Multiscale and Correlated Dynamic Adaptive Chemistry and Transport Modeling of Ignition and Flame Regimes of Stratified Fuel Mixtures
Abstract
The objective of the proposed work is to aims to develop a next generation, multi-scale, correlated dynamic adaptive chemistry and transport (CO-DACT) method for accurate and computationally efficient modeling of ignition, ignition to flame and knocking transition, and subgrid turbulence/chemistry interaction in stratified combustion of surrogate diesel fuel mixtures. The proposed work will combine 1) the development of new computationally methods using correlated dynamic adaptive chemistry reduction, correlated dynamic adaptive transport, matrix splitting of compressible flow Riemann solver for convection flux, and hybrid multi-timescale method for chemistry integration and detailed transport computation; 2) advancement in fundamental understanding of the mechanisms of combustion regimes and ignition to flame and knocking transition in both thermally and fuel stratified high pressure and low temperature combustion; and 3) the development of dynamic adaptive large eddy simulation (LES) and direct numerical simulation (DNS) method for accurate modeling of small scale combustion dynamics and subgrid turbulence-chemistry interaction. The work will consist of five thrusts: (1) Development of a correlated dynamic adaptive chemistry and transport (CO-DACT) method, (2) Development of an efficient hybrid multi-timescale (HMTS) and CO-DACT method, (3) Development of a matrix splitting method for efficient modeling of the convective transport in a compressible flow. (4) Modeling of unsteady ignition to flame and knocking transition with temperature and concentration stratified mixtures and alkane/aromatics kinetic coupling, and (5) Development of a dynamically adaptive large eddy simulation (LES) and direct numerical simulation (DNS) method using the computationally efficient CO-DACT algorithm to model appropriately subgrid turbulence/chemistry interaction and small scale combustion dynamics in a stratified turbulent jet flow. This will enable multi-physics and adaptive chemistry/transport modeling of both incompressible and compressible combustion, advance fundamental understanding of the mechanism of engine knocking and small scale turbulent combustion dynamics, and improve computation efficiency of commercial DARS-CFO software for advanced engine design.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1610076
Entities
People
- Yiguang Ju
Organizations
- Army Contracting Command
- Princeton University
- United States Army