Sandia researchers use Direct Numerical Simulations to enhance combustion efficiency and reduce pollution in diesel engines; cool flames
13 October 2017
Sandia National Laboratories mechanical engineer Jackie Chen and colleagues Alex Krisman and Giulio Borghesi recently identified novel behavior of a key, temperature-dependent feature of the ignition process called a cool flame in the fuel dimethyl ether. The researchers used a two-dimensional direct numerical simulation (DNS) to provide a fully resolved description of ignition at diesel engine-relevant conditions. The focus of the study is on the behavior of the low-temperature chemistry (LTC) and the way in which it influences the high-temperature ignition.
The cool flame burns at less than 1,150 Kelvin (1,610 ˚F)—about half the typical flame burning temperature of 2,200 K. While cool flames were first observed in the early 1800s, their properties and usefulness for diesel engine design have only recently been investigated.
The study showed that LTC develops as a “spotty” first-stage autoignition in lean regions which transitions to a diffusively supported cool-flame and then propagates up the local mixture fraction gradient towards richer regions.
The cool-flame speed is much faster than can be attributed to spatial gradients in first-stage ignition delay time in homogeneous reactors. The cool-flame causes a shortening of the second-stage ignition delay times compared to a homogeneous reactor and the shortening becomes more pronounced at richer mixtures.
They observed multiple high-temperature ignition kernels over a range of rich mixtures that are much richer than the homogeneous most reactive mixture; most kernels form much earlier than suggested by the homogeneous ignition delay time of the corresponding local mixture. Overall, the researchers said, the results suggest that LTC can strongly influence both the timing and location in composition space of the high-temperature ignition.
We’re trying to quantify the influence of cool flames in stratified turbulent jets during the ignition and flame stabilization processes. The insights gleaned will contribute to more efficient, cleaner burning engines. Our holy grail is to understand the physics of turbulent mixing coupled with high-pressure ignition chemistry, to aid in developing predictive computational fluid dynamics models that can be used to optimize engine design.
—Jackie Chen
The team’s research has shown that during autoignition, cool flames accelerate the formation of ignition kernels—tiny localized sites of high temperature that seed a fully burning flame—in fuel-lean regions. The work was performed at Sandia’s Combustion Research Facility using Direct Numerical Simulations, a powerful numerical experiment that resolves all turbulence scales, and was published in the Proceedings of the Combustion Institute with Krisman as the lead author. The work was supported by the Department of Energy’s (DOE’s) Office of Basic Energy Sciences.
Borghesi further extended the cool flame study by performing a three-dimensional study on n-dodecane, a diesel surrogate fuel that has been the recent focus of Sandia’s Engine Combustion Network on spray combustion in diesels (the study that Krisman authored with dimethyl ether, a simpler fuel, was in two dimensions). Borghesi’s paper is pending publication. Taken together, both Krisman’s and Borghesi’s papers will form a comprehensive study of low-temperature chemistry in autoignitive flames at different stages of ignition. The conditions of the flame that start the combustion process are crucial for improving engine efficiency and minimizing pollution formation.
The cool flame studies were performed at the DOE’s Oak Ridge Leadership Computing Facility on Titan, a 27-petaflop supercomputer, using a computational grant from DOE INCITE , or Innovative and Novel Computational Impact on Theory and Experiment. Computations using some of the world’s largest supercomputers, such as Titan, are required to produce an accurate and detailed calculation of the autoignition process.
As part of the DOE Exascale Computing Program, the team collaborates with outside institutions (including NVIDIA; Lawrence Berkeley, Oak Ridge, Argonne and Los Alamos national laboratories; the National Renewable Energy Laboratory and Stanford University) to develop performance-portable algorithms to enhance the computing efficiency for Direct Numerical Simulation combustion studies.
In the future, the team would like to investigate basic questions about the speed and structure of flames at diesel engine conditions and study the relationship between spray evaporation, ignition, mixing and soot processes associated with multicomponent fuels. These basic questions will contribute to studying the cool flame’s crucial role in engine energy production and exercise the valuable capabilities of Direct Numerical Simulations running on exascale supercomputers as a highly precise and detailed numerical simulation method.
Resources
Alex Krisman, Evatt R. Hawkes, Mohsen Talei, Ankit Bhagatwala, Jacqueline H. Chen (2017) “A direct numerical simulation of cool-flame affected autoignition in diesel engine-relevant conditions,” Proceedings of the Combustion Institute, Volume 36, Issue 3, Pages 3567-3575 doi: 10.1016/j.proci.2016.08.043
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