Towards DNS of Turbulent Combustion at the Exascale

Direct numerical simulation methodology and computing power have progressed to the point where it is feasible to perform DNS in representative of flow configurations encountered in practical combustors. These complex flows encompass effects of mean shear, flow recirculation, and wall boundary layers together with turbulent fluctuations which affect entrainment, mixing, ignition and combustion. Examples of recent DNS studies with complex flows relevant to gas turbine and internal combustion engines will be presented. These include turbulent premixed combustion with hydrogen/ammonia blends at elevated pressure as a drop-in zero carbon fuel replacement for natural gas in stationary gas turbines and multi-injection autoignition of n-dodecane jets at diesel conditions. These cases involve complex kinetic interactions with shear flows at elevated temperature and pressure relevant to practical energy applications, and their computational feasibility is dependent on a capable software stack, adaptive mesh refinement and a dynamic task-based programming model tailored for upcoming heterogeneous exascale machines. Prospects for on-the-fly dimension reduction of complex chemistry to reduce the exorbitant cost of large hydrocarbon chemistry evaluation in DNS will also be described as part of a holistic computational workflow including machine learning enabled by asynchronous task based programming on GPUs.