Terascale Direct Numerical Simulations of Turbulence Generated by Fractal Grids

湍流在环境、气象学和海洋学以及许多涉及流体流动的行业中都具有巨大的重要性，例如在化工、混合、汽车、航空航天和海军行业。举个例子，通过管道输送石油的成本与湍流引起的摩擦损失成正比。又如，全球海洋运输每年消耗约21亿桶石油。对湍流的理解可以导致减少壁面摩阻的流动控制方案。以每桶75美元(现在是一个非常保守的估计)计算，10%的降幅每年将节省150亿美元，更不用说由此带来的令人印象深刻的船舶排放污染物的减少。对于每年消耗约20亿桶喷气燃料的航空业，也可以做出类似的预测。在过去60年左右的时间里，在湍流中所做的努力主要是对特定流动进行临时建模，进展有限。需要了解湍流动力学，为此需要一个特殊的实验，这些湍流动力学可以分开放置，以便给我们理解它们的线索。这是最近在伦敦帝国理工学院所取得的成就，在那里，第一次在风洞中进行了由分形网格产生的湍流的实验，取得了令人印象深刻的结果。现在有必要开发这些流动的计算机模拟。这些都是非常大的模拟，特别是由于分形湍流发生器的多尺度特性，并且需要最先进的顶端并行计算。这是一项计算方面的挑战。迎接这一挑战为我们提供了一个前所未有的机会来理解湍流以及如何操纵它。

Turbulence is of enormous importance in the enviroment, meteorologyand oceanography and also in many industries where fluid flow isinvolved such as in the chemical, mixing, car, aerospace and navalindustries. Just as an example, the cost of pumping oil throughpipelines is directly proportional to the frictional losses whichturbulence causes. As another example, worldwide ocean shippingconsumes about 2.1 billion barrels of oil per year. Understandingturbulence can lead to flow control schemes for reducing skin frictiondrag. At 75 US dollars per barrel (nowadays a very conservativeestimate), 10% such reduction would save 15 billion US dollars peryear, not to mention the consequent impressive reductions ofpollutants in ship emissions. Similar projections can be made forairline industries which consume about 2 billion barrels of jet fuelper year.Over the past 60 years or so the efforts in turbulence have beenmostly in ad hoc modelling of specific flows and the progress has beenlimited. An understanding of turbulence dynamics is needed, and forthis a particular experiment is needed where these turbulence dynamicscan be set out of joint so as to give us clues for understanding them.This is what has been achieved recently at Imperial College Londonwhere the first ever experiments of turbulence generated by fractalgrids in wind tunnels have been conducted with impressive results. Itis now necessary to develop computer simulations of these flows. Theseare very large simulations, in prticular because of the multiscalenature of the fractal turbulence generators, and require state-of-theart top-end parralel computing. The challenge is computational.Meeting this challenge presents us with an unprecedented opportunityto understand turbulence and how to manipulate it.