Modelling Methanol–Diesel Jet Interaction of a Dual-Fuel Direct-Injection System Using Superposed Stream Functions and Schlieren Imaging

Clemente Mallada R, Strauß L, Wittmann F, Kowis C, Rieß S, Wensing M (2025)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2025

Book Volume: A5-4

Pages Range: 77-82

Conference Proceedings Title: PROCEEDINGS OF The 11th INTERNATIONAL CONFERENCE ON MODELING AND DIAGNOSTICS FOR ADVANCED ENGINE SYSTEMS

Event location: Makuhari Messe International Conference Hall, Chiba, Japan

Abstract

Methanol is increasingly recognized as a renewable and sustainable fuel candidate for heavy-duty engine applications, especially when employed in dual-fuel direct injection (DFDI) strategies. In such systems, methanol is introduced via a gasoline direct injector (GDI), forming stratified charge layers, while a diesel injector provides a high-cetane pilot injection for ignition. This strategy leverages methanol’s clean-burning properties and diesel’s ignition stability.

Applying the principle of momentum conservation to steady, incompressible jets has yielded a theoretical framework exemplified by the works of Naber&Siebers and Musculus&Kattke. These models serve as tools for estimating spray penetration and air entrainment, bridging the gap between numerical simulations and experimental validations. To understand and optimize the interaction between the methanol and diesel jets within these systems, a robust modeling framework is essential. However, they are inherently limited to single-jet behavior and do not account for the interactions between multiple jets, as is characteristic in DFDI configurations.

In this work, the authors propose to apply well-known self-similar solutions of the convection-diffusion Navier–Stokes equations for the far flow field of an axisymmetric stationary gas jet in an incompressible ambient to model the two interacting gas jets. Under a simplified but physically motivated constraint, each transient jet is represented by the analytical stream function of a stationary jet that carries half the momentum, and the mass distribution is approximated by the superposition of these stream functions so that the flow features of jet merging and deflection are captured.

The estimated density and mass distributions derived from this approach are qualitatively compared to the mean optical thickness obtained experimentally from high-speed Schlieren imaging. The experiments are conducted at engine-like conditions in a constantly scavenged, constant-pressure vessel at three different ambient densities (17, 22, and 27 kg/m³). A methanol spray is injected via a GDI at 500 bar, and a diesel jet is injected at 1500 bar. The two jets collide at an angle of 0.42 radians.

The proposed model serves as a semi-analytical diagnostic tool, offering improved physical insight into jet–jet interaction dynamics in DFDI systems. While it does not replace full CFD simulations, it provides a complementary means for interpreting experimental visualizations and guiding simulation validation efforts. The work aims to contribute towards a more physically grounded methodology for analysing mixture formation.

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How to cite

APA:

Clemente Mallada, R., Strauß, L., Wittmann, F., Kowis, C., Rieß, S., & Wensing, M. (2025). Modelling Methanol–Diesel Jet Interaction of a Dual-Fuel Direct-Injection System Using Superposed Stream Functions and Schlieren Imaging. In The Japan Society of Mechanical Engineers (JSME) (Eds.), PROCEEDINGS OF The 11th INTERNATIONAL CONFERENCE ON MODELING AND DIAGNOSTICS FOR ADVANCED ENGINE SYSTEMS (pp. 77-82). Makuhari Messe International Conference Hall, Chiba, Japan, JP.

MLA:

Clemente Mallada, Rafael, et al. "Modelling Methanol–Diesel Jet Interaction of a Dual-Fuel Direct-Injection System Using Superposed Stream Functions and Schlieren Imaging." Proceedings of the COMODIA 2025 The 11th International Conference on Modeling and Diagnostics for Advanced Engine Systems, Makuhari Messe International Conference Hall, Chiba, Japan Ed. The Japan Society of Mechanical Engineers (JSME), 2025. 77-82.

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