Influence of Nozzle Geometry Parameters on the Propagation of Fuel Spray Investigated with Linear and Non-Linear Regression Models

Conrad C, Wensing M (2020)


Publication Type: Journal article

Publication year: 2020

Journal

Journal Issue: 2020

DOI: 10.4271/2020-01-2114

Abstract

The nozzle geometry of fuel injectors has a strong influence on turbulences and pressure gradients within the nozzle flow. The flow situation at the nozzle outlet determines the spray propagation into the ambient atmosphere. This spray penetration is critical for gasoline direct injection (GDI) systems. When the spray penetration is too high, it can cause wall and cylinder impingement, which increases particle emissions drastically. However, prediction of fuel spray propagation in dependency of nozzle hole geometry is difficult due to the large difference in scale between the nozzle flow and the spray development. Because of this, spray measurements with varying nozzle geometry parameters and statistical evaluation of these datasets are useful for the future development of fuel injectors. In this study, shadowgraphy measurements of real-size single-hole glass nozzles are presented. The nozzles cover a wide range of geometry parameters relevant to a GDI system. The total penetration depth of the spray plume is evaluated for each nozzle with an injection pressure of 10 MPa. Based on this data, features are derived from the nozzle geometry which have a high correlation to the total penetration depth. These features are used to build a linear regression model in order to understand the basic influence of nozzle parameters on single plume spray propagation.

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How to cite

APA:

Conrad, C., & Wensing, M. (2020). Influence of Nozzle Geometry Parameters on the Propagation of Fuel Spray Investigated with Linear and Non-Linear Regression Models. SAE Technical Papers, 2020. https://dx.doi.org/10.4271/2020-01-2114

MLA:

Conrad, Chris, and Michael Wensing. "Influence of Nozzle Geometry Parameters on the Propagation of Fuel Spray Investigated with Linear and Non-Linear Regression Models." SAE Technical Papers 2020 (2020).

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