1.5) that belong to the regularity class
Accordingly, the initial data satisfy
For functions such as \(\varrho \) in (4.1) and \(\varrho _0\) in (4.2), we further introduce the following notation:
In addition, we consider the initial data \((\varrho _0,\theta _{0},\varvec{u}_0)\) to be extended by \(((\varrho _0)_\star ,(\theta _{0})_\star ,\varvec{0})\) outside \({\overline{\Omega }}\).
4.2 Mixed Finite Element-Finite Volume Method
We recall the mixed FE-FV numerical method introduced in [15]Footnote 4, see also [5, Chapter 7].
4.2.1 Spatial Discretization
Let \(H\in (0,1)\). The spatial domain \(\Omega \subset {\mathbb {R}}^d\) is approximated by a family \(\{\Omega _h\}_{h\,\in \,(0,H]}\) that is connected to a family of (finite) meshes \(({\mathcal {T}}_h)_{h\,\in \,(0,H]}\) via the constraint
We assume that the following conditions are satisfied:
-
There is a constant \(D>0\) such that
$$\begin{aligned} \Omega \subset \Omega _h\subset \big \{\varvec{x}\in {\mathbb {R}}^d\,\big |\, \textrm{dist}(\varvec{x},{\overline{\Omega }})<Dh\big \} \quad \text {for all }h\in (0,H]; \end{aligned}$$(4.4) -
Each element K of a mesh \({\mathcal {T}}_h\) is a d-simplex that can be written as
$$\begin{aligned} K = h{\mathbb {A}}_K (K_{\textrm{ref}}) + {\textbf{a}}_K\,, \qquad {\mathbb {A}}_K\in {\mathbb {R}}^{d\times d}\,, \qquad {\textbf{a}}_K\in {\mathbb {R}}^d\,, \end{aligned}$$where the reference element \(K_\textrm{ref}\) is the convex hull of the zero vector \(\varvec{0}\in {\mathbb {R}}^d\) and the standard unit vectors \({\textbf{e}}_{1},\dots ,{\textbf{e}}_{d}\in {\mathbb {R}}^d\), i.e., \(K_{\textrm{ref}} = \textrm{conv}\{{\textbf{0}},{\textbf{e}}_{1},\dots ,{\textbf{e}}_{d}\}\,\);
-
There exist constants \(C>c>0\) such that \(\textrm{spectrum}({\mathbb {A}}_K^T{\mathbb {A}}_K) \subset [c,C]\) for all \(K\in {\bigcup _{\,h\,\in \,(0,H]}}{\mathcal {T}}_h\) ;
-
The intersection of two distinct elements \(K_1,K_2\) of a mesh \({\mathcal {T}}_h\) is either empty, a common vertex, a common edge, or (in the case \(d=3\)) a common face.
The symbol \({\mathcal {E}}_{h}\) denotes the set of all faces, \(d=3\), or all edges, \(d=2\), in the mesh \({\mathcal {T}}_h\). \({\mathcal {E}}_{h,\textrm{ext}}\) and \({\mathcal {E}}_{h,\textrm{int}}\) stand for the sets of exterior and interior faces, respectively, i.e.,
Moreover, for \(K\in {\mathcal {T}}_h\), we put \({\mathcal {E}}_h(K) = \big \{\sigma \in {\mathcal {E}}_h\,\big |\,\sigma \subset K\big \}\) and \({\mathcal {E}}_{h,z}(K) = \big \{\sigma \in {\mathcal {E}}_{h,z}\,\big |\,\sigma \subset K\big \}\), where \(z\in \{\textrm{int},\textrm{ext}\}\). In connection with these sets, we shall use the abbreviations
Each face \(\sigma \in {\mathcal {E}}_{h}\) is equipped with a unit vector \(\varvec{n}_\sigma \) that is determined as follows: We fix an arbitrary element \(K_\sigma \in {\mathcal {T}}_h\) such that \(\sigma \in {\mathcal {E}}_h(K_\sigma )\) and set \(\varvec{n}_\sigma = \varvec{n}_{K_\sigma }(\varvec{x}_\sigma )\). Here, \(\varvec{x}_\sigma \) denotes the center of mass of \(\sigma \) and \(\varvec{n}_{K_\sigma }(\varvec{x}_\sigma )\) is the outward-pointing unit normal vector to the element \(K_\sigma \) at \(\varvec{x}_\sigma \). Finally, it will be convenient to write \(A \lesssim B\) whenever there is an h-independent constant \(c>0\) such that \(A \le cB\) and \(A \approx B\) whenever \(A\lesssim B\) and \(B\lesssim A\).
4.2.2 Function Spaces and Projection Operators
The space of piecewise constant functions is denoted by
Footnote 5For \(v\in Q_h\) and \(K\in {\mathcal {T}}_h\) we set \(v_K = v(\varvec{x}_K)\), where \(\varvec{x}_K\) denotes the center of mass of K. The projection \(\Pi _{Q,h}\equiv \overline{\;\cdot \;}:L^2(\Omega _h)\rightarrow Q_h\) associated with \(Q_h\) is characterized by
The Crouzeix-Raviart finite element spaces are denoted by
With these spaces we associate the projections \(\Pi _{V,h}:W^{1,2}(\Omega _h)\rightarrow V_h\), \(\Pi _{V,h}^0:W^{1,2}(\Omega _h)\rightarrow V_{0,h}\) that are determined by
respectively. Additionally, we agree on the notation
4.2.3 Mesh-Related Operators
Next, we recall the necessary mesh-related operators. We start by repeating the definitions of the discrete counterparts of the differential operators \(\nabla _{\varvec{x}}\) and \(\textrm{div}_{\varvec{x}}\). They are determined by the stipulations
respectively. We continue by recalling the trace operators. For arbitrary \(\sigma \in {\mathcal {E}}_{h}\), \(\varvec{x}\in \sigma \), and
we set
The convective terms shall be approximated by means of a dissipative upwind operator. For \(\sigma \in {\mathcal {E}}_{h}\), \(\varvec{v}\in \varvec{V}_{0,h}\), and \(\varvec{r}\in Q_h\cup \varvec{Q}_h\) we put
where \(\varepsilon >0\) is a given constant, \([x]^+ = \max \{x,0\}\) and \([x]^- = \min \{x,0\}\).
Remark 4.1
As in [15], we tend to omit parts of the subscripts and superscripts of the operators defined in Sects. 4.2.2 and 4.2.3 if no confusion arises. This includes the letters h and \(\sigma \) as well as the word in.
4.2.4 Time Discretization
To approximate the time derivatives, we employ the backward Euler method. Consequently, the discrete time derivative \(D_{t}\) is given by
where \(\Delta t>0\) is a given time step and \(\varvec{s}^{k-1}_h\) and \(\varvec{s}^k_h\) are the numerical solutions at the time levels \(t_{k-1}=(k-1)\Delta t\) and \(t_k=k\Delta t\), respectively. For the sake of simplicity, we assume that \(\Delta t\) is constant and that there is a number \(N_T\in {\mathbb {N}}\) such that \(N_T\Delta t= T\).
4.2.5 Numerical Scheme
The mixed FE-FV method introduced in [15, Definition 3.2] reads as follows.
4.2.6 Discrete Initial Data
The initial data for the mixed FE-FV method (4.5)–(4.7) are determined as follows:
As a consequence of this stipulation, we observe that \((\varrho _h^0,\theta _{h}^{0},\varvec{u}_h^0)\in Q_h^+\times Q_h^+\times \varvec{V}_{0,h}\) with
4.3 Discrete Energy and Entropy Inequalities
The solvability of the FE-FV method (4.5)–(4.7) is guaranteed by [15, Lemma 3.4]. In particular, it follows from a combination of this lemma with (4.9) that for every \(k\in {\mathbb {N}}_0\)
In addition, it turns out that the numerical solutions satisfy an energy balance and an entropy inequality that read as follows:
Given a solution \((\varrho _h^k,\theta _{h}^{k},\varvec{u}_h^k)_{k\,\in \,{\mathbb {N}}}\subset Q_h^+\times Q_h^+\times \varvec{V}_{0,h}\) to the FE-FV method (4.5)–(4.7) starting from the initial data (4.8), we define the functions \(\varrho _h^{-},\varrho _h,\theta _{h}:{\mathbb {R}}\times \Omega _h\rightarrow (0,\infty )\), \(\varvec{u}_h:{\mathbb {R}}\times \Omega _h\rightarrow {\mathbb {R}}^d\) that are piecewise constant in time by setting
In addition, we introduce the functions \(S_h,E_h:{\mathbb {R}}\times \Omega _h\rightarrow {\mathbb {R}}\) via the stipulations
Next, let us state two consequences of the discrete energy balance (4.11).
4.3.1 Stability Estimates
From (4.11) we obtain the subsequent energy estimates (cf. [15, Corollary 4.4]):
where \(q\in [1,\infty )\) if \(d=2\) and \(q\in [1,6]\) if \(d=3\).
Remark 4.2
Note that the proof of [15, Corollary 4.4] can be extended to include the estimates in (4.23). In addition, the different way of approximating the spatial domain \(\Omega \) (we now have \(\Omega \subset \Omega _h\) instead of \(\Omega _h\subset \Omega \)) requires some minor and straightforward modifications. We leave the details to the interested reader.
Moreover, for further application it is convenient to observe that the energy balance (4.11) provides us with the following
4.4 Consistency
We proceed by stating a suitable consistency formulation of the numerical scheme (4.5)–(4.7).
Theorem 4.3
(Consistency of the FE-FV method). Let \(\beta =\min \left\{ \varepsilon -1,\frac{1-2\delta }{4}\right\} \) and \(\tau \in [0,T]\). Further, suppose \((\varrho _h,\theta _{h},\varvec{u}_h)_{h\,\in \,(0,H]}\) is a family of solutions to the FE-FV method (4.5)–(4.7) with
starting from the initial data \((\varrho _h^0,\theta _{h}^{0},\varvec{u}_h^0)_{h\,\in \,(0,H]}\) defined in (4.8). Then
for all \(\varphi \in C^{1}(\overline{\Omega _T})\) as \(h\downarrow 0\),
for all \(\varvec{\varphi }\in C^{1}(\overline{\Omega _T})^d\), \(\varvec{\varphi }|_{[0,T]\times \partial \Omega }=\varvec{0}\), as \(h\downarrow 0\),
for all \(\varphi \in C^{1}(\overline{\Omega _T})\) as \(h\downarrow 0\) and
for all \(\psi \in C^{1}(\overline{\Omega _T})\), \(\psi \ge 0\), as \(h\downarrow 0\). Here, the constants in the \({\mathcal {O}}\) notation do not depend on the particular time \(\tau \in [0,T]\).
Proof
The proof is given in Appendix A.3. \(\square \)
4.5 Error Estimates
We continue with the derivation of a priori error estimates for the FE-FV method. For convenience, we agree that in this section the constants hidden in the \(\lesssim \) -symbols and the \({\mathcal {O}}\) notation neither depend on the times \(\tau \in [0,T]\) nor on the number \(\alpha >0\) that will appear in the sequel.
4.5.1 Discrete Relative Energy
To begin with, we introduce a suitable extension of the relative energy \(E(\,\cdot \,|\,\cdot \,)\) that we will refer to as the discrete relative energy. It will be used to measure a “distance” between a numerical solution \((\varrho _h,\theta _{h},\varvec{u}_h)\) and a triplet \((\varrho ,\theta ,\varvec{u})\) of functions of the class (4.1) and reads
Our aim is to repeat the proof of Lemma 3.2 on the numerical level to obtain a version of the relative energy inequality for . First, our initial observation is that
for every \(\tau \in [0,T]\). To be able to transfer the next step in the proof of Lemma 3.2 to the discrete setting, we need to derive a suitable analogue of (3.8).
4.5.2 Partial Integration for Diffusion Terms
For the treatment of the diffusion terms, we extend the velocity to a function using Stein’s extension operator \({\mathfrak {E}}_{\textrm{Stein}}\), see [20, Chapter VI, Theorem 5], i.e., we put \({\widehat{\varvec{u}}}(t,\cdot )={\mathfrak {E}}_{\textrm{Stein}}[\varvec{u}(t,\cdot )]\)Footnote 6. As a consequence,
where \(C_\textrm{Stein}(\Omega ,2)>0\) is given by
Having extended \(\varvec{u}\) as described above, we may use Gauss’s theorem to observe that
for all \(\tau \in [0,T]\). Here, the first, the fourth and the fifth equality are due to (4.4), (4.31) and the first and the last estimate in (4.14) which yield
and
Similarly, we deduce that
for all \(\tau \in [0,T]\). In addition, we may employ (4.4), (4.31) and the first and second estimate in (4.14) to observe that
Combining the previous estimates, we obtain the subsequent analogue of (3.8):
for all \(\tau \in [0,T]\), where the second equality is due to the first estimate in (A.3) and the first estimate in (4.14) which imply
4.5.3 Relative Energy Inequality for —General Form
It is now easy to transfer the remaining part of the proof of Lemma 3.2 to the discrete setting. Indeed, starting from (4.30) and ignoring the \(h^\delta \)-terms, a repetition of the steps of the proof of Lemma 3.2 using (4.24), (4.26)–(4.29) and (4.32) instead of (2.3), (2.4)–(2.7) and (3.8) yields
for all \(\tau \in [0,T]\). Then, using (4.26) and (4.28), we easily verify that
for all \(\tau \in [0,T]\). Consequently,
for all \(\tau \in [0,T]\).
4.5.4 Relative Energy Inequality for —Reduced form for Strong Solutions (Part I)
In a particular situation when \((\varrho ,\theta ,\varvec{u})\) is a strong solution to (1.1)–(1.5) of the class (4.1), the relative energy inequality (4.33) reduces to
Our goal is now to rewrite (4.34) in such a way that we can apply Gronwall’s lemma. To this end, we first consider the terms \(T_j\), \(j\in \{1,\dots ,8\}\). Clearly,
Moreover, the second and third estimate in (4.13) yield
Then, exactly as in the proof of Theorem 3.3, we see that
To handle the term \(T_8\), we need a suitable analogue of (2.8).
4.5.5 A Discrete Analogue of Poincaré’s Inequality (2.8)
For the derivation of the discrete analogue of (2.8) it shall be convenient to introduce the following notation:
With this notation at hand, we observe that
where in the second step we have used (A.11) as well as the estimates
which are based on the first estimate in (A.3) and the estimates (4.31), (A.13), (A.15). The last step in (4.35) is due to the estimates
that are based on (A.14), (4.31), (A.15).
4.5.6 Relative Energy Inequality for —Reduced form for Strong Solutions (Part II)
With the help of (4.35) we can now estimate the term \(T_8\) in (4.34) analogously to its continuous counterpart. We obtain
for all \(\alpha >0\). Together with the estimates for the terms \(T_j\), \(j\in \{1,\dots ,7\}\), stated in Sect. 4.5.4, this observation allows us to rewrite (4.34) as
for all \(\alpha >0\). Next, let us turn to the first line in (4.36). Using Hölder’s inequality, the first estimate in (A.3), (A.13) and (A.16), we deduce that
Moreover, denoting
and employing Hölder’s inequality, Taylor’s theorem, (A.12) and (A.16), we observe that
Consequently, we may rewrite (4.36) as
Fixing a sufficiently small \(\alpha >0\), we deduce from (4.37) the inequality
4.5.7 Error Estimates
We are now ready to apply Gronwall’s lemma to (4.38) which yields
Combining (4.39) with (4.35), we get
Furthermore, using Lemma A.1 and \(\theta _\star \le \theta _{h}\le \theta ^\star \), it is easy to see that for all \(p\in [1,\gamma ]\), all \(q\in [1,\infty )\) and all \(\tau \in [0,T]\)
Consequently, (4.40) yields
Remark 4.4
The optimal convergence rates are obtained for \(\varepsilon \ge 7/6\) and \(\delta =1/6\). In this case, \(\min \{\beta ,\delta \}=1/6\) and, in particular, the convergence rates for \(\varvec{u}_h\) in the -norm, for \(\varrho _h\) in the --norm (provided \(\gamma \le 2\)) and for \(\theta _{h}\) in the -norm are 1/12.
4.6 Numerical Results
We conclude this section by illustrating experimentally convergence behaviour of the FE-FV method (4.5)–(4.7). More specifically, motivated by the numerical experiments presented in [21, Section 5.1] and [7, Chapter 14.6.2], we simulate a vortex flow in \(\Omega =[0,1]^2\subset {\mathbb {R}}^2\) with the initial data
where
The parameters of the FE-FV method are chosen as \(\mu =0.1\), \(\nu =0\), \(\varepsilon =2.0\), \(\delta =0.1667\) and the final time for our convergence study is \(T=0.1\). The nonlinear algebraic system (4.5)–(4.7) is solved using a fixed point iteration. Thus, in each subiteration, the CFL stability condition
is required. This is ensured by the choice \(\Delta t=16h/130\). We concentrate on the following errors:
where \(h_\textrm{ref}=1/1024\) and
Tables 1 and 2 show the experimental order of convergence for two different values of the adiabatic exponent \(\gamma = 1.4\) and \(\gamma = 1.67.\)
Here, the experimental orders of convergence were computed using the standard formula
where \(\varvec{s}_h\) stands for a numerical solution on a mesh \(\Omega _h,\) analogous notations are used for \(\varvec{s}_{2h}\) and \(\varvec{s}_{h_\textrm{ref}}.\) We observe that EOC for the density, velocity, gradient of velocity and potential temperature are around 1, while the second order EOC are obtained for the relative energy. Similarly as in theoretical analysis the convergence rates in the relative energy are twice as good as those of the density, velocity and potential temperature. Our numerical experiments indicate that theoretical results obtained in Sect. 4.5 might be suboptimal, such a behaviour was observed in the literature also for other numerical methods and models, see, e.g., [9, 13, 16]. Figure 1 illustrates time evolution of the solution computed at different times on a mesh with \(h=1/128\) and for \(\gamma =1.4.\)
5 Conclusions
In the present paper, we have proved the DMV-strong uniqueness principle for the Navier–Stokes system with potential temperature transport (1.1)–(1.5). This result shows that strong solutions are stable in the class of DMV solutions introduced in [15]. We have derived the relative energy by taking the total physical entropy into account. More precisely, the pressure was rewritten as a function of the density and entropy, instead of the total potential temperature only. Moreover, we also require the entropy inequality (2.7) that is included in our definition of DMV solutions. The importance of Poincaré’s inequality (2.8) became clear from the proof of DMV-strong uniqueness: It allowed us to rewrite viscosity terms in such a way that Gronwall’s lemma was applicable and yield the DMV-strong uniqueness principle.
As an application of the DMV-strong uniqueness principle we derive a priori error estimates by applying the relative energy to numerical solutions. Our theoretical error estimates include not only the errors between the numerical and the strong solutions but also the so-called variational crime errors due to the approximation of a smooth domain \(\Omega \) by polygonal approximations \(\Omega _h\), \(\Omega \subset \Omega _h\) such that \(\textrm{dist}(\varvec{x},\partial \Omega )={\mathcal {O}}(h)\) for all \(\varvec{x}\in \partial \Omega _h.\)
Data Availability Statement
Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.
Notes
\({\mathcal {P}}({\mathbb {R}}^{d+2})\) denotes the space of probability measures on \({\mathbb {R}}^{d+2}\).
Here, the (Lipschitz) continuous representative of \(\varphi \in W^{1,\infty }(\Omega _T)\) is meant.
\({\mathcal {M}}({\overline{\Omega }})^{d\times d}_{\textrm{sym},+}\) denotes the set of bounded Radon measures defined on \({\overline{\Omega }}\) and ranging in the set of symmetric positive semi-definite matrices, i.e., \({\mathcal {M}}({\overline{\Omega }})^{d\times d}_{\textrm{sym},+} = \left\{ \mu \in {\mathcal {M}}({\overline{\Omega }})^{d\times d}_{\textrm{sym}}\,\left| \,\int _{\,{\overline{\Omega }}}\,\phi (\xi \otimes \xi ):\textrm{d}\mu \ge 0 \;\text {for all} \; \xi \in {\mathbb {R}}^d, \; \phi \in C({\overline{\Omega }}), \; \phi \ge 0\right. \right\} \).
\(P_n(K)\) denotes the set of all restrictions of polynomial functions \({\mathbb {R}}^d\rightarrow {\mathbb {R}}\) of degree at most n to the set K.
This stipulation is to be understood componentwise.
Compared to [4, Corollary 2.12] we only have the factor h instead of \(h^2\) on the right-hand side which is due to the fact that (4.4) only ensures that there is a constant \(d_\Omega >0\) such that \(\textrm{dist}[\varvec{x},\partial \Omega ]\le d_\Omega h\) for all \(\varvec{x}\in \partial \Omega _h\).
In integrals of the form \(\int _{{\mathcal {E}}(K)}\) we consider the vector \(\varvec{n}_\sigma \) in the definition of the trace operators \((\cdot )^{\textrm{in},\sigma }\) and \((\cdot )^{\textrm{out},\sigma }\) to be replaced by \(\varvec{n}_K\).
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Acknowledgements
This research was initiated during a Research in Pairs stay at the Mathematical Research Institute in Oberwolfach in 2021. The authors gratefully acknowledge this generous support. The work has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the SFB/TRR 165 Waves to Weather. M.L. gratefully acknowledges support of the Gutenberg Research College of University Mainz and the Mainz Institute of Multiscale Modeling. The authors wish to thank E. Feireisl (Prague) and A. Novotný (Toulon) for fruitful discussions.
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Appendix
Appendix
1.1 An Auxiliary Result Concerning the Relative Energy
Here, we prove the auxiliary result used in the proof of DMV-strong uniqueness.
Lemma A.1
Let , , \(0<{\underline{\varrho }}\le \varrho \le {\overline{\varrho }}\), \(0<{\underline{\theta }}\le \theta \le {\overline{\theta }}\), and \(\gamma >1\). Then there exist constants \(c_1,c_2,c_3,c_4>0\) that only depend on \({\underline{\varrho }},{\overline{\varrho }},{\underline{\theta }},{\overline{\theta }},c_\star \) and \(\gamma \), and corresponding sets
such that
where \(P(\varrho ,S)=\frac{1}{\gamma -1}\,p(\varrho ,S)\) with p from (3.2), \(S=S(\varrho ,\theta )\) is defined in (3.1), and .
Proof
To begin with, let \(0<c_1\le c_2\), and \(c_3\ge c_\star /\,{\overline{\theta }}\) be arbitrary numbers. Further, let \({\mathcal {R}}\), \({\mathcal {S}}\) be defined as described in the lemma. We decompose \({\mathcal {S}}\) into the sets
and observe that
wherefore
Here, the first inequality is obtained using Young’s inequality. Together, the above observations show that we can specify \(c_1,c_2,c_3\) in dependence of \({\underline{\varrho }},{\overline{\varrho }},{\underline{\theta }},{\overline{\theta }},c_\star ,\gamma \) such that
where \(c_{4,1}>0\) solely depends on \({\underline{\varrho }},{\overline{\varrho }},{\underline{\theta }},{\overline{\theta }},c_\star ,\gamma \). Having fixed \(c_1,c_2,c_3\) as described above, it remains to show that
where \(c_{4,2}>0\) only depends on \({\underline{\varrho }},{\overline{\varrho }},{\underline{\theta }},{\overline{\theta }},c_\star ,\gamma \). This inequality is a direct consequence of the fact that \(P=P(\varrho ,S)\) is strongly convex on every compact convex subset of \((0,\infty )\times {\mathbb {R}}\) which, in turn, follows from the positive definiteness of the Hessian of P on \((0,\infty )\times {\mathbb {R}}\). \(\square \)
1.2 Mesh-Related Estimates
We recall several important mesh-related estimates; see, e.g., [7] and the references therein. We begin with the discrete trace and inverse inequalities. We have
for all \(r\in Q_h\), all \(K\in {\mathcal {T}}_h\), all \(\sigma \in {\mathcal {E}}_h(K)\), and all \(1\le q\le p\le \infty \). In addition,
are valid for all \(p\in [1,\infty ]\), all \(v\in V_{0,h}\), all \(K\in {\mathcal {T}}_h\), and all \(\sigma \in {\mathcal {E}}_h(K)\). Moreover, given \(\phi \in C(\overline{\Omega _h})\cap W^{1,\infty }(\Omega _h)\), it is easy to see that
Next, combining [18, Theorem 6.1] with [10, Lemma 2.2] we obtain a discrete version of Poincaré’s inequality, namely
for all \(v\in V_{0,h}\), where \(q\in [1,\infty )\) if \(d=2\) and \(q\in [1,6]\) if \(d=3\). Due to [2, Theorem 5], we have the following estimates for the projection operators \(\Pi _{Q,h}\) and \(\Pi _{V,h}\):
for all \(q\in [1,\infty ]\), all \(\phi \in W^{1,q}(\Omega _h)\), and all \(\psi \in W^{2,q}(\Omega _h)\).
Furthermore, we record the following estimate concerning the comparison of the operators \(\Pi _{V,h}\) and \(\Pi _{V,h}^0\), see [4, Corollary 2.12]:
Footnote 7for all \(\phi \in C^{1}({\mathbb {R}}^d)\) and all \(K\in {\mathcal {T}}_h\).
Finally, we report the boundedness of the projection operators \(\Pi _{Q,h}\) and \(\Pi _{V,h}\). It follows from Jensen’s inequality, cf. [5, p.90], that
Furthermore, we may use (A.13) and the triangle inequality to deduce that there exists an h-independent constant \(C>0\) such that
1.3 Proof of Theorem 4.3
This appendix is devoted to the proof of Theorem 4.3. Its proof is an adaption of the proof of [15, Theorem 5.1]. Apart from the estimates listed in Appendix A.2, we need the subsequent results.
Lemma A.2
Let \(\phi \in C^{1}(\overline{\Omega _T})\), \(\tau \in \{\Delta t,\dots ,N_T\Delta t\}\), \((r_h^k)_{k\,\in \,{\mathbb {N}}_0}\subset Q_h\), and define the functions via
Then
Proof
Let \(m\in {\mathbb {N}}\) be such that \(\tau =m\Delta t\). Then
Moreover, using Hölder’s inequality, we deduce that
Together, the previous computations yield the desired result. \(\square \)
Lemma A.3
Let \(r,f\in Q_h\), \(\varvec{v}\in \varvec{V}_{0,h}\) and \(\phi \in C(\overline{\Omega _h})\cap W^{1,\infty }(\Omega _h)\). Then
Corollary A.4
Let \(\varvec{s},\varvec{g}\in \varvec{Q}_h\), \(\varvec{w}\in \varvec{V}_{0,h}\), and \(\varvec{\psi }\in C(\overline{\Omega _h})^d\cap W^{1,\infty }(\Omega _h)^d\). Then
Lemma A.5
Let \(r\in Q_h\), \(v\in V_{0,h}\), \(\phi \in W^{1,2}_0(\Omega _h)\), and \(\varvec{\phi }\in W^{1,2}_0(\Omega _h)^d\). Then
For the proof of the Lemmata A.3 and A.5, we refer to [5, Chapter 9.2, Lemma 7 with \(\chi =1\)] and [5, Chapter 9.3, Lemma 8], respectively. For the proof of Lemma A.3, we additionally need to observe that
which follows from the fact that \(r\in Q_h\). Corollary A.4 can be proven by applying Lemma A.3 with \((r,f,\varvec{v},\phi )=(s_i,g_i,\varvec{w},\psi _i)\), \(i\in \{1,\dots ,d\}\).
Having all necessary tools at our disposal, we can approach the proof of Theorem 4.3.
Proof of Theorem 4.3 (Part I)
In this part, we only consider the case \(\tau \in \{\Delta t,\dots ,N_T\Delta t\}\). We choose arbitrary test functions \(\varphi ,\psi \in C^{1}(\overline{\Omega _T})\), \(\psi \ge 0\), and \(\varvec{\varphi }\in C^{1}(\overline{\Omega _T})^d\), \(\varvec{\varphi }|_{[0,T]\times \partial \Omega }=\varvec{0}\). By extension with \(\varvec{0}\), we consider . Moreover, since \(\Omega \) is a smooth domain, \(\Omega _T\) is also a smooth domain. Thus, we may use Stein’s extension operator \({\mathfrak {E}}_{\textrm{Stein}}\), see [20, Chapter VI, Theorem 5], to extend \(\varphi ,\psi \) in such a way that \(\varphi ,\psi \in W^{1,\infty }({\mathbb {R}}^{d+1})\cap C({\mathbb {R}}^{d+1})\) and
for all \(k\in \{0,1\}\), where \(C_\textrm{Stein}(\Omega _T,1)>0\) is given by
Putting \(\varphi _h=\Pi _{Q}\varphi \), \(\psi _h=\Pi _{Q}\psi \) and \(\varvec{\varphi }_h = \Pi _{V}\varvec{\varphi }\), we make the following observations.
The continuity equation.
From (4.5) we deduce that
Using the fact that \(\varrho _h(t,\cdot )\in Q_h\) for every \(t\in [0,\tau ]\), we see that
Next, we observe that
Consequently, (4.4), the second estimate in (4.15), (A.16) and (A.21) yield
Combining (A.23), (A.3) and the first estimate in (4.23) with \(\Delta t\approx h\) and Lemma A.2 applied to \((r_h,\phi )=(\varrho _h,\varphi )\), we obtain
Next, let us consider the second term on the left-hand side of (A.22). Employing Hölder’s inequality, the first estimate in (A.3), the second estimate in (4.15), the first estimate in (4.14) and (A.21), we see that
Moreover, applying (A.21), (4.4), the second estimate in (4.15) and the first estimate in (4.13), we obtain
Consequently,
Then, using Lemma A.3 with \((r,\varvec{v},f,\phi )=(\varrho _h,\varvec{u}_h,\varphi _h,\varphi )(t,\cdot )\), \(t\in [0,\tau ]\), as well as the estimates (A.5)–(A.7), (A.12) and (A.21), we deduce that
where
These terms can be further estimated as follows.
-
Term \(|I_{2,h}|\). Due to (4.21), we obtain
$$\begin{aligned} |I_{2,h}|\lesssim h \int ^{T}_{0}\int _{{\mathcal {E}}_\textrm{int}}\big |\llbracket \varrho _h\rrbracket \,\langle \varvec{u}_h\cdot \varvec{n}_\sigma \rangle _\sigma \big |\,\textrm{d}S_{\varvec{x}}\textrm{d}t\lesssim h^{1-\delta /2}(1+h^{-1/2})\,. \end{aligned}$$ -
Term \(|I_{3,h}|\). By means of Hölder’s inequality, the second estimate in (A.3), the first estimate in (A.2), the second estimate in (4.15), and the first estimate in (4.14), we derive
-
Term \(|I_{4,h}|\). Employing Hölder’s inequality, the second estimate in (4.14), and the second estimate in (4.15), we conclude that
-
Term \(|I_{5,h}|\). Applying the first estimate in (A.2) and the second estimate in (4.13), we get
Consequently,
where \(\alpha _1=\min \left\{ \varepsilon ,\frac{1-\delta }{4}\right\} \).
The potential temperature equation.
The proof of (4.28) can be done by repeating the proof of (4.26) with \(\varrho _h\) and \(\varrho _h^0\) replaced by \(\varrho _h\theta _{h}\) and \(\varrho _h^0\theta _{h}^{0}\), respectively.
The momentum equation.
Realizing that \(\varvec{\varphi }_h(t,\cdot )\in \varvec{V}_{0,h}\) for all \(t\in [0,T]\), we deduce from (4.7) that
Let us consider the first term on the left-hand side of (A.25). Since \(\varvec{\varphi }\) vanishes on \([0,T]\times (\Omega _h\backslash \Omega )\), we have
where by Hölder’s inequality, the second information in (4.10), (A.16), the second estimate in (4.19), (A.13) and \(\Delta t\approx h\)
and by Hölder’s inequality, the first estimate in (4.23), the third estimate in (4.14), (A.16), (A.5) and \(\Delta t\approx h\)
In view of the previous two computations, it is easy to verify that
whence Lemma A.2 applied to \((r_h,\phi )=(\varrho _h \overline{u_{h,i}},\varphi _i)\), \(i\in \{1,\dots ,d\}\), yields
as \(h\downarrow 0\). Next, we turn to the last three terms on the left-hand side of (A.25). It follows from Lemma A.5 that
Finally, let us examine the second term on the left-hand side of (A.25). Using Hölder’s inequality, the first estimate in (A.3), the second estimate in (4.16) and the first estimate in (4.14), we deduce that
Applying Corollary A.4 with \((\varvec{s},\varvec{w},\varvec{g},\varvec{\psi })=(\varrho _h\overline{\varvec{u}_h},\varvec{u}_h,\varvec{\varphi }_h,\varvec{\varphi })(t,\cdot )\), \(t\in [0,\tau ]\), as well as the estimates (A.8)–(A.10) and (A.13), we deduce that
where
We continue by estimating the above terms.
-
Term \(|J_{2,h}|\). We observe that \(\llbracket \varrho _h\overline{\varvec{u}_h}\rrbracket = \varrho _h^{\,\textrm{out}}\llbracket \overline{\varvec{u}_h}\rrbracket + \llbracket \varrho _h\rrbracket \overline{\varvec{u}_h}^{\,\textrm{in}}\), which implies
$$\begin{aligned} |J_{2,h}|&\lesssim h \int ^{T}_{0}\int _{{\mathcal {E}}(K)}\big |\varrho _h^{\,\textrm{out}} \llbracket \overline{\varvec{u}_h}\rrbracket \big [\langle \varvec{u}_h\cdot \varvec{n}_{{K}} \rangle _\sigma \big ]^-\big |\,\textrm{d}S_{\varvec{x}}\textrm{d}t+ h \int ^{T}_{0}\int _{{\mathcal {E}}(K)}\big |\llbracket \varrho _h\rrbracket \overline{\varvec{u}_h} \big [\langle \varvec{u}_h\cdot \varvec{n}_{{K}} \rangle _\sigma \big ]^-\big |\,\textrm{d}S_{\varvec{x}}\textrm{d}t\,. \end{aligned}$$(A.26)Employing Hölder’s inequality, (4.20), (A.4), the first estimate in (A.2), the first and third estimate in (4.14), and the second estimate in (4.15), we see that
(A.27)Next, using Hölder’s inequality, the estimates (A.2), (A.4), (4.17), the first and third estimate in (4.14), the second estimate in (4.15), and the fact that \(\Delta t\approx h\), we deduce that
(A.28)Consequently, plugging (A.27) and (A.28) into (A.26), we obtain
$$\begin{aligned} |J_{2,h}| \lesssim h^{1/2-\delta /4} + h^{1-\delta /4} + h^{1/4-\delta /2} + h^{3/4-\delta /2}\,. \end{aligned}$$ -
Term \(|J_{3,h}|\). Applying Hölder’s inequality, the first estimate in (A.2), the second estimate in (A.3), the first estimate in (4.14), and the second estimate in (4.16), we conclude that
-
Term \(|J_{4,h}|\). Employing Hölder’s inequality, the first estimate in (4.14), and the second estimate in (4.16), we obtain
-
Term \(|J_{5,h}|\).
Using the first estimate in (A.2) and the third estimate in (4.13), we deduce that
Keeping in mind that \(\varvec{\varphi }\) vanishes on \([0,T]\times (\Omega _h\backslash \Omega )\), we may summarize the previous observations as follows:
as \(h\downarrow 0\) with \(\alpha _2 = \min \left\{ \varepsilon ,\frac{1-2\delta }{4}\right\} >0\).
The entropy inequality.
Taking \(\psi _h^\star (t,\cdot )=\psi _h(t,\cdot )+C_\textrm{Stein}(\Omega _T,1)Dh \,||\psi ||_{{{C}^{{{1}}}{(\overline{\Omega _T})}}}\), \(t\in [0,\tau ]\), as a test function in (4.12) with \(\chi =\ln \), we deduce that
where
Now we may rewrite the first two integrals in (A.30) following the procedure used to handle the continuity equation. The error terms appearing during this process are exactly the same as in the case of the continuity equation with \(\varrho _h\) replaced by \(\varrho _h\ln (\theta _{h})\) and \(\varphi _h\) replaced by \(\psi _h\). However, the analogue of the error term \(I_{5,h}\) will not be there since (A.30) contains the usual upwind operator \(\textrm{Up}\left[ \,\cdot \,,\,\cdot \,\right] \) instead of the dissipative upwind operator \(F_h^{\,\textrm{up}}\left[ \,\cdot \,,\,\cdot \,\right] \). Since \((\theta _{0})_\star \le \theta _{h}\le (\theta _{0})^\star \),
for every \((k,\sigma )\in {\mathbb {N}}\times {\mathcal {E}}_{\textrm{int}}\) and suitably chosen values \((\eta _{\theta ,k,\sigma })_{\sigma \,\in \,{\mathcal {E}}_{\textrm{int}}}\subset [(\theta _{0})_\star ,(\theta _{0})^\star ]\) and, analogously,
it is easy handle these error terms. Thus,
as \(h\downarrow 0\). For the error terms \(H_{j,h}\), \(j\in \{1,\dots ,4\}\) we proceed as follows. Since \(H_{1,h}=-I_{5,h}\), we have \(|H_{1,h}|\lesssim h^{\alpha _1}\). Combining \((\theta _{0})_\star \le \theta _{h}\le (\theta _{0})^\star \) with Hölder’s inequality, the first estimate in (A.2), the second estimate in (4.13) and the first estimate in (4.15), we deduce that
Moreover, using \((\theta _{0})_\star \le \theta _{h}\le (\theta _{0})^\star \), the second information in (4.10) and (A.16), we easily verify that
Consequently, we may rewrite (A.31) as
as \(h\downarrow 0\) with \(\alpha _3=\min \{\alpha _1,\varepsilon -1\}\). \(\square \)
Proof of Theorem 4.3 (Part II)
In this part, we turn to the situation in which \(\tau \in [0,T]\) is arbitrary. Since the case \(\tau =0\) is trivial, we may assume without loss of generality that \(\tau \in (0,T]\). Let \(m\in \{1,\dots ,N_T\}\) be the smallest number such that \(t_m=m\Delta t\ge \tau \).
The continuity equation.
Using Hölder’s inequality, (A.16) and \(\Delta t\approx h\), we deduce that
Moreover, employing Hölder’s inequality the second and third estimate in (4.13), we see that
Consequently, (4.26) holds for any \(\tau \in [0,T]\).
The potential temperature equation and the entropy inequality.
Keeping in mind that \((\theta _{0})_\star \le \theta _{h}\le (\theta _{0})^\star \), one easily reduces the setting of the potential temperature equation and the entropy inequality to that of the continuity equation.
The momentum equation.
From Hölder’s inequality, the third estimate in (4.13) and \(\Delta t\approx h\) we deduce that
Furthermore, Hölder’s inequality, \(\Delta t\approx h\), the first two estimates in (4.14) as well as estimates in (4.13) and (4.15) yield
which implies that (4.27) holds for any \(\tau \in [0,T]\). \(\square \)
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Lukáčová-Medvid’ová, M., Schömer, A. Compressible Navier–Stokes Equations with Potential Temperature Transport: Stability of the Strong Solution and Numerical Error Estimates. J. Math. Fluid Mech. 25, 1 (2023). https://doi.org/10.1007/s00021-022-00733-z
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DOI: https://doi.org/10.1007/s00021-022-00733-z