Miniature Precision Components Inc has optimised the design of a new hydrocarbon trap by simulating it with EFD.Lab, a design-orientated flow simulation software package.
Mark Van de Bogert, Product Design Manager for Miniature Precision Components, evaluated the performance of 12 different design alternatives in order to minimise backpressure across the trap while achieving the required level of hydrocarbon absorption.
“EFD.Lab makes it easy and inexpensive for design engineers to perform computational fluid dynamics simulations that in the past would have required the service of analysts with advanced degrees and software packages that lease for tens of thousands of dollars per year,” Van de Bogert said.
The company saw the need for a cost competitive hydrocarbon trap for a partial zero emission vehicle (PZEV) which is 90 per cent cleaner than the average new car.
A key feature of the PZEV vehicle is a hydrocarbon trap in the air intake that prevents stray hydrocarbons from migrating out of the engine after shutdown.
The hydrocarbon trap presents the inherent design challenge of requiring the ability to trap nearly all hydrocarbons while avoiding a significant increase in backpressure for air entering the engine because that would adversely affect fuel efficiency and performance.
“Modelling the design in EFD.Lab was easy,” Van de Bogert said. “I simply called up the software inside CATIA. EFD.Lab automatically distinguished between the solid and empty spaces in our CAD model and meshed the empty regions to prepare for flow analysis. I added the boundary conditions within CATIA, a mass flow rate upstream and a pressure boundary condition downstream of the trap. I analysed various rib configurations and found that a 5 spoke version's backpressure was the lowest, but still not low enough.”
Van de Bogert then ran through about a dozen iterations on the 5-spoke design, changing the geometry of the spokes and the spacing of the carbon elements. The analysis results for each design showed flow rate and direction and pressure at each point in the trap. “The ability to visualize the flow helped me understand where the restrictions were in each design and provided insight into how to reduce the backpressure,” Van de Bogert said. “By the end of this process I had beaten the target for backpressure. We built a rapid prototype of the optimised design and were delighted to discover that the backpressure of the rapid prototype was within a tenth of an inch of water of the CFD predictions.”
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