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This paper describes the work performed in predicting and measuring the contribution of oil churning to the no-load losses of a commercial truck axle at typical running speeds. A computational fluid dynamics (CFD) analysis of the churning losses was conducted. The CFD model accounts for design geometry, operating speed, temperature, and lubricant properties. The model calculates the oil volume fraction and the torque loss caused by oil churning due to the viscous and inertia effects of the fluid. CFD predictions of power losses were then compared with no-load measurements made on a specially developed, dynamometer-driven test stand. The same axle used in the CFD model was tested in three different configurations: with axle shafts, with axle shafts removed, and with ring gear and carrier removed. This approach to testing was followed to determine the contribution of each source of loss (bearings, seals, and churning) to the total loss.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.

This paper presents total kinetic energy and dissipation rate spectra calculated from particle image velocimetry (PIV) measurements in a motored, spark-ignition direct-injection (SIDI) engine. Velocity fields were obtained at two engine speeds and swirl conditions in the second half of the compression stroke. Two magnifications were used to achieve a spatial dynamic range covering from the full cross-section of the flat piston window (∼45 mm) down to 350 μm. Sets of 300 instantaneous vector fields were filtered using a Gaussian filter to isolate flow structures over a range of length-scales. The kinetic energy and dissipation rate spectra have been normalized using mean kinetic energy and mean piston speed. Results indicate that if the mean piston speed is selected as the representative outer variable, the kinetic energy and dissipation rate spectra at 2000 RPM and 600 RPM become self-similar over a portion of the spectra regardless of swirl level.