Maximum entropy modelling and Bayesian inference in turbulent fluid mechanics.

以速度和密度等波动特性为特征的流体湍流，由于难以计算湍流产生的雷诺应力，仍然是科学上未解决的重大问题之一。该项目将带来一种新的技术，即Jaynes的最大熵法，来应对这一挑战，以制定和关闭湍流的理论和降阶数值模型。将审查对人类社会具有重要意义的几个具有良好特征的案例研究流程。湍流模型也将由最大熵和贝叶斯方法直接从实验数据中构建。这个项目将大大提高我们预测湍流行为的能力。

Fluid turbulence, characterised by fluctuating properties such as velocity and density, remains one of the great unsolved problems of science, due to the difficulty of calculating the Reynolds stresses created by the turbulence. This project will bring a new technique, the maximum entropy method of Jaynes, to this challenge, for the formulation and closure of theoretical and reduced-order numerical models of turbulent flows. Several well-characterised case study flows, of importance to human society, will be examined. Turbulent flow models will also be constructed by maximum-entropy and Bayesian methods directly from experimental data. The project will substantially enhance our ability to predict the behaviour of turbulent flows.