Examples of using Computational domain in English and their translations into Danish
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Computer
Discretization of the computational domain.
Let the computational domain be a parallelepiped, and the computational mesh of nodes set.
Tag Archives: discretization of 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.
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.
Zero heat flux is specified as a boundary condition at the boundaries of the computational domain.
The computational domain is represented by a parallelepiped with the spatial mesh, and the time mesh.
In this paper,we focus on modification of the scheme to account for convection in the computational domain.
Since the computational domain is arbitrary, the heat equation is solved numerically by using finite-difference methods FDM.
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 boundary is the boundary between a material(ground) and the environment as well as the boundary of the computational domain.
Due to the arbitrariness of the computational domain, where equation(1) is set, there is no analytical solution for this equation.
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.
When properly used,adaptive partitioning of the computational domain is a powerful tool in numerical computations to increase accuracy.
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.
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.
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.
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 meshin this area only, instead of refining the mesh throughout the computational domain.
In this article,we describe the theoretical advantages and disadvantages of using adaptive partitioning of the computational domain, and also give two examples for numerical computations of thermal fields in ground.
Areas with significant temperature gradients(near heat insulators, heat sources, cooling devices, etc.) require increased computational mesh density,consequently significantly increasing the total amount of nodes in the computational domain.