The transfer of boundary conditions on an orthogonal hexahedral mesh

In the simulation of physical processes and phenomena overall there is a problem of numerical solutions of differential problems in partial derivatives. One of the methods for numerical solutions of mathematical physics equations is the approach, based on the finite difference approximation. However, the major drawback of this method is the need to use orthogonal hexahedral mesh. While solving problems in practice, sometimes a complex geometric configuration of the computational domain (for example, see Figure 1) is used, and therefore, the drawback, mentioned above, is enough critical.

Picture 1 – The example of a complex surface as a part of the computational domain

Due to the aforesaid, there is quite a natural problem of the geometrical configuration approximation of computational domain by cell faces of the given orthogonal hexahedral mesh.

Let us turn to a more detailed problem statement. Let the computational mesh in 3D space be orthogonal and hexahedral. Namely, let be a set of mesh divisions along axis arranged in ascending order, similar to it let us introduce the ordered sets of mesh divisions along and respectively. According to designations, the following set of points is the set nodes of computational mesh . Geometric configuration that requires approximation by mesh faces, is defined by triangulated surface. Let be a set of triangles. This set is a part of surface triangulation, and its quantity is .With the numerical solution of mathematical physics problem, besides geometric approximation of surface by faces of mesh cells there is a problem of adequate transfer of triangulated surface area on cells faces, involved in its approximation. Thus, by means of set of triangles it is necessary to determine the set of faces of mesh cells, that approximate the triangulated surface, and match the transferred area with each of such face.

Let us give the algorithm, which solves the set above problem

1) Let us consider the mesh, which is dual to the initial one, i.e. such a mesh the nodes of which are cells centers of the initial computational mesh. Let us store a 3D array of real numbers, elements of which correspond to the cells of dual mesh. First of all we initialize elements of array by zeros.

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Alternate directions implicit scheme and the intermediate boundary conditions. Third type boundary conditions.

This second Note is dedicated to the discussion of the case of 3-rd type boundary conditions posed on the edges of the modeling region and will present an outline of the algorithm for the account of both the Dirichlet and 3-rd type boundary conditions on different edges.

Before passing to the discussion of that scheme, a few words should be said about another ADI scheme – namely 2D Peaceman – Rachford finite difference scheme. The correct account of the intermediate boundary conditions for both Dirichlet and 3-rd order types has been thoroughly discussed in [1]. One essential difference between the 3D Douglas – Rachford and 2D Peaceman – Rachford schemes is that in the latter scheme the spatial coordinates enter symmetrically, such that the second equation (in 2D Peaceman – Rachford) contains finite difference representations of both spatial derivatives. This fact leads to a cumbersome infer of relation between the values of the unknown function on different edges – for details see [1].

Surprisingly, although the Douglas – Rachford scheme is designed for a 3D spatial region, it is easier to treat the 3-rd order boundary conditions for it correctly due to the “non-symmetrical” entrance of the spatial coordinates in three equations – see Eq. (1) – (3):

, (1)
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Finite-difference approximation of the boundary conditions of the second and third order for the nonlinear heat conduction equation

Let us consider non-linear heat conduction equation

, (1)

, (2)

with the initial condition , and boundary conditions
, (3)

At . If , condition (3) is the boundary condition of the second order, but if , it is the boundary condition of the third order.

Let us introduce analytical grids in space and time:, , , .

Then, define grid functions , , , , , , , .

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