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High-fidelity large eddy simulation (LES) of direct-injection processes in internal combustion engines provides an essential component for development of high-efficiency, low-emissions vehicles. Here LES reveals how fuel from a state-of-the-art injector mixes with air inside an engine cylinder. Image: Joseph Oefelein and Daniel Strong, Sandia National Laboratories.
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Air and fuel mix violently during turbulent
combustion. The ferocious mixing needed to ignite fuel and sustain its burning
is governed by the same fluid dynamics equations that depict smoke swirling
lazily from a chimney. Large swirls spin off smaller swirls and so on. The
multiple scales of swirls pose a challenge to the supercomputers that solve
those equations to simulate turbulent combustion. Researchers rely on these
simulations to develop clean-energy technologies for power and propulsion.
A team led by mechanical engineers Joseph
Oefelein and Jacqueline Chen of Sandia National Laboratories (Sandia) simulates
turbulent combustion at different scales. A burning flame can manifest chemical
properties on small scales from billionths of a meter up to thousandths of a
meter, whereas the motion of an engine valve can exert effects at large scales
from hundredths of a meter down to millionths of a meter. This multiscale
complexity is common across all combustion applications—internal combustion
engines, rockets, turbines for airplanes and power plants, and industrial
boilers and furnaces.
Chen and Oefelein were allocated 113 million
hours on Oak Ridge Leadership Computing Facility's Jaguar supercomputer in
2008, 2009, and 2010 to simulate autoignition and injection processes with
alternative fuels. For 2011 they received 60 million processor hours for
high-fidelity simulations of combustion in advanced engines. Their team uses
simulations to develop predictive models validated against benchmark
experiments. These models are then used in engineering-grade simulations, which
run on desktops and clusters to optimize designs of combustion devices using
diverse fuels. Because industrial researchers must conduct thousands of
calculations around a single parameter to optimize a part design, calculations
need to be inexpensive.
"Supercomputers are used for expensive
benchmark calculations that are important to the research community,"
Oefelein says. "We [researchers at national labs] use the Oak Ridge
Leadership Computing Facility to do calculations that industry and academia
don't have the time or resources to do."
The goal is a shorter, cheaper design cycle
for U.S.
industry. The work addresses Department of Energy (DOE) mission objectives to
maintain a vibrant science and engineering effort as a cornerstone of American
economic prosperity and lead the research, development, demonstration, and
deployment of technologies to improve energy security and efficiency. The
research was funded by DOE through the Office of Science's Advanced Scientific
Computing Research and Basic Energy Sciences programs, the Office of Energy
Efficiency and Renewable Energy's Vehicle Technologies program, and the
American Recovery and Reinvestment
Act-funded Combustion
Energy Frontier
Research Center.
Making combustion more efficient would have
major consequences, given our reliance on natural gas and oil. Americans use
two-thirds of their petroleum for transportation and one-third for heating
buildings and generating electricity. "If low-temperature compression
ignition concepts employing dilute fuel mixtures at high pressure are widely
adopted in next-generation autos, fuel efficiency could increase by as much as
25 to 50%," Chen says.
Complementary codes
Direct numerical simulation reveals turbulent combustion of a lifted
ethylene/air jet flame in a heated coflow of air. Computation by Chun Sang Yoo
and Jackie Chen of Sandia National Laboratories, rendering by Hongfeng Yu of
SNL. Chen uses a direct numerical simulation (DNS) code called S3D to simulate
the finest microscales of turbulent combustion on a three-dimensional virtual
grid. The code models combustion unhindered by the shape of a device. These
canonical cases emulate physics important in both fast ignition events and
slower eddy turbulence and provide insight into how flames stabilize,
extinguish, and reignite.
Oefelein, on the other hand, uses a large
eddy simulation (LES) code called RAPTOR to model processes in laboratory-scale
burners and engines. LES captures large-scale mixing and combustion processes
dominated by geometric features, such as the centimeter scale on which an
engine valve opening might perturb air and fuel as they are sucked into a
cylinder, compressed, mixed, burned to generate power, and pushed out as
exhaust.
Whereas DNS depicts the fine-grained detail,
LES starts at large scales and works its way down. The combination of LES and
DNS running on petascale computers can provide a nearly complete picture of combustion
processes in engines.
"Overlap between DNS and LES means
we'll be able to come up with truly predictive simulation techniques,"
Oefelein says. Today experimentalists burn fuel, collect data about the flame,
and provide the experimental conditions to computational scientists, who plug
the equations into a supercomputer that simulates a flame with the same
characteristics as the observed flame. Researchers compare simulation with
observation to improve their models. The goal is to gain confidence that
simulations will predict what happens in the experiments. New products could
then be designed with inexpensive simulations and fewer prototypes.
In a high-fidelity DNS with cells just 5
millionths of a meter wide, Chen's team modeled combustion in a canonical
high-pressure, low-temperature domain to investigate processes relevant to
homogeneous charge compression ignition. Another simulation, using 7 billion
grid points, explored syngas, a mix of carbon monoxide and hydrogen that burns
more cleanly than coal and other carbonaceous fuels. It used 120,000
(approximately half) of Jaguar's processors and generated three-quarters of a
petabyte of data.
Since their 2008 simulation of a hydrogen
flame—the first to fully resolve detailed chemical interactions such as species
composition and temperature in a turbulent flow environment—they have simulated
fuels of increasing complexity. Because real-world fuels are mixtures,
simulations use surrogates to represent an important fuel component. Current
simulations focus on dimethyl ether (an oxygenated fuel) and n-heptane (a
diesel surrogate). Simulations are planned for ethanol and iso-octane
(surrogates for biofuel and gasoline, respectively).
Oefelein uses RAPTOR to investigate
turbulent reacting flows in engines. In a GM-funded experimental engine
designed at the University
of Michigan and used by
the research community as a benchmark, he explores phenomena such as
cycle-to-cycle variations, which can cause megaknock—an extreme form of the
"bouncing marbles" sound sometimes heard in older engines. The fuel
injection, air delivery, and exhaust systems are interconnected, and pressure
oscillations have huge effects on engine performance. "Megaknock can do
significant damage to an engine in one shot," said Oefelein. He noted that
combustion instabilities also plague power plants, where fear forces designers
of gas turbines to make conservative choices that lessen performance.
"Combustion instabilities can destroy a multimillion dollar system in
milliseconds," Oefelein says.
Petascale simulations will light the way for
clean-energy devices and fuel blends that lessen combustion instabilities. The
data they generate will inform and accelerate next-generation technologies that
increase energy security, create green jobs, and strengthen the economy.
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