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Modified characteristics projection finite element method for time-dependent conduction-convection problems
Boundary Value Problems volume 2015, Article number: 151 (2015)
Abstract
In this paper, we give a modified characteristics projection finite element method for the time-dependent conduction-convection problems, which is gotten by combining the modified characteristics finite element method and the projection method. The stability and the error analysis shows that our method is stable and has optimal convergence order. In order to show the effect of our method, some numerical results are presented. From the numerical results, we can see that the modified characteristics projection finite element method can simulate the fluid field, temperature field, and pressure field very well.
1 Introduction
The conduction-convection problem constitutes an important system of equations in atmospheric dynamics and dissipative nonlinear system of equations. There is a significant amount of literature as regards this problem. An optimizing reduced Petrov-Galerkin least squares mixed finite element (PLSMFE) [1] method for the non-stationary conduction-convection problems was given. An efficient sequential method was developed to estimate the unknown boundary condition on the surface of a body from transient temperature measurements inside the solid [2]. An analysis of conduction natural convection conjugate heat transfer in the gap between concentric cylinders under solar irradiation [3] was carried out by Kim et al., Boland and Layton [4] gave an error analysis for finite element methods for steady natural convection problems. Newton type iterative methods [5–7] and defect-correction methods [8–10] for the conduction-convection equations were presented.
The projection methods, which are efficient methods for solving the incompressible time-dependent fluid flow, were first introduced by Chorin [11] and Temam [12] in the late 1960s. This method is based on a special time-discretization of the Navier-Stokes equations. In this method, the convection-diffusion and the incompressibility are dealt with in two different sub-steps. The velocity obtained in the convection-diffusion sub-step is projected in order to satisfy the weak incompressibility condition. The projection methods can be classified into three families: the pressure-correction method [13, 14], the velocity-correction method [15], and the consistent splitting scheme [16, 17], which is called a gauge method also [18]. The convergence analysis of the semi-discrete projection methods can be found in Shen [19] and Guermond and Quartapelle [20]. In Guermond and Quartapelle [21], the projection method was implemented by the finite element method. It was used to solved the variable density Navier-Stokes equations in [22]. In [23], a gauge-Uzawa projection method was presented. Then it was applied to the conduction-convection equations [24] and incompressible flows with variable density [25].
As we know, the characteristics method is a highly effective method for the advection dominated problems. Douglas and Russell [26] presented the modified method of characteristics first. It was extended to nonlinear coupled systems by Russell [27] in two and three spatial dimensions. A detailed analysis for the Navier-Stokes equations has been done by Dawson et al. [28] and numerical tests have been presented by Buscagkia and Dari [29]. A second order MMOC mixed defect-correction finite element method [30] for time-dependent Navier-Stokes problems was given. Notsu et al. gave a single-step characteristics finite difference analysis for the convection-diffusion problems [31] and a single-step finite element method for the incompressible Navier-Stokes equations [32]. El-Amrani and Seaid gave the error estimates of the modified method of characteristics finite element methods for the Navier-Stokes [33], natural, and mixed convection flows [34]. In [35], Achdou and Guermond gave the projection/Lagrange-Galerkin method for the incompressible Navier-Stokes equations.
In this paper, we give the modified characteristics projection finite element method (MCPFEM) for the time-dependent conduction-convection problems, which is gotten by combining the modified characteristics finite element method and the projection method. We give stability and error analysis, which show that our method is stable and has optimal convergence order. In order to show the efficiency of our method, some numerical results are presented. At first, the numerical results of Bénard convection problems are given. Then we give some numerical results of the thermal driven cavity flow. From the numerical results, we can see that MCPFEM can simulate the fluid field, temperature field, and pressure field very well.
2 The modified characteristics projection finite element method for the time-dependent conduction-convection problems
In this paper, we consider the time-dependent conduction-convection problem in two dimensions whose coupled equations governing viscous incompressible flow and heat transfer for the incompressible fluid are Boussinesq approximations to the Navier-Stokes equations. For all \(t\in(0,t_{1}]\), find \((u,p,T)\in X\times M\times W\) such that
where Ω is a bounded domain in \(\mathbb{R}^{2}\) assumed to have a Lipschitz continuous boundary ∂Ω. \(u=(u_{1}(x,t),u_{2}(x,t))^{T}\) represents the velocity vector, \(p(x,t)\) represents the pressure, \(T(x,t)\) represents the temperature, κ represents the Grashoff number, \(\lambda=\mathit{Pr}^{-1}\), Pr is the Prandtl number, g represents the vector of gravitational acceleration, \(\nu =\mathit{Re}^{-1}\), Re is the Reynolds number, and f and b are the forcing functions.
In this section, we aim to describe some notations and materials which will be frequently used in this paper. For the mathematical setting of the conduction-convection problems (1), we introduce the Hilbert spaces
\(\Im_{h}\) is a quasi-uniform partition of \(\bar{\Omega}_{h}\) into non-overlapping triangles, indexed by a parameter \(h=\max_{K\in\Im _{h}}\{h_{K};h_{K}=\operatorname{diam}(K)\}\). We introduce the finite element subspace \(X_{h}\subset X\), \(M_{h}\subset M\), \(W_{h}\subset W\) as follows:
where \(P_{\ell}(K)\) is the space of piecewise polynomials of degree â„“ on K, \(\ell\geq1\), \(k\geq1\), \(j\geq1\) are three integers. \(W_{0h}=W_{h}\cap H_{0}^{1}(\Omega)\), and assume that \((X_{h},M_{h})\) satisfies the discrete LBB condition, there exists \(\beta>0\) such that
where \(d(v_{h},\varphi_{h})=-(\varphi_{h},\nabla\cdot v_{h})\). Let \(V_{h}\) be the kernel of the discrete divergence operator,
For each positive integer N, let \(\{\mathcal{J}_{n}: 1\leq n\leq N\}\) be a partition of \([0,t_{1}]\) into subintervals \(\mathcal{J}_{n}=(t_{n-1},t_{n}] \), with \(t_{n}=n\tau\), \(\tau=T_{1}/N\). Set \(u^{n}=u(\cdot,t_{n})\). The characteristic trace-back along the field \(u^{n-1}\) of a point \(x\in\Omega\) at time \(t_{n}\) to \(t_{n-1}\) is approximately
Consequently, the hyperbolic part in the first equation of (1) at time \(t_{n}\) is approximated by
where
for any function w.
With the previous notations, we get the projection FEM for the time-dependent conduction-convection problem (1), which is a slight transmutation of the projection FEM [13, 19] for the time-dependent Navier-Stokes equations.
Algorithm 2.1
(Projection FEM)
Start \(u_{h}^{0}\) as a solution of \((u_{h}^{0},v_{h})=(u_{0},v_{h})\) and \((T_{h}^{0},\psi_{h})=(T_{0},\psi_{h})\), \(p_{h}^{0}=0\) for all \(v_{h}\in V_{h}\), \(\psi_{h}\in M_{h}\).
- Step 1::
-
Find \(\hat{u}_{h}^{n+1}\in X_{h}\) as the solution of
$$\begin{aligned}& \biggl( \frac{\hat{u}_{h}^{n+1}-u_{h}^{n}}{\tau},v_{h} \biggr) +B\bigl({u}_{h}^{n},\hat{u}_{h}^{n+1},v_{h}\bigr)+\nu\bigl(\nabla \hat{u}_{h}^{n+1},\nabla v_{h}\bigr) \\& \quad =\kappa \nu^{2}\bigl(gT_{h}^{n},v_{h}\bigr)+ \bigl(f(t_{n+1}),v_{h}\bigr), \quad \forall v_{h} \in X_{h}, \end{aligned}$$where \(B(u_{h},v_{h},w_{h})=\frac{1}{2}((u_{h}\cdot\nabla )v_{h},w_{h})-\frac{1}{2}((u_{h}\cdot\nabla)w_{h},v_{h})\).
- Step 2::
-
Find \({u}_{h}^{n+1}\in V_{h}\), \(p_{h}^{n+1}\in M_{h}\) as the solution of
$$ \begin{aligned} & \biggl( \frac{{u}_{h}^{n+1}-\hat{u}_{h}^{n+1}}{\tau},v_{h} \biggr) +d\bigl(p_{h}^{n+1},v_{h}\bigr) =0,\quad \forall v_{h}\in V_{h}, \\ &d\bigl(q_{h},u_{h}^{n+1}\bigr) =0,\quad \forall q_{h}\in M_{h}. \end{aligned} $$(2) - Step 3::
-
Compute \(T_{h}^{n+1} \in W_{h}\) as the solution of the linear elliptic equation
$$\begin{aligned}& \biggl(\frac{T_{h}^{n+1}-T_{h}^{n}}{\tau}, \psi_{h} \biggr)+\bar{B}\bigl(u_{h}^{n+1},T_{h}^{n+1}, \psi_{h}\bigr)+\lambda\nu\bigl(\nabla T_{h}^{n+1}, \nabla \psi_{h}\bigr) \\& \quad =\bigl(b(t_{n+1}),\psi_{h} \bigr),\quad \forall\psi_{h}\in W_{0h}, \end{aligned}$$(3)\(\bar{B}(u_{h},T_{h},\psi_{h})=\frac{1}{2}((u_{h}\cdot\nabla)T_{h},\psi_{h})-\frac{1}{2}((u_{h}\cdot\nabla)\psi_{h},T_{h})\).
Remark 2.1
Denote by \(P_{h}\) the orthogonal projector in \((L^{2}(\Omega))^{2}\) onto V. We can readily check that (2) is equivalent to [19]
The MC time discretization, combined with the projection finite element method, leads to the following MC projection finite element method.
Algorithm 2.2
(MC projection FEM)
Start with \(u_{h}^{0}\) as a solution of \((u_{h}^{0},v_{h})=(u_{0},v_{h})\) for all \(v_{h}\in V_{h}\).
- Step 1::
-
Find \(\hat{u}_{h}^{n+1}\in X_{h}\) as the solution of
$$\begin{aligned}& \biggl(\frac{\hat{u}_{h}^{n+1}-\dot{u}_{h}^{n}}{\tau},v_{h} \biggr)+\nu\bigl(\nabla \hat{u}_{h}^{n+1},\nabla v_{h}\bigr) \\& \quad = \kappa\nu^{2}\bigl(gT_{h}^{n},v_{h} \bigr)+\bigl(f(t_{n+1}),v_{h}\bigr), \quad \forall v_{h}\in V_{h}, \end{aligned}$$(5)where
$$ \dot{u}_{h}^{n} =\left \{ \textstyle\begin{array}{l@{\quad}l} u_{h}^{n}(\dot{x}), & \dot{x}=x-u^{n}_{h}\tau\in\Omega, \\ 0, & \mbox{otherwise}.\end{array}\displaystyle \right . $$ - Step 2::
-
Find \({u}_{h}^{n+1}\in V_{h}\), \(p_{h}^{n+1}\in M_{h}\) as the solution of
$$ \begin{aligned} & \biggl(\frac{{u}_{h}^{n+1}-\hat{u}_{h}^{n+1}}{\tau},v_{h} \biggr)+b\bigl(p_{h}^{n+1},v_{h}\bigr)=0,\quad \forall v_{h}\in V_{h}, \\ &b\bigl(q_{h},u_{h}^{n+1}\bigr)=0,\quad \forall q_{h}\in M_{h}. \end{aligned} $$(6) - Step 3::
-
Compute \(T_{h}^{n+1} \in W_{h}\), the solution of the linear elliptic equation
$$ \biggl(\frac{T_{h}^{n+1}-\dot{T}_{h}^{n}}{\tau}, \psi_{h} \biggr)+\lambda\nu \bigl(\nabla T_{h}^{n+1},\nabla\psi_{h}\bigr)= \bigl(b(t_{n+1}),\psi_{h}\bigr),\quad \forall\psi_{h}\in W_{0h}, $$(7)where
$$ \dot{T}_{h}^{n} =\left \{ \textstyle\begin{array}{l@{\quad}l} T_{h}^{n}(\dot{x}), & \dot{x}=x-u^{n}_{h}\tau\in\Omega, \\ 0, & \mbox{otherwise}.\end{array}\displaystyle \right . $$
Remark 2.2
Define \(\dot{\mathcal{X}}_{x}^{n+1}(t)=x-(t_{n+1}-t)u_{h}^{n}\), \(\forall t\in[t_{n-1},t_{n+1}]\), \(2\leq l\leq N\). Since \(X_{h}\) is a subset of \(W^{1,\infty}(\Omega)\), under the condition \(\tau\leq\frac{1}{2L_{n}}\), \(L_{n}=\max_{1\leq i\leq n}\|u_{h}^{n}\|_{W^{1,\infty}}\) on the time step it is an easy matter to verify that this mapping has a positive Jacobian, since \(u_{h}^{n} \) vanishes on ∂Ω; this mapping is one-to-one and this is a change of variables from Ω onto Ω. This yields for any positive function ϕ on Ω the estimate (please see [36] for details)
3 Stability analysis
Theorem 3.1
(Stability)
If \(\tau\leq\frac{1}{2L_{n}}\), \(L_{n}=\max_{1\leq i\leq n}{\|u_{h}^{i}\|_{W^{1,\infty}}}\), the MC projection FEM is stable in the sense that
Remark 3.1
We will prove the boundary of \(\|u_{h}^{n}\|_{W^{1,\infty}}\) in the next section. Here, we use mathematical induction method.
Proof
Let \(v_{h}={u}_{h}^{n+1}\) in (5), we obtain
Using (6), we deduce
Noting \(\nabla\cdot u_{h}^{n+1}=0\), we get
Then we deduce
We arrive at
Now, we estimate the bound of \(\Vert\dot{u}_{h}^{n}\Vert_{0}^{2}-\Vert u_{h}^{n}\Vert_{0}^{2}\). By the definition of \(\dot{\mathcal{X}}_{x}^{n}(t_{n-1})\), we have
Hence,
Then we get
We have
On the other hand, by Cauchy-Schwarz inequality, we deduce
Combining (10), (11), and (12), we get
Let \(\psi_{h}=2\tau T_{h}^{n+1}\) in (7), we obtain
We deduce
Similar to (11), we have
Then we can get
Adding (13) and (15), summing over all n from 0 to N, we can get
Using Gronwall lemma, we deduce
 □
4 Error analysis
In order to get the error analysis, we give some lemmas first.
Lemma 4.1
Let \(e(x,n)= [\frac{u^{n}(x)-\bar{u}^{n-1}(x)}{\tau}- (\frac{\partial u}{\partial t}(x,t_{n})+u^{n}(x) \nabla u^{n}(x) ) ]\) and let \(\tau>0\) be such that \(u\in\mathscr{C}^{4}([\tau,T]; H^{3}(\Omega)^{2})\). For \(t_{n}>\tau\), we have
where \(g_{x}^{n}(t)=u(x-(t_{n}-t)u^{n-1},t)\), \(u^{n}(x)=u(x,t_{n})\).
Lemma 4.2
Let
and let \(\tau>0\) be such that \(T\in\mathscr{C}^{4}([\tau ,T];H^{3}(\Omega))\). For \(t_{n}>\tau\), we have
where \(\gamma_{x}^{n}(t)=T(x-(t_{n}-t)u_{h}^{n-1},t)\), \(u^{n}(x)=u(x,t_{n})\).
Lemma 4.3
There exists \(r_{h}:W\rightarrow W_{h}\); for all \(\psi\in W\) we have
When \(\psi\in W^{r,q}(\Omega)\) (\(1\leq q\leq\infty\)), we have
There exists \(\bar{r}_{h}:W_{0}\rightarrow W_{0h}\); for all \(\psi\in W_{0}\) we have
When \(\psi\in W^{r,q}(\Omega)\) (\(1\leq q\leq\infty\)), we have
Then we define the Galerkin projection \((R_{h},Q_{h})=(R_{h}(u,p),Q_{h}(u,p)):(X,M)\rightarrow(X_{h}, M_{h})\), such that
Lemma 4.4
The Galerkin projection \((R_{h},Q_{h})\) satisfies
4.1 Error estimate for velocity and temperature
Lemma 4.5
If \(\tau\leq\frac{1}{2L_{n}}\), \(L_{n}=\max_{1\leq i\leq n}{\Vert u_{h}^{i}\Vert_{W^{1,\infty}}}\), u, p, \(u_{t}\), and \(p_{t}\) are sufficiently smooth, we have
where \(\hat{\xi}_{h}^{n}=\hat{u}_{h}^{n}-R_{h}^{n}\), \({\xi}_{h}^{n}={u}_{h}^{n}-R_{h}^{n}\), \(\varepsilon_{h}^{n+1}=T_{h}^{n+1}-r_{h}T^{n+1}\), \(R_{h}^{n}=R_{h}(u^{n},p^{n})\), C is a positive constant independent of Ï„ and h.
Proof
Subtracting \((\frac{R_{h}^{n+1}-\dot{R}_{h}^{n}}{\tau},v_{h} )+\nu(\nabla R_{h}^{n+1},\nabla v_{h})\) from both sides of (5), we can get
Defining \(\eta^{n}=u^{n}-R_{h}^{n}\), we can get
Let \(v_{h}=2\tau\hat{\xi}_{h}^{n+1}\) in (26), we can get
where
Now, we estimate each term \(\mathcal{A}_{i}\), respectively. By Hölder inequality, we get
By the definition of ẋ and x̄, we can get
Using Taylor’s formula, we obtain
Therefore, we have
Then we deduce
Now, we estimate the boundedness of \(\mathcal{A}_{3}\). We have
By the definition of \(\hat{\mathcal{X}}_{x}^{n+1}(t_{n})\), we can get
Hence,
Then we get
Let \(G(x)=x-\hat{\mathcal{X}}_{x}^{n+1}(t_{n})^{-1}\), then \(|G(x)|\leq C\tau \), and
Similarly, we have
Then we deduce
Therefore, we get
Similarly, we obtain
For the term \(\mathcal{A}_{5}\), by Taylor’s formula, we can get \(\Vert T^{n+1}-T^{n}\Vert_{0}\leq C\tau\), then
Combining (27), (28), (20), and (34), we arrive at
Subtracting \(\tau^{-1}(r_{h}T^{n+1}-r_{h}\dot{T}^{n},\psi _{h})+\lambda\nu (\nabla r_{h}T^{n+1},\nabla\psi_{h})\) from both sides of (7), we can get
Letting \(\dot{\varepsilon}_{h}^{n+1}=\dot{T}_{h}^{n+1}-r_{h}\dot {T}^{n+1}\), \(\theta^{n+1}=T^{n+1}-r_{h}T^{n+1}\), \(\dot{\theta}^{n}=\dot {T}^{n}-r_{h}\dot{T}^{n}\), and \(\psi_{h}=2\tau\varepsilon_{h}^{n+1}\) in (36), we can get
Similarly to (32), we get
Then we deduce
Namely,
Summing over n from 0 to N gives
By Gronwall lemma, we obtain
Using (6), we get
Let \(v_{h}=2\tau{\xi}_{h}^{n+1}\), we can get
Then we have
Using the inequality (see [41], Remark 1.6 and [19]),
we have
Using the triangle inequality, we deduce
Via the inverse inequality, \(\Vert v_{h}\Vert_{W^{1,\infty}}\leq Ch^{-1}\Vert\nabla v_{h}\Vert_{0}\) (see [36]), we can get
We thus finish the proof. □
Theorem 4.6
(Error estimates for the velocity and temperature)
If \(\tau\leq\frac{1}{2L_{n}}\), u, p, \(u_{t}\), and \(p_{t}\) are sufficiently smooth, we have
Proof
Using triangle inequality, (23), and Lemma 4.3, we can get this theorem. □
4.2 Error estimates for the pressure
The following theorem on the pressure is a consequence of the previous theorem on the velocity.
Theorem 4.7
(Error estimate for pressure)
If \(\tau\leq\frac{1}{2L_{n}}\), u, p, \(u_{t}\), and \(p_{t}\) are sufficiently smooth, we have for all \(1\leq n\leq N\),
Proof
By (6), we deduce
By the LBB condition and Cauchy-Schwarz inequality, we get
Using (27), (28), (20), and (34), we arrive at
Thus, we finish the proof. □
5 Numerical experiments
In order to show the effect of our method, we give some numerical results in this section.
5.1 Bénard convection problem
The first experiments is Bénard convection problem in the domain \(\Omega =[0,5]\times[0,1]\) with the forcing \(f=0\) and \(b=0\). Figure 1 displays the initial and boundary conditions for velocity u and temperature T. It means that the boundary conditions for the velocity are the no-slip boundary condition \(u=0\) on ∂Ω, thermal insulation \(\partial_{\upsilon}T=0\) on the lateral boundaries, and a fixed temperature difference between top and bottom boundaries. Here, we choose \(h=1/16\), \(\tau=0.01\), and the finite element space is a Taylor-Hood finite element space. Here, we use the software package FreeFEM++ [42] for our program.
First, we set \(\kappa=10^{4}\), \(\lambda=1.0\), \(\nu=1.0\). Figure 2 gives the numerical temperature at \(t=0.05, 0.1, 0.15,\mbox{and }1.0\). Figure 3 gives the numerical pressure at \(t=0.05, 0.1, 0.15, \mbox{and }1.0\). Figure 4 gives the numerical streamline at \(t=0.05, 0.1, 0.15, \mbox{and }1.0\).
Then we set \(\kappa=10^{5}\), \(\lambda=1.0\), \(\nu=1.0\). Figure 5 gives the numerical temperature at \(t=0.05, 0.1, 0.15, \mbox{and }1.0\). Figure 6 gives the numerical pressure at \(t=0.05, 0.1, 0.15, \mbox{and }1\). Figure 7 gives the numerical streamline at \(t=0.05, 0.1, 0.15, \mbox{and }1\). From the numerical results, we can see that MCPFEM can simulate the fluid field, temperature field and pressure field very well, and it works well for a high Grashoff number κ.
5.2 Thermal driven cavity flow problem
Here, we consider the thermal driven flow in an enclosed square \(\Omega=[0,1]^{2}\) with the forcing \(f=0\) and \(b=0\), and the initial and boundary conditions are given by Figure 8. It means that the boundary conditions for velocity is no-slip boundary condition \(u=0\) on ∂Ω, and thermal insulation \(\partial_{\upsilon}T=0\) on the top and bottom boundaries, and a fixed temperature difference between left and right boundaries. Here, we choose \(h=1/32\), \(\tau=10^{-4}\), and the finite element space is a Taylor-Hood finite element space.
We choose \(\lambda=1\), \(\nu=1\), \(\kappa=10^{5}\mbox{ and }10^{6}\) respectively. Figures 9 and 10 give the numerical results for \(\kappa=10^{5}\mbox{ and }10^{6}\), respectively. From the numerical results, we can see that MCPFEM can simulate the fluid field, temperature field, and pressure field very well. The numerical experiments confirm our theoretical analysis and demonstrate the efficiency of our method.
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The authors would like to thank the anonymous referees for their valuable suggestions and comments, which helped to improve the quality of the paper. This work of the authors was supported in part by Chinese NSF (Grant Nos. 11301156 and 11401177).
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Si, Z., Wang, Y. Modified characteristics projection finite element method for time-dependent conduction-convection problems. Bound Value Probl 2015, 151 (2015). https://doi.org/10.1186/s13661-015-0420-7
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DOI: https://doi.org/10.1186/s13661-015-0420-7