Prediction of Ignition Regimes in DME/Air Mixtures with Temperature and Concentration Fluctuations
KAUST DepartmentClean Combustion Research Center
Physical Sciences and Engineering (PSE) Division
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Mechanical Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/630815
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AbstractThe objective of the present study is to establish a theoretical prediction of the autoignition behavior of a reactant mixture for a given initial bulk mixture condition. The ignition regime criterion proposed by Im and coworkers based on the Sankaran number (Sa), which is a ratio of the laminar flame speed to the spontaneous ignition front speed, is extended to account for both temperature and equivalence ratio fluctuations. The extended ignition criterion is then applied to predict the autoignition characteristics of dimethyl ether (DME)/air mixtures and validated by two-dimensional direct numerical simulations (DNS). The response of the ignition mode of DME/air mixtures to three initial mean temperatures of 770, 900 K, and 1045 K lying within/outside the NTC regime, two levels of temperature and concentration fluctuations at a pressure of 30 atm and equivalence ratio of 0.5 is systematically investigated. The statistical analysis is performed, and a newly developed criterion –the volumetric fraction of Sa < 1.0, FSa,S, is proposed as a deterministic criterion to quantify the fraction of heat release attributed to strong ignition. It is found that the strong and weak ignition modes are well captured by the predicted Sa number and FSa,S regardless of different initial mean temperatures and the levels of mixture fluctuations and correlations. Sap and FSa,S demonstrated under a wide range of initial conditions as a reliable criterion in determining a priori the ignition modes and the combustion intensity.
CitationLuong MB, Hernandez Perez FE, Sow A, Im HG (2019) Prediction of Ignition Regimes in DME/Air Mixtures with Temperature and Concentration Fluctuations. AIAA Scitech 2019 Forum. Available: http://dx.doi.org/10.2514/6.2019-2241.
SponsorsThis work was sponsored by competitive research funding from King Abdullah University of Science and Technology. This research used the resources of the KAUST Supercomputing Laboratory (KSL).
JournalAIAA Scitech 2019 Forum