PRODUCT & TECH
Caterpillar-Argonne partnership shifts heavy-duty engine design into higher gear
Heavy-duty diesel engines still power most large vehicles used in the construction , mining and transportation industries in the US . Engineers are working to improve the fuel efficiency of these engines while minimising pollution to reduce energy consumption and ensure the sustainability of these industries in the future . To tackle this problem , researchers at the US Department of Energy ’ s ( DOE ) Argonne National Laboratory joined forces with Caterpillar Inc , one of the world ’ s largest manufacturers of construction and mining equipment . Taking advantage of Argonne ’ s high-performance computing resources , researchers developed a potential piston design for Caterpillar ’ s engines that could improve fuel efficiency while reducing harmful emissions .
The team first created a framework to optimise combustion system design using a 3Dcomputational fluid dynamics tool called CONVERGE , developed by Convergent Science , Inc . Merging heat transfer and combustion data derived from CONVERGE models with environmental data on soot and nitrogen oxide ( NOx ) production , they then ran hundreds of high-fidelity simulations to develop promising designs for piston bowls — the combustion chambers in diesel engines . Using this method , they were able to identify several designs that had the potential to improve fuel efficiency while reducing emissions . Caterpillar created prototypes of the top-performing
designs using additive manufacturing techniques to validate the model results . “ By leveraging the supercomputing resources available at Argonne , we ran very detailed simulations and also got the results much more quickly , reducing the simulation time from months to weeks ,” said Chao Xu , an Argonne postdoctoral appointee leading the simulation efforts .
One particularly promising piston bowl design improved the mixing process between fuel and air . Researchers found that it could reduce fuel consumption by nearly 1 %, a measurable improvement , while reducing soot by up to 20 %.
“ The workflow we developed will benefit everyone ,” said Sibendu Som , Manager of the Computational Multi-Physics Research Section in Argonne ’ s Energy Systems division , who supervises the team working on the project with Caterpillar . “ We are publishing our methodology so companies can use it to design new piston bowls for themselves .”
In addition to the project ’ s simulation innovations , one of the team ’ s key contributions was its development of an industry-friendly approach , which allows companies to optimise their engine designs using their own inhouse computer systems . This simplified model , based on the results of hundreds of the complex simulations , provides a similar level of accuracy while reducing the computational requirements by as much as 40 %. “ It actually reduces the testing costs if we have a predictive model and optimise designs on a supercomputer . It also reduces the time industry needs to develop a product — a great benefit ,” said Prithwish Kundu , a research scientist who is managing the project at Argonne .
“ Our work with Argonne on this project enabled the exploration of a massive design space ,” said Jon Anders , Principal Investigator and Senior Engineering Specialist in Caterpillar ’ s Integrated Components and Solutions division . “ By working together and leveraging simulation expertise and computing resources from Argonne with manufacturing and testing expertise at Caterpillar , we were able to optimise and test a piston on a timeline that was far shorter than would have otherwise been possible .”
This research was funded by DOE ’ s Advanced Manufacturing Office and Vehicle Technologies Office in the Office of Energy Efficiency and Renewable Energy , under the High-Performance Computing for Manufacturing ( HPC4Mfg ) Program umbrella . The team used Argonne ’ s Laboratory Computing Resource Center , as well as the Mira supercomputer ( now retired ), operated by the Argonne Leadership Computing Facility , a DOE Office of Science User Facility .
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