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WCNS schemes and some recent developments
Advances in Aerodynamics volumeÂ 6, ArticleÂ number:Â 2 (2024)
Abstract
Weighted compact nonlinear schemes (WCNS) are a family of nonlinear shock capturing schemes that are suitable for solving problems with discontinuous solutions. The schemes are based on grids staggered by flux points and solution points, resulting in algorithms with the nonlinear interpolation step independent of the difference step. Thus, only linear difference operators are needed, such that geometric conservation law can be preserved easily, resulting in the preservation of freestream condition. In recent years, these schemes haveÂ attracted a lot of attention in the community of computational fluid dynamics. This paper intends to give a brief review of the basic algorithms of these schemes and present some related recent developments.
1 Introduction
With the fast growth of computational capability, highorder methods play aÂ more and more important role in the field of computational fluid dynamics. Highorder schemes, usually referred to schemes with convergence rates higher than secondorder, admit better resolution properties than their lower order counterparts. More importantly, highorder schemes may produce more accurate results than loworder schemes in terms of using the same computational cost. In the past three decades, great progress has been achieved for highorder schemes. Some representative schemes are widely used, such as weighted essentially nonoscillatory (WENO) schemes [1,2,3], weighted compact nonlinear schemes (WCNS) [4], discontinuous Galerkin schemes [5,6,7], spectral difference schemes [8,9,10], flux reconstruction schemes [11, 12], and so on.
WCNS schemes are a family of highorder schemes that are suitable for solving problems with discontinuous solutions. These schemes are originally developed for addressing shockcapturing problems of compact linear schemes [13]. Although dissipation can be introduced to improve the shock capturing capability of compact linear schemes [14], oscillations are difficult to be removed for strong shocks. Therefore, nonlinear schemes are often needed. In [15, 16], based on grids staggered by flux points and solution points, compact nonlinear schemes were developed by employing the idea of ENO schemes for the interpolation step. Later on, the idea of WENO schemes was introduced further to construct WCNS schemes [4, 17]. Since then, WCNS schemes were further developed and widely used in applications [18]. Some benchmark examples were presented in [19] to demonstrate the efficiency of WCNS schemes. They were used in Reynoldsaveraged NavierStokes (RANS) simulations [20,21,22,23,24,25,26], large eddy simulations (LES) [27,28,29,30,31,32], hybrid RANS/LES simulations [33, 34], and even direct numerical simulations (DNS) [35]. Some important phenomena were also investigated by applying these schemes. The areas include boundary layer transition [36,37,38,39,40], acoustic wave [41,42,43,44], vortices [45], interaction between shock wave and vortex [46, 47], detonation [48,49,50], bodywake interactions [51], Mach reflection [52], elasticplastic deformation [53], multicomponent compressible flows [54], magnetohydrodynamics [55], and so on.
Compared with WENO schemes, WCNS schemes have some advantages, mainly lying in the flexibility of the choice of numerical fluxes and the convenience of preserving geometric conservation law. In this paper, we provide a brief review of WCNS schemes, aiming at introducing some basic ideas of the algorithms and presenting some recent developments. The rest of this paper is arranged as follows. In SectionÂ 2, the basic algorithm of WCNS schemes is given. In SectionÂ 3, conservative boundary closures are discussed. In SectionÂ 4, geometric conservation law that arises from coordinate transform is presented. To preserve this law numerically, a symmetric conservative metric method (SCMM) is also introduced. Finally, concluding remarks are given in SectionÂ 5.
2 Algorithm of WCNS schemes
To describe WCNS schemes, let us consider the onedimensional conservation law
where \(u=u(x,t)\) denotes the conservative quantity and f(u) is the flux. As illustrated in Fig. 1, the spatial interval [a,Â b] is divided into N subintervals by flux points
where \(h = (ba)/N\) stands for the length of the interval. The solution points, denoted by \(x_j\), are placed at the center of the subintervals \([x_{j1/2},x_{j+1/2}]\), i.e.,
2.1 Basic procedure
At time t, suppose the values of u at solution points \(x_j\) are known, denoted by \(u_j\). Then the spatial discretization algorithm of WCNS schemes can be summarized as the following three steps:

(i)
Apply interpolation schemes to obtain the left and right values at flux points \(x_{j+1/2}\), denoted by \(u_{j+1/2}^L\) and \(u_{j+1/2}^R\), respectively.

(ii)
Compute the numerical flux \(f_{j+1/2}=\hat{f}\left(u_{j+1/2}^L,u_{j+1/2}^R\right)\), where \(\hat{f}\) denotes some approximate Riemann solvers.

(iii)
Employ difference schemes to calculate the flux derivatives at solution points \(x_{j}\), denoted by \(f^\prime _{j}\).
After spatial discretization, we obtain a system of ordinary differential equations
which can be solved by some timemarching schemes, such as the explicit RungeKutta scheme [56], the twostage fourthorder scheme [57], and some other implicit schemes [58, 59]. It shall be mentioned that one can also perform interpolation for the flux directly as done in [60]. However, in that case the nonlinearity is performed for the flux, leading to the difficulty in preserving geometric conservation law, which is very important for applications to complex configurations.
2.2 Interpolation schemes
For the interpolation step, many interpolation schemes can be applied. For smooth solutions, linear interpolation schemes can be applied, such as explicit upwind interpolation schemes [61], compact upwind linear interpolation schemes [13], dissipative compact linear interpolation schemes [62, 63], and so on.
Here, we introduce a fifthorder interpolation scheme [4] for the left values, while the right values can be obtained according to the symmetry property of the grids. As illustrated in Fig. 2, to get the left values \(u_{j+1/2}^L\) at flux points \(x_{j+1/2}\), the following explicit upwind fifthorder interpolation scheme can be derived, i.e.,
where the coefficients can be obtained by using the method of Lagrangian interpolation. However, this scheme is not suitable for the case with discontinuous solutions. To address this problem, one may first decompose the fifthorder scheme (5) as
where \(u_{j+1/2}^{(k)}\) are thirdorder interpolation schemes with different stencils, expressed as
and \(\gamma _k\) are linear optimal weights with values
Then, following the recipe of WENO schemes [3] we introduce nonlinear weights defined by
where
Here, the small parameter \(\varepsilon\) is set to be \(10^{6}\) to avoid the denominator becoming zero, and \(\beta _k\) are smoothness indicators of the interpolation schemes applied to compute \(u_{j+1/2}^{(k)}\), defined by
Finally, we obtain the fifthorder shock capturing interpolation scheme
However, it was pointed out in [64] that the scheme (16) based on the nonlinear weights defined by Eqs.Â (11) and (12) may degenerate to thirdorder at critical points. To address this issue, one can implement the idea of improving the performance of WENO schemes for the nonlinear interpolation step of WCNS schemes. In particular, we present here a recent work [65] such that the optimal fifthorder convergence rate can be achieved for any smooth solutions, i.e., regardless of the order of critical points. The scheme can still be written in the form of Eq.Â (16), where \(\omega _k\) are still given by Eq.Â (11), but with \(\alpha _k\) defined by
Here, \(\beta _k\) are still given by Eqs.Â (13)(15), and \(\lambda\) is a parameter defined by
where
It can be seen from Fig. 3 that \(\alpha _k\) are more sensitive to the values of \(\beta _k\) for smaller value of \(\lambda\). For smooth solutions, the definition of \(\lambda\) (18) satisfies the condition
Since the smoothness indicators defined by Eqs.Â (13)(15) obey the relations \(\beta _k = \mathcal {O}(h^2)\), we have
This condition ensures that the corresponding scheme (16) is fifthorder, regardless of the order of critical points.
There are some other methods for improving the performance of the nonlinear interpolation schemes. For example, lowdissipation WCNS schemes were constructed in [66,67,68,69,70,71]. In [72,73,74], compact nonlinear interpolation schemes were developed to improve the resolution of WCNS schemes. The ideas of targeted ENO schemes and multiresolution WENO schemes were introduced for the interpolation step of WCNS schemes in [75] and [76, 77], respectively. A parameterfree \(\varepsilon\)adaptive algorithm was also proposed in [78, 79] to improve the performance of WCNS schemes.
2.3 Difference schemes
By using interpolation schemes, we can get the left and right values at flux points \(x_{j+1/2}\). Then various approximate Riemann solvers [80,81,82] can be applied to compute the numerical fluxes \(f_{j+1/2}\) at flux points \(x_{j+1/2}\). It shall be mentioned that both flux vector splitting and flux difference splitting methods are applicable here for WCNS schemes, while only flux vector splitting methods can be applied for reconstructionbased WENO schemes. In [83,84,85,86], the effect of flux evaluation methods for WCNS schemes was investigated in details. Here we pay attention to difference schemes.
It was shown in [87, 88] that the resolution of WCNS schemes is dominated by the compactness of the interpolation step, while it is less related to the difference step. Therefore, the difference scheme is usually chosen to be an explicit one for the purpose of efficiency. For instance, the sixthorder explicit central difference scheme presented in [87, 89] reads as
For the reason of robustness, some other hybrid difference schemes involving both the fluxes at flux points and solution points can also be used. For example, the sixthorder scheme presented in [90] can be written as
where \(\alpha \ge 0\) is a parameter that can be tuned to control its dissipation property. The sixthorder difference scheme implemented in [91] is expressed as
It was shown that WCNS schemes can benefit from linear difference operators in terms of preserving geometric conservation law [92, 93]. It shall also be mentioned that alternative WENO schemes were proposed in [94], where the WENO reconstruction is employed for the variable rather than the flux. Thus, linear difference operators can be applied directly. It shall be mentioned that the alternative WENO schemes are closely related to WCNS schemes, as pointed out in [95, 96]. Since it is not easy to find the original conference paper [95] for the derivation in details, we present the demonstration of the relation in Appendix A.
3 Conservative boundary closures
Compared to interior schemes of WCNS schemes, boundary closures are seldom considered theoretically. Although some concerns have been mentioned in previous works, the stability issue has not been clearly investigated. By using the result of Gustafsson [97], the order of boundary closures should be at most one order lower than that of the interior for firstorder hyperbolic conservation laws. Otherwise, the global convergence rate cannot be equal to the order of the interior. For Cartesian grids, the inverse LaxWendroff method [98,99,100] may be applied to derive the boundary closures. However, this method is difficult for applications to practical problems. In most cases, we may need curvilinear grids and apply biased schemes near boundary.
For WCNS schemes, conservative boundary closures were derived based on global conservation in [61]. Some applications can also be found in [101, 102]. The derivation is based on the difference scheme consisting of only flux points, like the sixthorder difference scheme (5). For aÂ more general case, we introduce here the method used in [61] and consider the 2rthorder difference scheme
where the coefficients \(\alpha _k\) can be determined according to the order condition. For instance, one can apply the method of Lagrangian interpolation to get the values of \(\alpha _k\) as tabulated in TableÂ 1 for \(2\le r \le 6\).
To mimic the global conservation property of the onedimensional conservation law (1), i.e.,
we first rewrite the interior difference scheme (25) into a conservative form
where
Then we define the interior operator as
Finally, we introduce the left and right boundary operators, written respectively as
and
such that the following global conservation property holds
Now what we need to do is just to decompose the boundary operators as the sum of the difference schemes at solution points near boundary. Due to the symmetry property of the grid, we only have to consider the case for the left. It was shown in [61] that
which means that there must be as least a near boundary difference scheme with only first order of accuracy if we require \(\mathcal {L}[f] = \sum _{j=1}^{r1} f^\prime _j\). To address this issue, we modified Eq. (33) to be
where the \(2r2\) unknowns, \(\omega _j\) and \(x_j^*\), are determined by the conditions of the accuracy. Here, the new introduced solution points \(x_j^*\) are nonuniformly distributed, which are called conservative solution points. The detailed values of \(\omega _j\) and \(x_j^*\) can be found in [61]; see Eqs. (32)(36) therein. That is to say, we replace the solution points near boundary with the conservative points and consider socalled semiuniform grids, where the flux points are still uniformly distributed, as illustrated in Fig. 4.
To determine the conservative difference schemes near boundary, we first require that
Then we set the schemes \(f^\prime _j\) to be \((2r2)\)thorder, determined by the following stencils
where the coefficients \(a_{j,k}\) can be determined conveniently by using the method of Lagrangian interpolation. For the righthand side, the boundary closures for the difference scheme can be obtained symmetrically.
For the interpolation step, we just need to apply interpolation schemes with biased stencils. Then we can construct boundary closures that are time stable up to eleventh order of global accuracy. For problems with discontinuous solutions near boundary, nonlinear shockcapturing boundary interpolation schemes were proposed recently in [103]. It was shown that the shockcapturing issue near boundary can be resolved well by using the idea of multiresolution interpolation and the technique of tuning parameter in the smoothness indicators.
4 Geometric conservation law and SCMM method
For practical applications, it often necessitates to apply curvilinear grids. In that case, we shall consider conservation law in curvilinear coordinates. Since the pioneering work [104], some problems related to geometric conservation law have been studied by many researchers [92, 93, 105,106,107,108,109]. According to [110], the geometric conservation law can be classified as surface conservation law and volume conservation law. For static curvilinear grids, which is the case considered in this paper, the volume conservation law is satisfied automatically. Thus, we only need to consider the surface conservation law.
4.1 Surface conservation law
To describe the definition of the surface conservation law, let us consider the threedimensional conservation law, written as
where U denotes the conservative quantity, andÂ F, G and H are fluxes in x, y and z directions, respectively. In curvilinear coordinates (\(\xi ,\eta ,\zeta\)) [111],Â Eq. (37) can be expressed as
where \(\mathcal {F}=(F,G,H)\) is the tensor of the fluxes, andÂ the Jacobian term J is defined as
and the surface vectors \(\textbf{S}^{(\xi )}\), \(\textbf{S}^{(\eta )}\) and \(\textbf{S}^{(\zeta )}\) are determined by
with \(\textbf{r}=(x,y,z)^T\). It is straightforward to check that the following relation holds, i.e.,
which is the socalled surface conservation law.
4.2 SCMM method
In the context of discretization space, the surface conservation law (41) may not hold exactly, leading to geometric induced errors in the solution. It was shown that preserving the surface conservation law discretely is very important for highorder finite different schemes [106].
For loworder algorithms [104, 112], some techniques can be made to satisfy the surface conservation law discretely. For highorder finite different schemes, according to the knowledge of the authors, the most satisfied way so far is to apply the SCMM method with linear difference operators. This method is a further development of the conservative metric method (CMM) proposed in [92]. The CMM method can maintain the freestream property of the original conservation law and also improve the behavior of WCNS schemes for applications to curvilinear coordinates [18]. However, the CMM method does not admit appropriate geometric meaning that is similar with finite volume methods. To address this issue, the SCMM method was proposed in [93].
The SCMM method is based on the symmetric conservative form of the Jacobian (39) and the surface vectors (40), where the Jacobian is written as
and the surface vectors are expressed as
For the SCMM method, linear difference operators are applied to discretize the metric derivatives. The discretization of the Jacobian term is denoted as
where \(\delta _\xi ^n\), \(\delta _\eta ^n\) and \(\delta _\zeta ^n\) (\(n=1,2,3\)) denote the linear difference operators for \(\xi\), \(\eta\) and \(\zeta\) directions, respectively. Here the superscripts are counted from outside to inside of the brackets.
The spatial term of Eq. (38) has aÂ similar form to the Jacobian (42), and its discretized form can be expressed as
For freestream flow, U is constant, so is \(\mathcal {F}\). In that case, if the linear difference operators satisfy the condition
then it is easy to observe from Eq. (47) that
Therefore, the semidiscretized form of Eq. (38) becomes
Since static grids are considered here, the Jacobian is independent of time. Thus, we know from Eq. (50) that \(U_{j,k,l}\) is constant, indicating that the freestream condition is preserved exactly. Actually, the condition (48) also ensures that the surface conservation law (41) is maintained discretely. However, if we intend to have some geometric meanings of the Jacobian, it is better to further require that
which is the condition of the SCMM method. In this case, the discretized value \(J_{j,k,l}\) (46) represents a weighted sum of some volumes consisting of grid points in the physical space [113, 114].
5 Conclusions
In this paper, we have summarized some main algorithms of WCNS schemes and presented some related recent developments. The schemes are based on grids staggered by flux points and solution points. Thus, the spatial discretization is divided into the interpolation step and the difference step. This setup has benefit in the flexibility of choosing numerical fluxes. In addition, the nonlinear procedure is applied only to the interpolation step but not the difference step. Thus, the geometric conservation law can be preserved exactly in a discrete setting, providing that the introduced SCMM method is applied. We have also introduced the socalled conservative boundary closures for the difference step, such that the scheme is globally conservative and also time stable, with the global convergent rates as the same as the interior.
In future, some aspects of WCNS schemes are worth studying further, mainly lying in the improvement of their robustness, accuracy and resolution. To improve the robustness of the schemes for practical applications, one should address the issue of positivity preserving [115,116,117]. So far, how to preserve the positivity property and the geometric conservation law on curvilinear grids at the same time is still an open problem. Although a fifthorder WCNS scheme with unconditionally optimal convergence rate is available [65], the extension to other orders of accuracy shall be addressed. In addition, for a given grid the actual truncation error of a scheme is determined by its resolution. Thus, to improve the resolution property of WCNS schemes [118] deserves a further study as well.
Availability of data and materials
The data used in this paper are available from the corresponding author on reasonable request.
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This work was supported by the National Natural Science Foundation of China (Grant No. 11972370) and the National Key Project of China (Grant No. GJXM92579).
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Appendix A: Relation between WCNS and alternative WENO schemes
Appendix A: Relation between WCNS and alternative WENO schemes
The alternative WENO schemes [94] for the onedimensional conservation law (1) can be written as
where
If we drop the truncation error and evaluate the derivatives in the above equation by the following central difference schemes,
then we have
In this case, the spatial discretization term \((\hat{f}_{j+1/2}\hat{f}_{j1/2})/h\) in Eq. (52) is equal to that of the WCNS scheme (4) with the difference scheme
which is exactly the hybrid sixthorder difference scheme (23) with \(\alpha =1\).
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Chen, Y., Deng, X. WCNS schemes and some recent developments. Adv. Aerodyn. 6, 2 (2024). https://doi.org/10.1186/s4277402300165x
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DOI: https://doi.org/10.1186/s4277402300165x