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The effects of numerical methodology in defining the initial conditions and simulating the compression stroke in D.I. diesel engine CFD computations are studied. Lumped and pointwise approaches were adopted in assigning the initial conditions at IVC. The lumped approach was coupled with a two-dimensional calculation of the compression stroke. The pointwise methodology was based on the results of an unsteady calculation of the intake stroke performed by using the STAR-CD code in the realistic engine and port geometry. Full engine and 60 deg. sector meshes were used in the compression stroke calculations in order to check the accuracy of the commonly applied axi-symmetric fluid dynamics assumption. Analysis of the evolution of the main fluid dynamics parameters revealed that local conditions at the time of injection strongly depend on the numerical procedure adopted.

Experimental measurements and numerical computations were made to characterize a spray generated by a high-pressure swirl injector. The Phase Doppler technique was applied to get information on droplet sizes (d10) and axial velocities at defined distances from the injector tip. Global spray visualization was also made. Computations were carried out using a modified version of KIVA 3V. In particular, the break-up length of the sheet and its dimension were computed from a semi-empirical correlation related to the wave instability theory suggested by Dombrowski, including the modifications introduced by Han and Reitz. Two different approaches were used to describe the initial spray conditions. According to the first, discrete particles with a characteristic size equal to the thickness of the sheet are injected. The second approach assumes, that the particles having a SMD computed by a semi-empirical correlation are injected according to a statistical distribution.

Powertrain controller design is among the most challenging problems due to the complexity of the functions that the system has to support, to the safety aspects and to the cost limits imposed by car manufacturers. To compound these difficulties, time-to-market requirements are becoming more and more stringent. Design time, continuously changing specifications and safety considerations have pushed the design more and more towards software implementation of the main functionality. Software has been traditionally designed with very little abstraction in mind thus forcing a tight dependency of the implementation on the particular hardware architecture, e.g., the instruction set of the micro- controller. Software legacy has made the rapid adoption of new technology and IC's almost impossible, stifling innovation. In addition, the absence of a correct abstraction hierarchy made verifying the correctness of the behavior of the system as well as adding new functionality extremely difficult.

Knock is a non-deterministic phenomenon and its intensity is typically defined by a non-symmetrical distribution, under fixed operating conditions. A statistical approach is therefore the correct way to study knock features. Typically, intrinsically deterministic knock models need to artificially introduce Cycle-to-Cycle Variation (CCV) of relevant combustion parameters, or of cycle initial conditions, to generate different knock intensity values for a given operating condition. Their output is limited to the percentage of knocking cycles, once the user imposes an arbitrary knock intensity threshold to define the correlation between the number of knocking events and the Spark Advance (SA). In the first part of the paper, a statistical analysis of knock intensity is carried out: for different values of SA, the probability distributions of an experimental Knock Index (KI) are self-compared, and the characteristics of some percentiles are highlighted.