Exascale computing and data science provide a unique opportunity for direct numerical simulation (DNS) of turbulent combustion with ammonia/hydrogen blends to investigate pressure effects on the combustion rate and NOx and N2O emissions in rich-quench-lean staged configurations. DNS of lean turbulent premixed hydrogen-air flames have also provided fundamental understanding of turbulence-chemistry interactions coupled with thermo-diffusive effects. Combined with experiments, the DNS data provide a new turbulent burning rate scaling across a broad range of aero-thermo-chemical conditions accounting for both thermo-diffusive and turbulence effects. To accelerate DNS of turbulent combustion with detailed chemistry, reduced-order surrogate models (ROMS) for chemical species dimension reduction on-the-fly will be described. In particular, significant acceleration is demonstrated with scalable rank adaptive time-dependent bases with CUR decomposition.
Jacqueline H. Chen,
Sandia National Laboratories
Jacqueline H. Chen is a senior scientist at the Combustion Research Facility at Sandia National Laboratories. She has contributed broadly to research in turbulent combustion elucidating ‘turbulence-chemistry’ interactions in combustion through direct numerical simulations. To achieve scalable performance of DNS on heterogeneous computer architectures, she led an interdisciplinary team of computer scientists, applied mathematicians and computational scientists to develop an exascale direct numerical simulation capability for turbulent reactive flows with complex chemistry and multi-physics. She has also contributed to reduced order modeling to accelerate DNS with complex chemistry. She is a member of the United States National Academy of Engineering and a Fellow of the Combustion Institute and the American Physical Society. She is an Associate Fellow of the AIAA.