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Diesel Breeding PUBLIC ACCESS

Looking Into Engines Helps Cross the Best With the Best.

[+] Author Notes

This article was prepared by staff writers in collaboration with outside contributors.

Mechanical Engineering 124(09), 53 (Sep 01, 2002) (1 page) doi:10.1115/1.2002-SEP-4

Abstract

This article discusses the various ways of improving the performance of diesel engines. A Wisconsin engineer is making use of computation methods that mimic natural selection—or, in this case, maybe eugenics—to improve the performance of diesel engines. Peter Senecal, a partner with Convergent Thinking in Madison, WI, is using computational fluid dynamics (CFD) advanced visualization, and a selection method using genetic algorithms aimed at reducing engine emissions and enhancing fuel efficiency. He has been looking ahead to 2007, when tighter vehicle emissions requirements take effect. Senecal and two of his partners, Keith Richards and Eric Pomraning, are continuing the research into cleaner and more efficient engines. Findings have helped to optimize engine design for increased efficiency and lower emissions—two areas of great importance to engine manufacturers and environmentalists.

Article

A Wisconsin engineer is making use of computation methods that mimic natural selection-or, in this case, maybe eugenics- to improve the performance of diesel engines.

Peter Senecal, a partner with Convergent Thinking in Madison, Wis., is using computational fluid dynamics, advanced visualization, and a selection method using genetic algorithms aimed at reducing engine emissions and enhancing fuel efficiency. He is looking ahead to 2007, when tighter vehicle emissions requirements take effect.

Convergent Thinking models interaction between fuel spray and combustion chamber geometry-critical to diesel engine performance and emissions. The image shows the temperature field of combustion in a conventional piston bowl with a six-hole fuel injector.

Grahic Jump LocationConvergent Thinking models interaction between fuel spray and combustion chamber geometry-critical to diesel engine performance and emissions. The image shows the temperature field of combustion in a conventional piston bowl with a six-hole fuel injector.

Genetic algorithms are mathematical operations modeled on the biological principle of gene selection. The idea is to identify desirable traits in different computer models and then combine them. Senecal applied the method to engines when he was earning his PhD. in mechanical engineering at the University of Wisconsin in Madison.

Now Senecal and two of his partners, Keith Richards and Eric Pomraning, are continuing the research into cleaner and more efficient engines. A fourth partner in Convergent Thinking, David Schmidt, who is also a professor at the University of Massachusetts in Amherst, is developing techniques to simulate diesel fuel injection more accurately.

Early research looked at changes in fuel injection velocity and timing. Significant improvements have been found, for example, by increasing the operating pressures of the fuel injectors. In its latest phase, the research factors in changes to engine geometry, as well as adjustments in fuel injection. Past results suggest that traditional engine geometry doesn't take full advantage of new injection systems, Senecal said.

The team uses KIVA CFD software, developed at the Los Alamos National Laboratory. The version Senecal uses was first adapted by the University of Wisconsin and further refined in-house at Convergent Thinking. Researchers view results by using EnSight visualization software from CEI of Apex, N.C.

This article was prepared by staff writers in collaboration with outside contributors.

The researchers use genetic algorithms to sort complex information of fluid dynamics in different combustion chambers. They run the algorithms through a series of engine simulations, each with a slightly altered design.

Ater running the scenarios, the genetic algorithms select the best performer from a group of trials and combine characteristics from that engine with those of other high performers. The engines with the best "genes" are simulated, using the same CFD and visualization process as in past studies. Senecal then rates the engines on their fuel efficiency and the amount of soot and NOx they generate.

Findings have helped to optimize engine design for increased efficiency and lower emissions-two areas of great importance to engine manufacturers and environmentalists.

"We can now indicate to designers the variables that are most important or ones that might have been overlooked had the computer not identified them," Senecal said. The computational studies, for example, have highlighted the importance of injecting fuel in short bursts instead of a single stream, for a cleaner and more efficient burn.

It usually takes Senecal and his colleagues two weeks to run a series of tests that can identify engine characteristics that produce significantly lower emissions without sacrificing fuel economy. At the University of Wisconsin, his engine optimization tool resulted in a design that Consumed 15 percent less fuel than a standard diesel engine while producing one-third the amount of nitrogen oxide and half the soot. The design, which did not involve changes in the shape of the combustion chamber, was tested and confirmed in a university laboratory.

Senecal said he plans a similar test of a design that will involve altered engine geometry. He said he can't say much about it because it's proprietary. He did say that he expects even better numbers than those in the earlier lab test.

Copyright © 2002 by ASME
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