Fuzzy systems as a fusion framework for describing nonlinear flow in porous media

A. Nazemi, M. Akbarzadeh-T., S. Hosseini
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Abstract

By increasing the velocity of flow in coarse grain materials, local turbulences are often imposed to the flow. As a result, the flow regime through rockfill structures deviates from linear Darcy law; and nonlinear or non-Darcy flow equations will be applicable. Even though the structures of these nonlinear equations have some physical justifications, they still need empirical studies to estimate parameters of these equations. Hence there is a great deal of uncertainty as an inherent part of the estimation process. In this paper we investigate fuzzy systems paradigm to combine three of the most commonly validated and utilized empirical solutions in the current literature. In this way, the results of the three empirical equations serve as inputs, and the combination framework serve as fusion algorithm. The results show that when learning injected to fuzzy logic based models, the system provides a powerful solution with a strong ability to track reality. Specifically, this paper concludes that ANFIS provide accurate combination framework with greatest performance among the considered conventional alternatives as well as Mamdani structures.
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模糊系统作为描述多孔介质非线性流动的融合框架
通过增加粗粒物料的流动速度,通常会对流动施加局部湍流。结果表明,堆石料结构的流态偏离了线性达西定律;以及非线性或非达西流动方程。尽管这些非线性方程的结构有一定的物理依据,但它们仍然需要实证研究来估计这些方程的参数。因此,作为评估过程的固有部分,存在大量的不确定性。在本文中,我们研究模糊系统范式,以结合当前文献中最常用的验证和利用的经验解决方案。这样,三个经验方程的结果作为输入,组合框架作为融合算法。结果表明,将学习注入到基于模糊逻辑的模型中,该系统提供了一个强大的解决方案,具有较强的现实跟踪能力。具体而言,本文得出的结论是,在考虑的传统替代方案和Mamdani结构中,ANFIS提供了具有最佳性能的精确组合框架。
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