A Residual-Based Fuzzy Logic Algorithm for Control of Convergence in a Computational Fluid Dynamic Simulation

Ryoo, Juntaek; Dragojlovic, Zoran

doi:10.1115/1.2826059

Cited by 6 publications

(1 citation statement)

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“…For example, fuzzy mathematics has been developed as a new branch of mathematics in the last 20 years. It is extensively applied in many fields of science and technology such as the control of convergence in CFD simulations (Ryoo et al , 1999; Dragojlovic et al , 2001). Later, this method was improved (Liu et al , 2002).…”

Section: Introductionmentioning

confidence: 99%

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

Cao

Tao

2007

Engineering Computations

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PurposeThis paper aims to accelerate the iteration convergence for elliptic fluid flow problems, so that an under‐relaxation factor control method is developed.Design/methodology/approachThere 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)βγ and α=(α0)(1/β)γ) are proposed to adjust the values of under‐relaxation factors for every n iterations.FindingsFrom 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.Research limitations/implicationsWhen 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.Originality/valueThis method is helpful for the acceleration of iteration convergence in simple problems, and is a preparation for the advanced research in complicated problems.

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Section: Introductionmentioning

confidence: 99%