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An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
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An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
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An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation

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An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation
Journal Article

An under‐relaxation factor control method for accelerating the iteration convergence of flow field simulation

2007
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Overview
This paper aims to accelerate the iteration convergence for elliptic fluid flow problems, so that an under-relaxation factor control method is developed. There should be an optimal under-relaxation factor that can result in the equivalence of the global residual norms of momentum equation u and momentum equation v. The two residual norms of the momentum equations will be equivalent through controlling the velocity under-relaxation factors, and then the iteration convergence can be accelerated. Two expressions (α=(α0)ßγ and α=(α0)(1/ß )γ ) are proposed to adjust the values of under-relaxation factors for every n iterations. From the five preliminary computations it is found that the value of γ can be larger than 1 and of n can be less than 5 for an open system, and the value of γ should be less than 1 and that of n should be larger than 10 for a closed system. These two pairs of parameters are then used in another five examples. It is found that the saving in CPU times is at least 43.9 percent for the closed system and 67.5 percent for the open system. When the Re or Ra of the two-dimensional problems are low, this control method is feasible. More research work is needed in order to apply it in three-dimensional or high Re or Ra problems. This method is helpful for the acceleration of iteration convergence in simple problems, and is a preparation for the advanced research in complicated problems.