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What is the closure problem in turbulence? 


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The closure problem in turbulence refers to the challenge of dealing with the hierarchical nature of the equations that describe turbulent systems. Both moment and kinetic approaches to turbulence formulation involve equations that have unclosed terms of higher order, which creates the need for closure. Various methods have been developed to address this problem, including theoretical physics methods such as the direct-interaction approximation (DIA) and self-consistent-field theory . Another approach is data-driven modeling, which uses nonlinear models to approximate turbulent fluctuations as state-dependent stochastic forcing . Deep recurrent neural networks have also been used to develop closure models that accurately reproduce the statistical properties of turbulence . The development of closure models is an ongoing theoretical challenge with significant practical implications .

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The closure problem in turbulence refers to the challenge of accurately modeling the influence of unresolved scales on the coarse-grained equations, leading to the need for closure models.
The closure problem in turbulence refers to the challenge of determining the values of higher-order statistical quantities based on lower-order statistical quantities, as these equations involve unclosed terms of higher order.
The closure problem in turbulence refers to the challenge of accurately predicting the statistical behavior of turbulent flows using mathematical models.
The closure problem in turbulence refers to the challenge of developing models that accurately represent the influence of small non-resolved scales on the dynamics of large resolved scales.

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