Toward High-Fidelity Aerodynamic Shape Optimization for Natural Laminar Flow

The current push for environmentally responsible aviation requires serious efforts to mitigate the escalating effects of such technology on climate change and natural resources. A clear vision for the efficiency of future transport aircraft – with specific targets for reduced fuel burn, emissions and noise – has been published in the U.S. National Aeronautics Research and Development Plan.1 As a result, manufacturers and researchers are investigating both conventional and unconventional aircraft designs to meet these targets. As part of the effort to reduce fuel burn and emissions, aerodynamicists are assessing the feasibility of natural laminar flow (NLF) as a key enabler of environmentally responsible commercial aviation. In the late nineteenth and early twentieth centuries, the breakthrough work of Reynolds and Prandtl began to shed light on the existence, theory, and experimentation of boundary-layers and laminar-turbulent transition.2 More than a century has passed, and designers have since become heavily reliant on Computational Fluid Dynamics (CFD), as well as single and multidisciplinary design optimization tools. Despite this, there remain few NLF applications in the current commercial fleet, with Honda’s recent HA-420 business jet3 and the nacelles on the recent Boeing 7874 being among the first, if not the only applications to date. Over the past few decades, the use of CFD under the assumption of fully-turbulent conditions has allowed for stunning advancements in aerodynamic design, but the conservatism leaves something to be desired. Indeed, design tools capable of incorporating and exploiting laminar-turbulent transition enable the design of aircraft with significantly reduced drag. The lack of NLF applications in the fleet points to the sparsity of available design tools for NLF; it also points to the challenges in reliably realizing extended regions of laminar flow in flight. The transition to turbulence is affected by many factors, including: Reynolds number (Re), freestream turbulence intensity