A combined PPAC-RCCE-ISAT methodology for efficient implementation of combustion chemistry
Abstract
Probability density function (PDF) methods are now well established and can be used to accurately simulate flames with strong turbulence chemistry interactions. A pre-partitioned adaptive chemistry (PPAC) methodology (Liang et al., Combustion and Flame, 2015) has been proposed recently for the efficient implementation of combustion chemistry in particle PDF methods. PPAC generates a library of reduced kinetic models in an offline preprocessing stage. At runtime, PDF particles are dynamically assigned one reduced model and its corresponding reduced representation, leading to a significant decrease in both storage requirements and CPU time required for the integration of chemical source terms. In this work, we augment PPAC by combining it with storage retrieval and dimension reduction techniques. Specifically, this work combines PPAC with in-situ adaptive tabulation (ISAT) and rate-constrained chemical equilibrium (RCCE). Implementations for PPAC-ISAT, PPAC-RCCE, and PPAC-RCCE-ISAT are described and their performance is examined for a partially stirred reactor (PaSR) test case. The combined PPAC-RCCE-ISAT methodology shows a significant improvement over the stand-alone PPAC methodology by reducing the number of redundant direct integrations of similar compositions and reducing the number of variables that need to be retained at runtime.
- Publication:
-
Combustion Theory and Modelling
- Pub Date:
- November 2019
- DOI:
- 10.1080/13647830.2019.1606453
- Bibcode:
- 2019CTM....23.1021N
- Keywords:
-
- PPAC;
- RCCE;
- ISAT;
- adaptive chemistry;
- dimension reduction