Acceleration of turbulent combustion DNS via principal component transport

We investigate the implementation of principal component (PC) transport to accelerate the direct numer-ical simulation (DNS) of turbulent combustion flows. The acceleration is achieved using the transport of PCs and the tabulation of the closure terms in the PC-transport equations using machine learning. Further acceleration is achieved by a treatment for bottlenecks associated with the acoustic time steps for low Mach number flows. The approach is implemented in 2D and 3D on a laboratory scale lean premixed methane-air flame stabilized on a slot burner. DNS based on the transport of thermochemical scalars (species and energy) is also carried out, first to develop a 2D DNS database for PC-transport equations' closure terms and, second, to validate the approach against species DNS in 2D and 3D, a principal goal of the present effort. The result s show that surrogate PC DNS can reproduce instantaneous profiles as well as statistics associated with turbulence, flame topology properties and measures of flame-turbulence interactions. The study also demonstrates that parametric simulations with surrogate PC DNS can be im-plemented at a fraction of the cost of a full 3D DNS with species and energy transport.& COPY; 2023 Published by Elsevier Inc. on behalf of The Combustion Institute.