Towards Computationally-efficient and Accurate Particle PDF Simulations of Turbulent Combustion Using Pre-partitioned Adaptive Chemistry

Book excerpt: There is a time critical need for design of fossil fuel based energy conversion devices that attain the dual and usually competing objectives of high efficiency and low pollutant emissions. The design of such devices can be informed by, and in certain instances derived from predictive computations. A crucial component of reacting flow simulations that are predictive is the turbulent combustion model. Probability density function (PDF) methods have been shown to accurately capture flames with strong turbulence chemistry interactions. However, PDF methods are known to be more computationally intensive than simpler topology based approaches such as steady laminar flamelet models. The recently proposed pre-partitioned adaptive chemistry (PPAC) methodology mitigates the cost of using particle PDF methods while maintaining their accuracy. PPAC generates a set of reduced models in an offline preprocessing stage, which are then dynamically utilized at runtime for integrating particle compositions. In the first part of this work, PPAC is augmented by combining it with complementary dimension reduction (rate-controlled constrained equilibrium (RCCE)) and storage retrieval methods (in-situ adaptive tabulation (ISAT)). The combined PPAC-RCCE-ISAT method is shown to outperform standalone PPAC by avoiding redundant direct integrations leading to a significant reduction in the CPU cost, and achieving a sizable reduction in the memory requirement by retaining fewer variables at runtime. Though PPAC has been developed for reducing the computational cost of particle PDF computations, it had previously been tested only in a partially stirred reactor (PaSR). Consequently, an integrated PPAC (-ISAT) particle PDF solver is developed as part of the current work. A detailed assessment of PPAC and PPAC-ISAT in LES/PDF simulations of turbulent combustion is completed using the developed solver. For a large-scale simulation of Sandia flame D, the coupled PPAC-ISAT particle PDF solver is shown to reduce the average wall clock time of a standalone ISAT implementation using the detailed mechanism by 39%, with a minimal loss of accuracy. A key assumption made in the PPAC framework is that the compositions used in the offline preprocessing stage are representative of those encountered at runtime. Hence, the efficient generation of a representative database is crucial to the success of PPAC. The suitability of existing canonical 0D-1D reactors is examined for this purpose. Specifically, compositions obtained from these canonical reactors are compared to the compositions extracted from a variety of direct numerical simulations using an ISAT based approach. We show that the compositions obtained from 1D counterflow flames and PaSR are representative of a significant fraction of the compositions encountered in turbulent combustion simulations. To directly quantify the impact of using databases generated from canonical 0D-1D reactors, we use the coupled PPAC-ISAT particle PDF solver for performing LES/PDF simulations of Sandia flame D. We explore two databases: a first one generated using compositions extracted from 1D counterflow flames, and a second one using compositions from a PaSR. We show that the use of these efficiently generated databases leads to results that are comparable to the case where the database is comprised of compositions extracted from the LES/PDF simulation itself. Finally, avenues for further research that can significantly improve the utility of PPAC for enabling computationally-efficient and accurate particle PDF computations are identified.