Multiscale and Correlated Dynamic Adaptive Chemistry and Transport Modeling of Ignition and Flame Regimes of Stratified Fuel Mixtures
Abstract
Major Goals: Advanced engines need to operate at higher boosted pressure, lower temperature, and variety of alternative fuels for higher energy efficiency, higher power, more fuel flexibility, and less emissions. However, at higher pressures, low temperature chemistry plays a critical role in affecting engine performance, engine knocking, combustion processes, and results in strong turbulence/chemistry interaction as well as new ignition and flame regimes. Quantitative modeling of such complicated reactive flow at extreme conditions requires detailed models for chemical kinetics and transport, and thus is extremely challenging. The goal of this proposal is to develop a hybrid multi-timescale and correlated dynamic adaptive chemistry and transport (HMTS/CO-DACT) method for accurate and computationally-efficient modeling of low temperature ignition and knock formation of surrogate diesel fuel mixtures. Accomplishments: In this project, we developed a hybrid multi-timescale and correlated dynamic adaptive chemistry and transport (HMTS/CO-DACT) method for accurate and computationally efficient modeling of low temperature ignition and knock formation of surrogate diesel fuel mixtures. The results showed that the present CO-DACT method is very computationally efficient to handle detailed chemical kinetics and multi-species transport properties. The method was successfully applied not only to low temperature and high temperature ignition and flame modeling but also to the simulations of engine knocking. The results show clearly that not only low temperature chemistry but also its interaction with turbulence significantly affect knock formation. By considering both the temperature and fuel concentration gradients, an engine knock regime diagram with and without low temperature chemistry is obtained.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 14, 2019
- Accession Number
- AD1089031
Entities
People
- Yiguang Ju
Organizations
- Princeton University