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The simulation of technological and environmental flows is crucial for industrial development, particularly in addressing the turbulence that characterizes most of these flows. Traditionally, this challenge has been approached using deterministic equations that parametrize turbulence effects as functions of the relevant variables. However, this method can be problematic, especially when simulating reacting flows, as suitable approximations for the closure of these equations are often unavailable. An alternative approach involves constructing stochastic models that capture the random nature of turbulence. These models offer the advantage of overcoming the closure issues inherent in deterministic methods, relying on relatively simple and physically consistent frameworks. Consequently, stochastic methods appear to be the optimal solution for many challenges related to industrial flow simulations. Nevertheless, implementing these methods is not straightforward. A significant concern is the numerical solution of stochastic equations for flows relevant to environmental and technological applications. When calculating industrial flows, it is often necessary to consider a grid with approximately 100 cells, adding complexity to the simulation process.
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Statistical mechanics of turbulent flows, Stefan Heinz
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- Année de publication
- 2003
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