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Resabtors - Advanced Multi-Material Muffler Designs for Clean Air Applications
Technical Paper
2020-01-1554
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
Developing and producing resonators for the charged-air side of combustion engines requires a profound knowledge base in the areas of designing, simulating, and producing these parts in different materials (aluminum, copper, stainless steel, and technical plastic).
As combustion engines are constantly being discussed, this existing knowledge base should be used for other applications within and outside the automotive industry. It became apparent very quickly that new challenges often require completely new solutions, designs, and materials to meet the requirements of flow noise reducing parts.
For example, mufflers based on “specially treated foams” and “meta-materials” can be introduced for clean air application. These materials offer new opportunities for adjusting the frequency range and allow for improved broadband flow noise attenuation.
Such parts are called “Resabtors”, taking into account the different flow noise attenuation principles of resonation and absorption. Since installation space is very limited in almost all applications, it was necessary to combine these two principles in one component. This results in significant challenges in identifying the properties of the material and predicting the noise attenuation level via simulation. It was finally possible to solve these challenges. A development environment which has made fast and precise design possible now exists and will be described in the following.
Like all sound absorbers placed in a flow, Resabtors can also produce unwanted flow-induced noise. With the help of mechanical models, a deeper understanding of the origin of flow-induced noise could be achieved. With this knowledge, measures were then derived to reduce the flow-induced noise.
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Buck, R. and Krebs, I., "Resabtors - Advanced Multi-Material Muffler Designs for Clean Air Applications," SAE Technical Paper 2020-01-1554, 2020, https://doi.org/10.4271/2020-01-1554.Data Sets - Support Documents
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References
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