Àëãîðèòìû ðåøåíèÿ ïàðàáîëè÷åñêèõ óðàâíåíèé íà êðèâîëèíåéíûõ ñåòêàõ
( Algorithms of Solution of Parabolic Equations on Curvilinear Grids
Preprint, Inst. Appl. Math., the Russian Academy of Science)

Çàñëàâñêèé Ì.Þ.
(M.Yu.Zaslavsky)

ÈÏÌ èì. Ì.Â.Êåëäûøà ÐÀÍ

Ìîñêâà, 2003

Àííîòàöèÿ

Ðàññìîòðåíû ðàçëè÷íûå ÷èñëåííûå ìåòîäû äëÿ äâóìåðíûõ êðàåâûõ çàäà÷ äëÿ ïàðàáîëè÷åñêèõ óðàâíåíèé. Ïðåäïîëàãàåòñÿ, ÷òî êîýôôèöèåíòû óðàâíåíèé ðàçðûâíû è ëèíèè ðàçðûâîâ íå ñîâïàäàþò ñ êîîðäèíàòíûìè. Ýòî ïðèâîäèò ê íåîáõîäèìîñòè èñïîëüçîâàíèÿ íåîðòîãîíàëüíûõ ñåòîê. Ðàññìîòðåíû ïîëíîñòüþ íåÿâíàÿ, ðåãóëÿðèçîâàííàÿ è àääèòèâíûå ñõåìû. Ñïåöèàëüíûé ìåòîä ðåãóëÿðèçàöèè, ó÷èòûâàþùèé ðàçðûâû â êîýôôèöèåíòàõ, ïîçâîëÿåò ïîñòðîèòü ñõåìû áîëåå, ÷åì ïåðâîãî ïîðÿäêà àïïðîêñèìàöèè ïî âðåìåíè, êîòîðûå ëåãêî ðàñïàðàëëåëèâàþòñÿ.

Abstract

The different computational methods for 2D parabolic boundary problems have been considered. It is assumed the coefficients of the equations are discontinuous and the lines of discontinuity don’t coincide with coordinate ones. It results in the necessity of using the non-orthogonal grids. The fully implicit, additive and regularized schemes have been developed. The specific method of regularization taking into account discontinuity of coefficient allows constructing the schemes more than first order of time approximation, which are easily parallelized.

 

Contents

 

1. Introduction  

2. Fully implicit scheme

and support operator method

3. Regularized scheme  

4. Finite difference flux method

5. Variational difference flux method

6. Variational difference

locally one-dimensional method  

7. Results of calculations

8. Conclusions

Reference


 

Introduction

 

Now there are many difference schemes for the heat conductivity parabolic equations with discontinuous coefficients, if the surfaces and lines of discontinuity being not coincident with coordinate ones. The discontinuity of coefficients in a heat conduction equation means that normal (to a discontinuity surface) derivatives are discontinuous. In this case, attempts of approximating the equations by means of the difference schemes without the taking into account the position of discontinuities may reduce the accuracy of approximation. For the best method of describing the phenomena it is expedient to use grids adapted to the media structure. Besides the schemes should satisfy the requirements of stability, monotonicity and conservativity. At the same time because of the usage of multiprocessing systems, it needs to provide the possibility of effective parallelezation of the difference schemes. But the explicit schemes, most simply parallelized, are not considered because of hard limitation of a time-step for schemes stability.

 In the present work some methods of solution of the posed problem for the 2D equation are considered

,                                        (1.1)

where

,                                   (1.2)

in domain . It is supposed that the coefficient  is a piecewise continuous function. Boundary conditions may be general. The examined examples correspond to zero boundary conditions of the second type

,                                               (1.3)

where  is the boundary of domain. Further, for simplicity we shall consider square domain .

The cells of examined grids have a form of tetragons, though it should be noticed, that the proposed schemes might be generalized easy for grids containing triangles. The well-known support operator method has been used for a spatial approximation of the problem. The feature of this method is a definition of the divergence and gradient difference operators by using the difference analogy of the known identity:

.                    (1.4)

If the operators of the divergence and gradient are in accordance with the difference approximation of (1.4), the approximation orders of both operators are matched.

Let . The equality (1.4) allows a definition of the divergence operator if the operator of gradient (or the flux operator ) is being determined. It is the reason of the method denomination. Really, the support operator method approximates the system (1.1), (1.2) instead of the approximation of the equation  only. It is analogous to the ideas developed in the known article (Glowinski R., Wheeler M.F., 1988).

Five difference schemes were compared: fully implicit scheme on the basis of a of the support operators method (Samarskii A.A., Koldoba A.V., Poveshchenko Yu.A., Tishkin V.V., Favorskii A.P., 1996; Koldoba A.V., Poveshchenko Yu.A., Popov Yu.P., 1985), the scheme with regularizator (Samarskii A.A., 1989), two modifications for curvilinear grids of the scheme proposed by Yu.B. Radvogin, and also a variant of the locally one-dimensional scheme based on a variational-difference principle (Goloviznin V.M., Korshunov V.K., Samarskii A.A., Chudanov V.V., 1985). The results of comparison in midpoint of the process evolution and in a final are represented in the tables.

The main aim of the article is to create the effective methods of the 2D and 3D problems solution for the parabolic equations with piecewise continuous coefficients. There are many methods for rectangular grids but usually the surfaces and lines of the coefficients discontinuity don’t coincide with coordinate ones. The parabolic equations have standard forms of the balance equations connecting the time derivatives of value with the flow divergence. The evident method is fully implicit but it results in the solution of the linear system of the large order. One possibility is determine the flow components at the intermediate moments of the time and following divergent closure of the system. This idea had been realized by Radvogin Yu.B. only for rectangular grids. The problem of the mixed derivatives for nonrectangular grid had not been discussed in the article. In this work it was shown that the contravariant component of flux (DFM) or covariant components (VDFM) are sufficient to be calculated. Then using the balance equation for each cell the divergence expression may be obtained. The closed equations for the flux components may be constructed if the mixed derivatives being omitted. The flux components equations are of the order O(1). However, it is sufficient for the final approximation of the second order for rectangular grid and of the first order for non-orthogonal grid. Similar principles are used for VLODM. It is a sample of the additive scheme, i.e. there is no approximation of each stage but only total.

The method considered is a regularization method based on Samarskii idea analogous to preconditioning the algebraic linear system. The difference approximation of the equations (1.1), (1.2) may be rewritten , where , ,  and  are finite difference approximation of the operators by support operators method,  and  are positive one-dimensional operators, described below. It is essential the scheme is effective because it does not need to solve the complicated linear algebraic equations, as the elliptic operator is determined on the explicit layer. Besides, this scheme is easily parallelized.

The calculations for heat conductivity coefficients with different analytical properties have been realized for tasks on rectangular and curvilinear grids when the analytical solution being known.

 It is evident the proposed schemes may be generalized on a 3D case.

 

 

Fully implicit scheme

and support operator method

 

Now we describe the most obvious way of approximation: a fully implicit scheme and a method of operator  approximation. Let's mark, that hereinafter the temperature is considered in cell-centers and corresponding fluxes - in cell-edges. This method of discretisation allows the natural approximation of boundary conditions of Neumann type. Besides, it simplifies the construction of difference scheme near the surfaces or lines of coefficients discontinuities, since the fluxes normal to these lines are continuous (it is supposed that lines of discontinuities coincide with grid lines).

The fully implicit scheme has a form

                                                    (2.1)

where  is a value  on an implicit time-layer,  - difference approximation of the operator  by  the support operator method.

Support operators method is a version of the finite volume method. The last one is based on the known identity  for a vector . Thus it needs to know components of vector  in the same points of cell edges, but it is inconvenient, since the values of gradient different components are usually determined in different edges. It is offered to average the component values by usage of four neighbor bases (in a 2D case). Besides the integral identity (1.4) will be used instead of the standard formulation of the Gauss–Ostrogradskii theorem for calculating the divergence if the gradient vector being known. The last one allows constructing a difference scheme not on an initial grid, but on arbitrary one providing the best approximation.

The operator  was considered as the support operator. Let  and  be curvilinear coordinates, under level lines passing through cell-centers or their corresponding edges, and the distance between cell-centers for coordinates  coincides with the distance in coordinates .  Besides it is supposed, that under transformation  the domain  is mapped into unit square (see fig. 2.1). The numbers of a grid points along coordinate lines are designated with  and  accordingly. Then the covariant components of a flux  in local basis  look like

,                     (2.2)

,                     (2.3)

,                     (2.4)

                        (2.5)


 and  are equal to the parts of segment  and , lying inside a cell ,  and  are the lengths of these segments.


Fig. 2.1                                                      Fig. 2.2

 

Suppose, that the grid lines are orthogonal to the boundary of the domain (Fig. 2.1). Then we have according the boundary conditions (1.3)

                (2.6)

For approximating the second term of the left hand part of (1.4) the additional grid  has been constructed. The edges of the grid  connect the cell centers of the grid . For covering of whole area  we shall add some cells formed by segments of boundary and normals to it (see a fig. 2.2, the continuous lines bound cells of a grid , dashed - ).

Let's consider an internal cell  of grid . Its vertices are denoted with F, G, H, I. The notation of angles is represented in the fig. 2.3. Then the inner product of vectors  and  in the vicinity of vertex F has a form

       (2.7)

Similarly in vertex G:

   (2.8)

 

 

 

 

 

 

 

 

 

Fig. 2.3

 

Using (2.6), (2.7) and analogous expressions for vertices H and I the quantity of integral over the cell may be represented

. (2.9)

Here , , ,  are some non-negative values, the sum of which equals the square of FGHI. Let the vertices F, G, H, I have indexes , , ,  respectively. Then the expression (2.9) may be rewritten

                  (2.10)

For boundary cell, but not for an angular one, the sum (2.10) will include only two terms. For example, for a cell  we obtain the following according to (2.6):

         (2.11)

For angular cells there will be only one term, which equals to 0 owing to (2.6).

The integral over domain , where summation is performed over all cells of .

Let grid vector  be a difference gradient:

. It is possible to consider, that vector  component normal to boundary is equal to 0, i.e.  .

Then

,                         (2.12)

Where .

Here for

                 (2.13)

          (2.14)

Remark, the sum (2.12) does not include expressions with , that corresponds to boundary conditions (1.3).

Here  and  are length of some segments. For example, they may be the segments connecting centers of gravity of cells ,  and ,  of grid  accordingly. Then it’s natural to consider the expression

,                               (2.15)

as a difference analogue of the operator , where  are squares of some domains, associated with nodes . They may be squares of a tetragon with vertices in centers of gravity of cells , ,  and  of grid  (it is assumed that for boundary cells these vertices coincide with centers of boundary segments, and for angular - with its angle vertex). It is possible to lie  for simpler variant. In fact it means the theorem of Gauss-Ostrogradskii for this domain, and the grid functions  and  are contravariant components of a flux on cell edges of a grid .

The finite volume method was used in works of Edwards M.G. and Aavatsmark I. for investigation of single-phase and multiphase problems of underground hydrodynamics (M.G. Edwards, C.F. Rogers, 1998; Aavatsmark I., Barkve T., O. Boe, T. Mannseth, 1996). They define the divergence using the Gauss therem for one cell. The feature of the support operator method is a definition of flux  from an equality (1.4). It results to the following: the order of the divergence and gradient operators approximations is the same. This method of difference schemes construction based on reviewing of the system (1.1), (1.2) instead of the equation , that is similar to work Glowinski R., Wheeler M.F., 1988, where the same representation is used for a mixed finite element method.

 

 

The regularized scheme

 

The following type of scheme is developed as the regularized scheme:

,                                                (3.1)

where  operator is a regularizator (Samarskii A.A., 1989).

As known, for an absolute stability of the scheme it is sufficient to examine

           (3.2)

with boundary conditions

                              (3.2 ')

for the heat conductivity equation with a variable coefficient on a rectangular grid (Samarskii A.A., 1989). Here  is a unit operator,  is a max value of a heat conductivity. The obtained scheme is a scheme of the first order of approximation by time. Under drawing an analogy with rectangular grids it is possible to use the regularizator of the following form for curvilinear grids

   (3.3),

with boundary conditions

                             (3.3 ')

where  are curvilinear coordinates. Coordinate lines of the system  coincide with lines of coordinates , but the initial grid maps into uniform rectangular one in a plane  with steps  and  (see fig. 2.1),  and  are factors depending on "irregularity" of a grid and for a rectangular grid equaling 1.

However, the regularizator of the type mentioned above gives unsatisfactory results of calculations for the discontinuous coefficient of the heat conductivity, as it does not provide the necessary order of the approximation in the vicinity of the discontinuity line.

Because of this fact the following form of the regularizator  is offered:

 (3.4)

with boundary conditions (3.3 ').

Usually regularized schemes are schemes of the first order of approximation by time. The exception are the schemes on rectangular grids being the schemes of the second order of approximation, if  and operators . Therefore it is possible to expect that the schemes of the type mentioned above with regularized operators similar to main one of the problem near coefficients discontinuity lines will be by more precise, than additive schemes described below.

It is easy to find expressions for factors  and , corresponding to absolute stability of the scheme (3.1) with regularizator (3.4), for a concrete grid. Let  be a grid function, obtained on -th time step (). Under stability the following will be understood

                             (*)

Here is an inner product in the space of grid functions, defined in cells of a grid  (the summation is performed over all cells of a grid ):

                 (3.5)

as well as

                  (3.5’)

It should be noted that it needs to introduce last terms in both parts of (*). It is concerned with the fact the expressions in the (*) without terms are not a norms, but just as semi-norms. So the left part is a norm in solution space and right part is a norm in space of initial data.

Let's prove, that the satisfaction of the inequality

.                              (3.6)

is sufficient for stability of the scheme (3.1) (in sense of (*)).

Really, having multiplied both parts of (3.1) by  (in inner product ), we have:

Thus, if (3.6) is fair, then , from which (*) immediately follows.

Besides the inner product  we shall introduce

,

where the summation is performed over all cells of a grid . It should be marked, that norms induced by inner products  and  are equivalent:

Then,

,                                               (3.8)

,          (3.9)

.             (3.8)

and

                     (3.10)

Here

For approximation of  it is assigned in (1.4)  just as it was done in support operator method. Then the right part of (1.4) becomes 0 and according to the formulas (2.13), (2.14)

,                      (3.11)

where , and the summation is performed over all cells of a grid .

Thus,

,                    (3.12)

where

Since each edge appears twice in the sum (3.12) except the boundary ones, it is sufficient to suppose

                              (3.13)

                              (3.14)

for satisfaction of

Let's assume . Then both introduced inner products coincide and it is necessary to prove

, where ,

 with boundary conditions (1.3). Since both operators  are non-negative determined (with respect to inner product , which coincides with  in a considered case), all their eigenvalues , corresponding to eigenfunctions , are non-negative. Consider the case . Since all grid functions are decomposed by basis : , then

.

Thus, we have proved, if having selected regularizing factors according to the formulas (3.13) and (3.14) the scheme (3.1) will be absolutely stable. As several tests without analytical solution have shown it will be also stable for variable . In other cases the regularizator (3.3) should be used.

It should be noted, that for the considered class of problems the scheme (3.1) with  equal to squares of tetragons with vertices in center of gravity of cells , ,  and  of grids , was also absolutely stable (with some  and ). Moreover, the scheme (3.1) with regularizator of the form

    (3.15)

with boundary conditions

                            (3.15')

was absolutely stable for some  and .

Let's remark, that the scheme (3.1) with regularizator (3.4) or (3.15) is economic, since the corresponding system of linear equations may be easily inverted by two sweep methods.

 

 

Difference flux method

 

Flux method is understood as the scheme of following sort: at the first step (predictor) the fluxes on edges of cells are calculated on "a intermediate time layer using the equations for each component of a vector . Usually they are difference approximations of the equation for a flux  by some methods. The second step (corrector) is a divergent closure due to initial equation.

Let's remind the scheme proposed by Yu.B. Radvogin for a heat conductivity equation with variable coefficient on a rectangular uniform grid.

Predictor

 (4.1)

   (4.2)

Corrector

 (4.3)

Here  and  are grid steps,  and  are fluxes normal to the cell edges. If  the scheme is absolutely stable, i.e. the scheme with surpassing definition of fluxes is stable.

On a step of predictor we effectively calculate components of fluxes normal to the cell edges referred to intermediate time layer. It should be noted, that each equation of (4.1) and (4.2) approximates equation for a flux with zero order, i.e. it is supposed that for each layer of cells the flux through its lateral boundaries is equal to zero. On a step of corrector using these values we calculate values of temperature for an implicit time layer.

The natural generalizing for curvilinear grids of the scheme proposed by Yu.B. Radvogin looks like the following:

predictor

                          (4.4)

 

                          (4.5)

Here  is defined by support operators method for each layer along directions  and   under the following assumption. It is supposed that flux along the same direction in other layers and flux along other direction are equal to 0.

Corrector

                                          (4 .6)

The operator  is defined by a support operator method: using contravariant components of a flux we calculate the covariant ones by a method depicted above. The equations (4.4) and (4.5) also may be solved effectively.

 

 

Variational difference flux method

 

Let the operator  be employed to both parts of (1.1) and then outcome be multiplied by . Then due to (1.2) the equation for flux is obtained

                               (5.1)

Discretising in time with the help of the implicit scheme (), we have

                            (5.2)

Multiplying (5.2) by an arbitrary variation  and integrating over arbitrary domain  we obtain due to boundary conditions (1.3), if boundary fluxes being equal to zero:

.               (5.3)

Thus, functional

                 (5.4)

reaches its stationary value on a solution of the equations (1.1) and (1.2) with boundary conditions (1.3).

Let the curvilinear coordinates  in domain  be introduced by the same way as in the third item. For a definiteness we suppose that a Jacobian . Designating  and  number of cells along directions  and  respectively, the expressions in (5.4) may be rewritten in local contravariant base of a curvilinear coordinate system .

The orts of contravariant base look like

,                (5.5)

where  are Lame coefficients of a curvilinear coordinate system.

Since ,

where  and  are contravariant components of flux then having made substitution  we obtain

,    (5.6)

.          (5.7)

As well as in a difference flux method, we suppose that for each layer of cells the flux through its boundary is equal to zero. Let's consider the approximation of a functional (5.4), having taken into account of any layer of cells along  or  as  (see fig. 5.1).

 

For a layer  along  we have:

,    (5.8)

where

               (5.9)

 (5.10)

                    (5.11)

          (5.12)

           (5.13)

 

 


Fig. 5.1

 

Then functional  may be represented as

,                   (5.14)

where

,                                     (5.15)

.        (5.16)

The difference analogue of the equation (5.1) follows from a condition of a minimum of a functional (5.8):  or

        (5.17)

Using boundary conditions  the equation is solved by sweep method.

For a layer  along  the reasonings are similar, therefore we list only finite outcome - difference equation:

      (5.18)

and boundary conditions .

For divergent closure we use the initial equation (1.1) and formula (5.7):

.             (5.19)

 

 

The variational locally one-dimensional method

 

The developed scheme is very similar with previous one. Let's specify their differences. In a flux method using known distribution of temperature the fluxes on an intermediate time layer are calculated, and then divergent closure is performed. In the given scheme using known temperature covariant component of a flux only along one direction (for example, along ) is calculated, then the temperature on an intermediate time layer is obtained under supposition that the fluxes along  are equal to zero. Then using the new distribution of temperature on an intermediate time layer covariant component of a flux along  is calculated. Finally, the temperature on an implicit time layer is obtained under assumption that of a component of the flux along  is zero. Since the calculations coincide with one described above we represent only final formulas – the difference equations:

        (6.1)

   (6.2)

 

 

      (6.3)

    (6.4)

 

 

 

Calculation results

 

All five algorithms were tested on a rectangular grid, scalene grid (see fig. 7.1) and sine grid (see fig. 7.2). The square  was divided into 10õ10, 20õ20 and 40õ40 of cells. The exact solutions were the following

1.  ,

2.  ,

3.  ,

4.  , ,

where  is obtained from the equation

                    (7.1)

Besides, the problem with sources have been tested too. Instead of (1.1) the following equation have been considered  .  At the same time the regularized and fully implicit schemes have been developed. These schemes were also tested on solution

5.


 

Fig. 7.1                                                    Fig. 7.2

 

 

 

 

The middle of calculation

Final moment

Rectang.

Scalene

Sine

Rectang.

Scalene

Sine

10

Implicit

0.002543

0.005791

0.017498

0.004267

0.004786

0.005831

Regul.

0.001028

0.005610

0.018306

0.001701

0.002891

0.004672

DFM

0.003288

0.009470

0.044702

0.005555

0.006121

0.007731

VDFM

0.003288

0.006604

0.015847

0.005555

0.005988

0.006746

VLODM

0.003288

0.006745

0.017656

0.005555

0.006006

0.006412

20

Implicit

0.001802

0.002757

0.003224

0.003002

0.003170

0.002974

Regul.

0.000255

0.002479

0.002564

0.000419

0.001269

0.001628

DFM

0.002562

0.014380

0.068315

0.004299

0.004519

0.008980

VDFM

0.002562

0.003858

0.009687

0.004299

0.004412

0.004330

VLODM

0.002562

0.003945

0.010538

0.004299

0.004419

0.004205

40

Implicit

0.001614

0.001661

0.001674

0.002684

0.002732

0.002675

Regul.

5.910e-5

0.001393

0.001048

9.692e-5

0.001078

0.001036

DFM

0.002378

0.037927

0.043497

0.003983

0.005954

0.006813

VDFM

0.002378

0.003501

0.003585

0.003983

0.003988

0.003924

VLODM

0.002378

0.003427

0.003743

0.003983

0.003990

0.003912


Table 7.1

 

 

The middle of calculation

Final moment

Rectang.

Scalene

Sine

Rectang.

Scalene

Sine

10

Implicit

0.060256

0.084513

0.052579

6.954å-9

0.003246

7.405å-4

Regul.

0.035828

0.066245

0.034633

1.694e-9

0.004266

0.001353

DFM

0.076859

0.099951

0.093450

1.642å-8

0.003478

7.715å-4

VDFM

0.076859

0.100001

0.064092

1.642å-8

0.003300

0.001186

VLODM

0.076859

0.100644

0.062796

1.642å-8

0.003302

0.001289

20

Implicit

0.042323

0.049574

0.039917

2.493å-9

7.776å-4

9.130å-5

Regul.

0.016587

0.024491

0.021972

4.006e-10

0.001244

4.014å-4

DFM

0.059831

0.069960

0.087101

6.660å-9

9.922å-4

1.112å-4

VDFM

0.059831

0.066459

0.058264

6.660å-9

8.126å-4

6.367å-4

VLODM

0.059831

0.066603

0.058629

6.660å-9

8.135å-4

6.438å-4

40

Implicit

0.037857

0.039757

0.037575

1.895å-9

1.930å-4

4.612å-6

Regul.

0.011800

0.015915

0.017438

2.436e-10

6.094å-4

1.101å-4

DFM

0.055590

0.062290

0.072428

5.273å-9

4.033å-4

5.492å-6

VDFM

0.055590

0.057125

0.055641

5.273å-9

2.220å-4

1.999å-4

VLODM

0.055590

0.057186

0.055720

5.273å-9

2.223å-4

2.004å-4


Table 7.2

 

 

The middle of calculation

Final moment

Rectang.

Scalene

Sine

Rectang.

Scalene

Sine

10

Implicit

0.058951

0.080214

0.038918

9.32å-10

0.002992

2.058å-4

Regul.

0.033464

0.060647

0.042225

1.762e-10

0.004628

2.669å-5

DFM

0.058421

0.077163

0.055781

9.03å-10

0.003042

1.950å-4

VDFM

0.058421

0.079921

0.045288

9.03å-10

0.003015

2.455å-4

VLODM

0.066577

0.087797

0.048211

1.468å-9

0.003015

2.640å-4

20

Implicit

0.043829

0.050063

0.040376

3.47å-10

7.128å-4

1.048å-5

Regul.

0.017012

0.024025

0.020200

4.493e-11

0.001601

3.104å-5

DFM

0.043922

0.051174

0.065077

3.49å-10

7.568å-4

2.731å-5

VDFM

0.043922

0.050462

0.045016

3.49å-10

7.251å-4

3.991å-5

VLODM

0.052266

0.058096

0.050214

5.93å-10

7.254å-4

4.490å-5

40

Implicit

0.040019

0.041671

0.039675

2.68å-10

1.760å-4

4.102å-7

Regul.

0.012873

0.016171

0.015776

2.893e-11

8.474å-4

7.318å-6

DFM

0.040273

0.048669

0.055690

2.72å-10

2.191å-4

6.596å-6

VDFM

0.040273

0.042710

0.042085

2.72å-10

1.856å-4

9.758å-6

VLODM

0.048662

0.050290

0.050019

4.69å-10

1.864å-4

1.131å-5


Table 7.3

 

 

The middle of calculation

Final moment

Rectang.

Scalene

Sine

Rectang.

Scalene

Sine

10

Implicit

0.029916

0.139758

0.111295

0.068440

0.132269

0.068473

Regul.

0.027471

0.143325

0.117483

0.062569

0.126339

0.071540

DFM

0.031644

0.139261

0.118225

0.072636

0.136601

0.066644

VDFM

0.031644

0.143370

0.119056

0.072636

0.137619

0.070704

VLODM

0.031644

0.144451

0.117742

0.072636

0.137898

0.071240

20

Implicit

0.010815

0.152431

0.024321

0.022945

0.056930

0.016478

Regul.

0.008049

0.153958

0.021091

0.017029

0.051391

0.012137

DFM

0.012768

0.147452

0.068678

0.027176

0.060852

0.021627

VDFM

0.012768

0.155467

0.025705

0.027176

0.061600

0.021214

VLODM

0.012768

0.157788

0.025298

0.027176

0.061783

0.021195

40

Implicit

0.005784

0.097919

0.006320

0.012025

0.028871

0.011572

Regul.

0.002941

0.096378

0.003688

0.006122

0.023593

0.006318

DFM

0.007790

0.092611

0.042937

0.016247

0.032853

0.017442

VDFM

0.007790

0.098255

0.008891

0.016247

0.033321

0.015941

VLODM

0.007790

0.100245

0.008740

0.016247

0.033407

0.015942


Table 7.4

 

 

The middle of calculation

Final moment

Rectang.

Scalene

Sine

Rectang.

Scalene

Sine

10

Implicit

8.242å-5

8.480å-5

6.975å-4

0.010368

0.010438

0.014873

Regul.

2.162e-5

2.398e-5

4.494e-5

3.519å-4

3.905å-4

0.001466

20

Implicit

2.250å-5

2.959å-5

8.245å-5

0.002562

0.002585

0.002981

Regul.

2.452å-5

2.536e-5

2.656e-5

9.644e-5

1.422å-4

2.441å-4

40

Implicit

4.942å-6

9.133å-6

6.943å-6

6.071å-4

6.142å-4

6.127å-4

Regul.

2.552e-5

2.574e-5

2.532e-5

6.182e-5

7.687e-5

7.351e-5


Table 7.5

 

The results of calculations are represented in tables 7.1…7.5 according to number of the test (1…5). Final time for tests 1…4 was 0.25, for the test 5 was . Numbers of steps by time are 100 and 600 respectively. Factors  and  are supposed to be equal to 1.5 in the scheme with regularizator (3.15).

 

 

Conclusions

 

The computer simulation of the different boundary and initial problem demonstrates some features of the methods developed. All additive and almost additive schemes DFM, VDFM, VLODM have the same accuracy and CPU times. The fully implicit scheme accuracy is better than for additive scheme but CPU time is essentially more and there is a serious problem of parallelelizing this scheme. The best scheme is a regularized one. The error of the approximation and CPU time are less than for other methods except the case of the large values of function decrements. Besides the order of the time approximation is more than the first as it has been discussed above.

If the spatial part of the function is  and the decrement is  the asymptotic stability of the scheme is not satisfied. Really at the end of evolution the absolute error of the solution is 1.694e-9 for rectangular grid, 0.00426 for scalene grid and 0.00135 for sinusoidal one, if the step is about of 1/10. For N=20, 40 correspondingly the values of errors are 0.00124, 6.094e-4 for scalene grid. As for other methods the error were less. It may be explained by the fact that regularization operators are not strictly agreed with the approximation of the elliptic operator by the support operator method.

 

 

 

Author expresses thank to Pergament A.Kh. for proposed topic of investigation and invaluable assistance during article preparation.

 

 

Reference

 

1.      Samarskii A.A. The theory of difference schemes. Moscow, “Nauka”, 1989 (in Russian).

2.     Samarskii A.A, Koldoba A.V., Poveshchenko Yu.A., Tishkin V.V., Favorskii A.P. Difference schemes on irregular grids. Minsk, 1996. (in Russian)

3.     Goloviznin V.M., Korshunov V.K., Samarskii A.A., Chudanov V.V. The method of factorized heat displacements for solution of 2D problems of heat conductivity on irregular grids. Preprint of KIAM, N58, 1985 (in Russian).

4.     Glowinski R., Wheeler M.F. Domain decomposition and mixed finite element methods for elliptic problems. -  First International Symposium on Domain Decomposition Methods for Partial Differential Equations, Philadelphia, 1988, SIAM, pp.144-171

5.     Edwards M.G., Rogers C.F. Finite volume discretisation with imposed flux continuity for the general tensor pressure equation. Computational geosciences, vol 2, 1998, pp 259-290

6.      Aavatsmark I., Barkve T., O. Boe, T. Mannseth. Discretisation on non-orthogonal, quadrilateral grids for inhomogeneous anisotropic media. Journal of computational physics, 127, 1996, pp 2-14