Abstract
In this paper, we introduce and analyze a high-order, fully-mixed finite element method for the free convection of
n-dimensional fluids,
1 Introduction
Free convective flows can be found in a wide amount of settings throughout nature and industry, for instance, in mantle convection, stratified oceanic flows and the cooling of electronic devices, to name a few. Many of these processes can be modeled by coupling the equations of continuity, momentum (Navier–Stokes) and energy using the Boussinesq approximation, which (in this context) assumes the density of the fluid to be constant in all terms of the equations, except in the buoyancy term of the momentum equation, where a linear dependence is considered. Nevertheless, other properties may also vary with temperature, as is the case of, for example, viscosity and thermal conductivity in oils and nanofluids, which poses a significant effect on the fluid flow. In this regard, several finite element methods to approximate the solution to this and related problems, both with constant and temperature-dependent properties have been proposed (see [2, 3, 4, 5, 6, 8, 12, 13, 14, 22, 23, 25, 26, 27] and the references therein).
In particular, the authors in [22, 23] propose finite element methods based on primal formulations of the Boussinesq system. The first one deals with the problem in its primitive variables, while the second one introduces the normal heat flux through the boundary as an additional variable to achieve conformity of the scheme. Nonetheless, both methods are proved to be optimally convergent whenever the exact solution is smooth enough, and the data and the
The purpose of this work is to extend the analysis and results of [4] by deriving now
an augmented fully-mixed finite element method for the Boussinesq problem, but considering this time both the viscosity and the thermal conductivity of the fluid as temperature-dependent functions, and mixed thermal boundary conditions. To this end, we consider again the mixed formulation of the Navier–Stokes equations in [4], to then, using this same approach, construct a mixed formulation for the energy equation. More precisely, we consider the temperature gradient and pseudoheat vector as additional variables, which together with the temperature, rate of strain, pseudostress, velocity and vorticity comprise the unknowns of the problem. At this point, we remark that the main difference with respect to [13] is the consideration in this work of temperature-dependent parameters, which also becomes the cause of defining the rate of strain and temperature gradient in addition to the variables defined in the aforementioned work (recall from [2] that the vorticity appears in this formulation because of the consideration of a more physical version of the Cauchy stress tensor). That being said, part of our analysis follows basically the same uncoupling and fixed-point strategies from [2, 4, 5, 12, 13], reason why we do not provide all details but
make the proper references when it corresponds. At a continuous level, we prove that the uncoupled problems are well posed thanks to the Lax–Milgram theorem, and then we prove that the fixed-point operator admits a unique fixed point by means of the Banach fixed-point theorem, whenever the data is sufficiently small and assuming that the exact solution has a slightly higher regularity than the one the well-posedness results provide. Then, following these same steps, we provide a well-posedness result for the Galerkin scheme where one of the key features of this work can be appreciated: there is no need to impose inf-sup conditions on the discrete analysis, which gives us the freedom to choose any combination of finite element subspaces. In particular, we approximate the pseudostress and pseudoheat variables using Raviart–Thomas elements of order k, the velocity and temperature using Lagrange elements of order
Finally, we consider worthwhile to mention other features of this fully-mixed method. First, as Dirichlet conditions appear naturally in mixed formulations, it is not necessary to define boundary unknowns to achieve conformity in the scheme (see the Lagrange multiplier defined in [2, 4]), thus unifying the analysis of the uncoupled problems and simplifying the computational implementation of this method. Also, as not only the velocity and temperature of the fluid are part of the solution but also their gradients, many other physical variables of interest can be computed as a simple post-process without requiring numerical differentiations that could deteriorate the good quality of the results. Nevertheless, it is also fair to mention that the use of dual-mixed approaches, and the consequent increase in the number of unknowns, yields much larger linear and nonlinear systems to be solved at the discrete level, and hence, the devising of more efficient numerical methods for computing their solution arises as an unavoidable need. In this regard, we believe that the use of Hybridizable Discontinuous Galerkin Methods (HDG) specially designed for nonlinear problems (see, e.g., [18]), appears as a very attractive possibility to be explored in a separate work.
1.1 Outline
The rest of this paper is organized as follows. First, we end this section by introducing some notation that will be used throughout the paper. Then, in Section 2, we set the Boussinesq problem with temperature-dependent viscosity and thermal conductivity functions, and introduce the new variables that will allow us to construct a fully-mixed formulation. Next, in Section 3, we uncouple the problem using a fixed-point argument. The uncoupled problems are then analyzed by means of the Lax–Milgram theorem, and existence of a unique fixed point is proved by fulfilling the hypotheses of the Banach fixed-point theorem. Later, in Section 4 these techniques are used to prove the well-posedness of the corresponding Galerkin scheme, but this time using the Brouwer fixed-point theorem, and then we make a specific choice of finite element subspaces. Finally, in Section 5 we derive some a priori error estimates by suitably applying the usual Strang’s lemmas for linear problems, to then in Section 6 illustrate the good performance of this augmented fully-mixed finite element method and confirm the theoretical rates of convergence through several numerical examples in two and three dimensions.
1.2 Preliminaries
Let us denote by
In addition, for any tensor fields
where
equipped with the usual norm
is a standard Hilbert space in the realm of mixed problems. Finally, in what follows,
2 The Model Problem
In this section, we first introduce the Boussinesq problem with its original unknowns, to then define suitable new variables that will later allow us to construct a fully-mixed formulation.
2.1 The Original Formulation
Let us consider the flow of a non-isothermal, incompressible, Newtonian fluid with varying viscosity and thermal conductivity within a region Ω. Then, under the Boussinesq approximation, the problem reads: Find a velocity
(2.1)
where
2.2 Introduction of New Variables
Let us first consider the spaces
and, in a similar way to [4], define the following variables, known respectively as the rate of strain, pseudostress and vorticity tensors:
where
(2.2)
Notice that the continuity equation is implicitly present in (2.2b), and it suggests us that rate of strain tensor
Next, in order to construct a mixed formulation for the energy equation, we follow the approach taken in [9, 13] and define
which from now on will be called “pseudoheat”. In addition, analogously to the mixed formulation for the momentum equation, we consider the temperature gradient as another new variable
Therefore, the energy equation (2.1c) can be rewritten in these terms as
(2.3)
where the Neumann condition (2.1f) has been converted to (2.3e) thanks to the no-slip condition
In this way, the Boussinesq problem (2.1) can now be seen as the set of equations (2.2) and (2.3). Then a mixed formulation of each one of them can be constructed upon integration by parts of (2.2a) and (2.3a) when multiplied by proper test functions, which is the purpose of the next section.
3 The Continuous Problem
We now turn to the construction and analysis of a fully-mixed formulation for the Boussinesq problem introduced in the previous section.
3.1 An Augmented Fully-Mixed Formulation
First, we recall from [4] the equations corresponding to the mixed formulation of the momentum equation:
where
Then, to obtain a mixed formulation for the energy equation, we multiply equation (2.3a) by a test function
and integrate by parts. Using the boundary condition (2.3d), we get
where
Notice that, due to the second term in both (3.2) and (3.5), we require the velocity and temperature to have (weak) bounded derivatives as shown in the following inequalities, which can be obtained by using the Hölder inequality and the continuous injections
where
for the momentum and continuity equations, and
for the energy equations, where
Remark 3.1.
We now stress that the incorporation of equations (3.9)–(3.12), which are extracted directly from [4], allows us to establish the ellipticity of the resulting bilinear form (cf. proof of Lemma 3.3 below). The same reason applies to the introduction of (3.13)–(3.16) (cf. proof of Lemma 3.4 below). In turn, the concept “redundant” employed here refers to the fact that the equations yielding these augmented terms have already been considered before for the derivation of the weak formulation, but tested differently to the way they are tested now in (3.9)–(3.12) and (3.13)–(3.16).
In this way, denoting by
and
the augmented fully-mixed formulation for this Boussinesq problem is: Find
(3.17)
where, given
for all
for all
for all
Remark 3.2.
Before we continue, let us have a brief look at what the energy equation (2.1c) would have looked like if we had considered instead a heat-temperature mixed formulation. Indeed, if we define
equation (2.1c) can be rewritten as
Then, multiplying the first equation by a test function
for all
where
In the upcoming sections, we analyze problem (3.17) using fixed-point strategies from [2, 4, 5, 13]. More precisely, in Section 3.2 we rewrite (3.17) as a fixed-point problem, in Section 3.3 we prove the main results stated and employed in Section 3.2, and then in Section 3.4 we establish sufficient conditions for existence and uniqueness of this fixed point.
3.2 The Fixed-Point Approach
First, let us define
where
In turn, consider the operator
where
The well-definedness of the mappings
Lemma 3.3.
Assume that for
where
Lemma 3.4.
Assume that for
Then there exists
Consequently, we can define the operator
and look at (3.17) as the fixed-point problem: Find
Indeed, we begin the corresponding analysis by showing next that the operator
Lemma 3.5.
Given
Assume that the stabilization parameters
with
Proof.
Let
3.3 Proofs of Lemmas 3.3 and 3.4
As usual, we consider
and
Proof of Lemma 3.3.
Notice that an analogous result has been proved in [4, Lemma 2.3] for the case where a non-homogeneous velocity boundary condition is imposed, however, since we want to find
We begin by analyzing the ellipticity of the bilinear form
Then, using the bounds for the viscosity and the Cauchy–Schwarz and Young inequalities, we obtain for
any
Note here, in particular, that in order to get positive quantities multiplying
whereas the norm of
where
we deduce the existence of a positive constant
The rest of the proof is identical to [4, Lemma 2.3], but we recall it for completion purposes.
Thus, the foregoing inequality, the definition of
and then, we easily see that
provided that
that is,
thus proving ellipticity for
Therefore, by the Lax–Milgram theorem, there exists a unique
Next, we recall the following Poincaré-type inequality that will help us to prove the ellipticity of the
bilinear form defining the operator
Lemma 3.6.
There exists
Proof.
See [20, Theorem 5.11.2]. ∎
Proof of Lemma 3.4.
Let
thus obtaining the existence of a positive constant
For
Hence, from the previous two equations, there exists a positive constant denoted by
Next, to prove that
Then, using the bounds for the thermal conductivity function, the Cauchy–Schwarz and Young inequalities, we get for any
Hence, applying Lemma 3.6 and defining the constants
there exists
which, together with (3.21) and inequality (3.8), allows us to write
Therefore, we easily see that
provided that
that is,
thus proving ellipticity for
and
and then, using the continuous injection from
such that
Since
At this point we remark that, while (3.36) and (3.39) guarantee
the ellipticities of
We end this subsection by commenting that for computational purposes, a particular choice of stabilization
parameters has to be made. Hence, we first consider the middle points of the intervals for
Notice that
3.4 Solvability Analysis of the Fixed-Point Problem
In this subsection, we pursue to comply with the hypotheses of the Banach fixed-point theorem to ensure existence and uniqueness of a fixed point. More precisely, the main results of this subsection are stated as follows.
Lemma 3.7.
Let
with
where
and
Theorem 3.8.
Let
(3.42)
with constants
and
In order to prove Lemma 3.7 and Theorem 3.8, we first recall from (3.33)
that
Therefore, it only remains to prove that
and (following (3.28))
and on the other hand, that
and (following (3.29))
Here,
Lemma 3.9.
Let
(3.46)
for all
Proof.
See [4, Lemma 2.6]. ∎
We stress here that Lemma 3.9 makes use precisely of the regularity assumption (3.44)
and the fact, that under the specified range of ε,
Lemma 3.10.
Let
for all
Proof.
Let
Then, defining the constants
the result (3.47) holds with
In a similar way, we show next that the operator
Lemma 3.11.
Let
for all
Proof.
Let
it follows that
for any
The last term in the previous inequality can be easily split using (3.8), that is,
whereas for the first term we use the Hölder inequality to show that
with
and hence, there exists
In this way,
and (3.51) now yields
Since
such that
for any
thus obtaining (3.48) with
Consequently, the proof of Lemma 3.7, that is, the Lipschitz-continuity
of
Proof of Lemma 3.7.
Let
The bound for the first term comes directly from (3.47),
whereas for the second one, we first use the Lipschitz-continuity of
Summarizing, Lemma 3.5 ensures us that
Proof of Theorem 3.8.
Notice that (3.42a) ensures that both (3.32) and (3.43)
hold, so that
4 The Galerkin Scheme
We advocate in this section to present the Galerkin scheme for the continuous problem (3.17), whose well-posedness will be proved using the same steps and methods as in the previous section.
4.1 Preliminaries
Let us consider
and
Hence, according to the continuous formulation (3.17), the Galerkin scheme reads: Find
(4.1)
where the forms
We will see that it is possible to establish sufficient conditions for well-posedness of (4.1)
in the same form they were established for the continuous problem (3.17). To this end,
we now split the discrete formulation into the two corresponding mixed formulations.
In fact, we first set
where
In turn, we let
where
Therefore, by introducing the operator
we can rewrite (4.1) as the fixed-point problem: Find
In this case, existence of a fixed point for this problem will be proved by means of the Brouwer fixed-point theorem, which we recall next.
Theorem 4.1 (Brouwer).
Let W be a compact and convex subset of a finite-dimensional Banach space, and let
Proof.
See [10, Theorem 9.9-2]. ∎
4.2 Solvability Analysis
We first study under which conditions
Lemma 4.2.
Assume that for
where
with
Proof.
It follows from a direct application of the Lax–Milgram theorem to (4.2) in the same way it was applied in Lemma 3.3. ∎
Lemma 4.3.
Assume that for
Then, for each
with
Proof.
It also follows from an application of the Lax–Milgram theorem to (4.3) in the same way it was applied in Lemma 3.4. ∎
Analogously to the continuous case, the previous two lemmas provide the well-definedness of the operator
Lemma 4.4.
Given
Assume that the stabilization parameters
Moreover,
We now turn to prove the continuity of
Lemma 4.5.
Let
for all
Proof.
It comes from [4, Lemma 2.6], but employing an
Lemma 4.6.
Let
for all
Proof.
As in the previous lemma, the proof is based on the one for its continuous counterpart Lemma 3.11, but just taking
Consequently, we have the following result for the operator
Lemma 4.7.
Given
for all
Proof.
Let
and since (3.41) holds,
where
Having proved that
Theorem 4.8.
Let
and
4.3 Specific Finite Element Subspaces
An interesting point to realize in this fully-mixed approach with respect to the finite-dimensional subspaces
is that we have not imposed any kind of inf-sup conditions as in [2, 4],
or any other requirement than being finite-dimensional, which give us the chance to freely choose these subspaces.
In particular, the most natural finite element subspaces of
where according to the terminology described in Section 1,
According to [7, 16], their corresponding approximation properties are as follows.
$(\mathbf{AP}_{h}^{\mathbf{t}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\boldsymbol{\sigma}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\mathbf{u}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\boldsymbol{\gamma}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\boldsymbol{\zeta}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\mathbf{p}})$.
There exists a constant
$(\mathbf{AP}_{h}^{\varphi})$.
There exists a constant
5 A Priori Error Analysis
Let
(5.1)
and
(5.2)
In addition, we denote as usual
Then the main result of this section reads as follows.
Theorem 5.1.
Assume that the data satisfy
where
Similar to [2, Lemma 5.3] and [4, Lemma 4.2], we will apply the
Strang Lemma to the pair of equations (5.1) and (5.2) separately,
to then join the resulting estimates to derive the Céa estimate (5.4).
In this regard, we emphasize that, given arbitrary
Lemma 5.2 (Strang).
Let V be a Hilbert space, let
In turn, let
Then, for each
where
Proof.
See [11, Theorem 11.1]. ∎
Lemma 5.3.
Let
Proof.
See [4, Lemma 4.2]. ∎
Lemma 5.4.
Let
(5.5)
Proof.
It is clear from (3.29) that
where
In what follows we make use of the boundedness constants
which back into (5.6) gives (5.5), concluding this way the proof. ∎
As a result of the previous two lemmas, we have a preliminary estimate for the error:
(5.7)
where
all being positive constants independent of the discretization parameters. Thus, we first bound the terms
inequality (5.7) becomes
thus leading us to the main result of this section, that is, to Theorem 5.1.
In fact, thanks to (5.3), the estimate (5.8)
readily implies (5.4) with
Consequently, when using the finite element subspaces (4.9)–(4.15), the following can be established regarding the rates of convergence of the method.
Lemma 5.5.
In addition to the hypotheses of Theorems 3.8, 4.8 and 5.1, assume that there exists
6 Numerical Results
We now present two examples that will illustrate the performance of the augmented fully-mixed finite element
method (4.1) with the subspaces indicated in (4.9)–(4.15)
on a set of quasiuniform triangulations. This means that, given an integer
where tol is a specified tolerance.
Let us first define the error per variable
as well as their corresponding rates of convergence
where h and
6.1 Example 1: Two-Dimensional Smooth Exact Solution
In our first example, we consider
Dirichlet boundary conditions will be imposed on
where
with
and
Concerning the stabilization parameters, these are taken as pointed out at the end of Section 3.3,
with
In Figure 1 we display part of the solution obtained with fully-mixed finite element
method using a first-order approximation and 1,409,884 DOF. Notice that not only we are able to recover
the original unknowns but also to compute further variables of physical interest.
In turn, Tables 1 and 2 show the convergence history for a sequence
of quasi-uniform mesh refinements, thus confirming the rates of convergence predicted by
Lemma 5.5, that is, when using first and second-order finite elements,
and considering that the exact solution is smooth enough, whence the method converges with
orders
Convergence history for Example 1, with a uniform mesh refinement and a first-order approximation.Here, the simulation with 1,816 DOF took ten fixed-point iterations, while the rest of them took nine iterationsto achieve a tolerance of
| Finite Element: | ||||||||
| DOF | ||||||||
| 1,816 | 4.5307 | 15.6976 | 7.7257 | 2.3619 | 14.3622 | 0.4298 | 1.5650 | 0.3698 |
| 6,972 | 2.1933 | 7.9406 | 3.3074 | 1.0874 | 8.8796 | 0.2124 | 0.7864 | 0.1758 |
| 27,052 | 1.0947 | 3.9421 | 1.6088 | 0.5396 | 6.0695 | 0.1022 | 0.3809 | 0.0831 |
| 107,142 | 0.5331 | 2.0064 | 0.8011 | 0.2678 | 2.5649 | 0.0517 | 0.1962 | 0.0426 |
| 431,398 | 0.2581 | 0.9882 | 0.3925 | 0.1216 | 1.5602 | 0.0259 | 0.0970 | 0.0211 |
| 1,707,922 | 0.1271 | 0.4937 | 0.1947 | 0.0613 | 0.7027 | 0.0127 | 0.0482 | 0.0105 |
| h | ||||||||
| 0.4129 | – | – | – | – | – | – | – | – |
| 0.1940 | 0.9605 | 0.9023 | 1.1233 | 1.0270 | 0.6366 | 0.9331 | 0.9111 | 0.9845 |
| 0.0995 | 1.0402 | 1.0482 | 1.0788 | 1.0490 | 0.5695 | 1.0951 | 1.0851 | 1.1221 |
| 0.0527 | 1.1333 | 1.0638 | 1.0982 | 1.1032 | 1.3567 | 1.0736 | 1.0453 | 1.0521 |
| 0.0311 | 1.3744 | 1.3419 | 1.3519 | 1.4961 | 0.9419 | 1.3087 | 1.3350 | 1.3342 |
| 0.0150 | 0.9729 | 0.9535 | 0.9635 | 0.9411 | 1.0960 | 0.9778 | 0.9600 | 0.9503 |
Convergence history for Example 1, with a uniform mesh refinement and a second-order approximation.Here, all the simulations took nine fixed-point iterations to achieve a tolerance of
| Finite Element: | ||||||||
| DOF | ||||||||
| 5,812 | 0.9568 | 3.0676 | 1.3170 | 0.6622 | 2.2406 | 0.0690 | 0.2052 | 0.0434 |
| 22,564 | 0.2193 | 0.7735 | 0.3002 | 0.1932 | 0.6699 | 0.0154 | 0.0467 | 0.0098 |
| 88,036 | 0.0554 | 0.1939 | 0.0750 | 0.0472 | 0.2187 | 0.0038 | 0.0118 | 0.0023 |
| 349,660 | 0.0140 | 0.0494 | 0.0192 | 0.0119 | 0.0494 | 0.0010 | 0.0031 | 0.0006 |
| 1,409,884 | 0.0035 | 0.0121 | 0.0047 | 0.0029 | 0.0152 | 0.0002 | 0.0008 | 0.0001 |
| h | ||||||||
| 0.4129 | – | – | – | – | – | – | – | – |
| 0.1940 | 1.9507 | 1.8241 | 1.9580 | 1.6310 | 1.5987 | 1.9811 | 1.9595 | 1.9687 |
| 0.0995 | 2.0591 | 2.0712 | 2.0759 | 2.1084 | 1.6752 | 2.1123 | 2.0631 | 2.1848 |
| 0.0527 | 2.1678 | 2.1538 | 2.1490 | 2.1666 | 2.3443 | 2.0727 | 2.1265 | 2.1000 |
| 0.0311 | 2.6452 | 2.6677 | 2.6506 | 2.6598 | 2.2355 | 2.6761 | 2.6587 | 2.6447 |









Numerical Results for Example 1. From left to right and from up to down: XX-component of the Rate of Strain tensor, true vorticity magnitude (computed as twice the YX-component of the full vorticity tensor), Y-component of the temperature gradient, XX and YY components of the pseudostress tensor, pseudoheat magnitude and its vector field, velocity magnitude and its vector field, pressure and temperature. Snapshots obtained from a simulation with 1,409,884 DOF and a second-order approximation.
6.2 Example 2: Three-Dimensional Smooth Exact Solution
In our second example, we consider
With respect to boundary conditions, we impose Dirichlet conditions on
with
and
Concerning the stabilization parameters, we take them again as in Section 3.3,
but this time with
Part of the solution is displayed in Figure 2,
and a convergence history for a set of quasi-uniform mesh refinements is provided
in Table 3, thus showing also that, having the problem a smooth exact solution, this
fully-mixed finite element method converges optimally with order









Numerical Results for Example 2. From left to right and from up to down: XY and ZZ components of the rate of strain tensor (the last one postprocessed as
Convergence history for Example 2, with a uniform mesh refinement and a first-order approximation.Here, to achieve a tolerance of
| Finite Element: | ||||||||
| DOF | ||||||||
| 1,117 | 0.0219 | 0.2559 | 0.0420 | 0.0249 | 0.0262 | 0.7239 | 17.6230 | 1.2979 |
| 8,181 | 0.0128 | 0.1367 | 0.0265 | 0.0176 | 0.0196 | 0.4249 | 8.0953 | 0.6128 |
| 62,821 | 0.0079 | 0.0700 | 0.0140 | 0.0097 | 0.0132 | 0.2240 | 4.3469 | 0.3044 |
| 492,741 | 0.0042 | 0.0351 | 0.0071 | 0.0047 | 0.0077 | 0.1137 | 2.1971 | 0.1505 |
| 3,903,877 | 0.0022 | 0.0175 | 0.0035 | 0.0022 | 0.0040 | 0.0571 | 1.1017 | 0.0750 |
| h | ||||||||
| 0.7071 | – | – | – | – | – | – | – | – |
| 0.3536 | 0.7778 | 0.9044 | 0.6636 | 0.4972 | 0.4220 | 0.7689 | 1.1223 | 1.0828 |
| 0.1768 | 0.7024 | 0.9661 | 0.9205 | 0.8660 | 0.5634 | 0.9235 | 0.8971 | 1.0094 |
| 0.0884 | 0.9094 | 0.9951 | 0.9871 | 1.0518 | 0.7899 | 0.9788 | 0.9844 | 1.0165 |
| 0.0442 | 0.9513 | 1.0018 | 1.0000 | 1.0742 | 0.9191 | 0.9943 | 0.9958 | 1.0044 |
Funding statement: This research was partially supported by CONICYT-Chile through the project AFB170001 of the PIA Program: Concurso Apoyo a Centros Científicos y Tecnológicos de Excelencia con Financiamiento Basal; and by Centro de Investigación en Ingeniería Matemática (CI2MA), Universidad de Concepción.
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Articles in the same Issue
- Frontmatter
- A Fully-Mixed Finite Element Method for the n-Dimensional Boussinesq Problem with Temperature-Dependent Parameters
- Asymptotically Exact A Posteriori Error Analysis for the Mixed Laplace Eigenvalue Problem
- A Hybrid High-Order Discretization Method for Nonlinear Poroelasticity
- Stable Non-symmetric Coupling of the Finite Volume Method and the Boundary Element Method for Convection-Dominated Parabolic-Elliptic Interface Problems
- Crouzeix–Raviart Finite Element Approximation for the Parabolic Obstacle Problem
- Reliable Numerical Solution of a Class of Nonlinear Elliptic Problems Generated by the Poisson–Boltzmann Equation
- Simplified Iteratively Regularized Gauss–Newton Method in Banach Spaces Under a General Source Condition
- Convergence and Preconditioning of Inexact Inverse Subspace Iteration for Generalized Eigenvalue Problems
- Composite Finite Element Approximation for Parabolic Problems in Nonconvex Polygonal Domains
- A Nitsche-eXtended Finite Element Method for Distributed Optimal Control Problems of Elliptic Interface Equations
- Retraction of: Stabilizability of Infinite-Dimensional Systems by Finite-Dimensional Controls
Articles in the same Issue
- Frontmatter
- A Fully-Mixed Finite Element Method for the n-Dimensional Boussinesq Problem with Temperature-Dependent Parameters
- Asymptotically Exact A Posteriori Error Analysis for the Mixed Laplace Eigenvalue Problem
- A Hybrid High-Order Discretization Method for Nonlinear Poroelasticity
- Stable Non-symmetric Coupling of the Finite Volume Method and the Boundary Element Method for Convection-Dominated Parabolic-Elliptic Interface Problems
- Crouzeix–Raviart Finite Element Approximation for the Parabolic Obstacle Problem
- Reliable Numerical Solution of a Class of Nonlinear Elliptic Problems Generated by the Poisson–Boltzmann Equation
- Simplified Iteratively Regularized Gauss–Newton Method in Banach Spaces Under a General Source Condition
- Convergence and Preconditioning of Inexact Inverse Subspace Iteration for Generalized Eigenvalue Problems
- Composite Finite Element Approximation for Parabolic Problems in Nonconvex Polygonal Domains
- A Nitsche-eXtended Finite Element Method for Distributed Optimal Control Problems of Elliptic Interface Equations
- Retraction of: Stabilizability of Infinite-Dimensional Systems by Finite-Dimensional Controls