Introduction

Slotnick et al. (2014) note that in 2025 air transport will contribute 1.5 billion tonnes of CO2 emissions annually. The aerospace industry has largely given rise to the inception of computational fluid dynamics and much of its subsequent development. It seems likely, that with modern CFD developments, it will play a paramount role in continuing to help alleviate the environmental impact of aircraft. In aerospace, CFD originally would focus on studying basic airfoils. However, nowadays it has gone well beyond this. To meet the modern multi-objective, multi-scale, coupled industrial requirements, CFD has become a highly multi-disciplinary subject area. It is hoped that this aspect has come across in the preceding text.

Figure 8.1 shows the growth of computers. The dotted line shows the growth with year of the number one fastest computer. The full line gives the 500th fastest. The dashed line gives the growth in the use of LES in an applied, industrial turbomachinery journal – the ASME Journal of Turbomachinery. There is a clear trend in the growth in the use of eddy-resolving simulations with increased computing power. Clearly the industrial use of eddy-resolving simulations will lag this more academic use. However, as noted by Lele and Nichols (2014), for non-wall bounded flows, eddy-resolving simulations could be used in industry in the next five to ten years. Indeed there is some current use for specific circumstances. Also, notably, Morton et al. (2007) performed eddy-resolving simulations for F/A–18 fighter configuration. Tail buffet compared well with real flight spectral data.

In this chapter, it is explored how CFD will look in the next decade and beyond. Much of these ideas are based on the contributions to the Royal Society Theme issue of Tucker and DeBonis (2014).

Computer Science and Computers

As can be seen from Figure 8.1, there is healthy growth in computing power. As noted by Jameson (2008), in the past twenty-five years, computers have become a million times faster. However, algorithmic improvements are needed that are customized for high-performance computers. It is quite power intensive to move data around in memory.