Examples of using Computational domain in English and their translations into Finnish
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Tag Archives: discretization of the computational domain.
The computational domain is represented by a parallelepiped with the spatial mesh, and the time mesh.
There are often relatively small elements in the computational domain;
Since the computational domain of equation(1) is arbitrary, numerical methods are used to solve it.
Picture 1- The example of a complex surface as a part of the computational domain.
Let the computational domain be a parallelepiped, and the computational mesh of nodes set.
Zero heat flux is specified as a boundary condition at the boundaries of the computational domain.
Since the computational domain of equation(1) is arbitrary, numerical methods are used to solve it.
There were four pairs of calculations with different levels of computational domain discretization.
The computational domain contains of four parallelepipeds and a particularity in the form of an asterisk in the center.
The initial temperature of the material(which occupies the computational domain) is equal to -1.0 °C.
Due to the arbitrariness of the computational domain, where equation(1) is set, there is no analytical solution for this equation.
The boundary is the boundary between a material(ground) and the environment as well as the boundary of the computational domain.
When properly used, adaptive partitioning of the computational domain is a powerful tool in numerical computations to increase accuracy.
Model of a kilometer-length pipeline with a qualitative discretization of the computational domain elements.
The computational domain is filled with material, whose volumetric heat capacity in the thawed and frozen states is equal to.
The mesh step along each coordinate axis is 1.0 m. Consequently, the computational domain contains 78,141 nodes.
When applying adaptive partitioning of the computational domain, strong reduction of the spatial step along any direction in the vicinity of a single node should be avoided.
The computation of extensive regions and long ormassive objects often involves many elements for discretization in the computational domain.
The computational time depending on the number of nodes in the computational domain is given in Table 3 and Figure 3.
When considering the problems of ground freezing and thawing, it is often necessary to take the presence of ground thermal stabilization devices(thermosyphons)into account in 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.
Answer: Even if we divide the computational domain into two parts, it is impossible to set an adequate boundary condition on the obtained borders because the thermal field from the first part influences the thermal field of the second.
Note: that this article does not analyze the accuracy of the calculations andthe dependence of accuracy of the obtained solution on the level of computational domain discretization.
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.
The latest versions of shaders(special programs performed on video cards) were utilized as well as a powerful new preprocessing engine for the computational domain and data visualization.
Summing up the advantages anddisadvantages of applying adaptive partitioning of the computational domain, we note that the application of this option makes sense when the domain contains elements whose geometric features are much smaller than the dimensions of the computational domain.
The latest versions of shaders(special programs performed on video cards) were utilized as well as a powerful new preprocessing engine for the computational domain and data visualization.
This entry was posted in Frost 3D Universal and tagged cooling devices,discretization of the computational domain, finite-element analysis, heat insulation, heat insulators, large computational meshes, long section of pipeline, non-uniform cell size, parallelization of algorithms on GPU, thermal analysis.
It is also worth mentioning that if the user wants to achieve a more accurate solution on a small area, it makes sense to perform the refinement of the mesh in this area only,instead of refining the mesh throughout the computational domain.