Simulating Flame Lift-Off Characteristics of Diesel and Biodiesel Fuels Using Detailed Chemical-Kinetic Mechanisms and LES Turbulence Model

Abstract

Combustion in direct-injection diesel engines occurs in a lifted, turbulent diffusion flame mode. Numerous studies indicate that the combustion and emissions in such engines are strongly influenced by the lifted flame characteristics, which are in turn determined by fuel and air mixing in the upstream region of the lifted flame, and consequently by the liquid breakup and spray development processes. From a numerical standpoint, these spray combustion processes depend heavily on the choice of underlying spray, combustion, and turbulence models. The present numerical study investigates the influence of different chemical kinetic mechanisms for diesel and biodiesel fuels, as well as Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) turbulence models on predicting flame lift-off lengths (LOLs) and ignition delays. Specifically, two chemical kinetic mechanisms for n-heptane (NHPT) and three for biodiesel surrogates are investigated. In addition, the RNG k-ε (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250 μm and 125 μm were obtained for the RANS and LES cases respectively. Validations of these models were performed against experimental data from Sandia National Laboratories in a constant volume combustion chamber. Ignition delay and flame lift-off validations were performed at different ambient temperature conditions. The LES model predicts lower ignition delays and qualitatively better flame structures compared to the RNG k-ε model. The use of realistic chemistry and a ternary surrogate mixture, which consists of methyl decanoate, methyl 9-decenoate, and NHPT, results in better predicted LOLs and ignition delays. For diesel fuel though, only marginal improvements are observed by using larger size mechanisms. However, these improved predictions come at a significant increase in computational cost.

On large eddy simulation of diesel spray for internal combustion engines

“…The liquid length is also drastically over-predicted. This behavior in LES modeling has been observed in other studies (ECN1; Som et al, 2011;Bharadwaj et al, 2009); however, in those studies the reason for this was not clarified. Here, we show that incorrect prediction is due to the absence of STD the modeling that results in the incorrect prediction of exchange rate between the liquid and the gas phase seen in Fig.…”

“…Other studies showed that refinement of the grids might compromise the accuracy of results if spray is modeled using Lagrangien-Eulerin approach. It has shown that the error in prediction of liquid tip length and the rate of mass, momentum and heat exchange between liquid and gas phases increased when fine grids were employed (Som et al, 2011;Solsjo and Bai, 2011;Salewski and Fuchs, 2007).…”

Modeling the combustion of high molecular weight fuels by a functional group approach

“…Whenever a fine discretization of the computational domain to be modeled is required, small kinetic mechanisms are needed to limit the computational cost. For this reason, automatic or manual kinetic mechanism generation followed by mechanism reduction techniques are generally applied to most practical applications [6,7].…”

Large-Eddy Simulation (LES) of Spray Transients: Start and End of Injection Phenomena

“…The presence of hot ambient gas in the sac can be responsible for delayed liquid injection and higher liquid vaporization thereafter (Crua et al, 2010;Pickett et al, 2013). Crua et al (2010) and Stetsyuk et al (2014) observed Diesel jets in hot conditions using ultra-high speed video and found that the initial stage of fuel injection is more complex than the accepted linear temporal evolution. A gaseous pre-jet, with spheroidal cap shape, was observed for a wide range of conditions and issues sub-sonically into hot and still compressed air.…”

“…Further details about this implementation are provided in Senecal et al (2013Senecal et al ( , 2014, Som et al, 2012b andXue et al (2013).…”