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The analysis of thermal fields in the underhood region is complicated by the complex geometry and the influence of a multitude of different heat sources. This complexity means that running full CFD analyses to predict the thermal field in this region is both computationally expensive and time consuming. A method of predicting the thermal field using linear superposition has been developed in order to analyse the underhood region of a simplified Formula One race car, though the technique is applicable to all vehicles. The use of linear superposition allows accurate predictions of the thermal field within a complex geometry for varying boundary conditions with negligible computational costs once the initial characterisation CFD has been run. A quarter scale, rear end model of a Formula One race car with a simplified internal assembly is considered for analysis, though the technique can also be applied to commercial and industrial vehicles.

Accurate modeling of the initial transient period of spray development is critical within diesel engines, as it impacts on the amount of vapor penetration and hence the combustion characteristics of the spray. In addition, in multiple injection schemes shorter injections will be mostly, if not totally, within the initial transient period. This paper investigates how two different commercially available Computational Fluid Dynamics (CFD) codes (hereafter noted as Code 1 and Code 2) simulate transient diesel spray atomization, in a non-combusting environment. The case considered for comparison is a single-hole injection of n-dodecane representing the Engine Combustion Network’s ‘Spray A’ condition. It was identified that the different spray break-up models used by the codes (Reitz-Diwakar for Code 1, Kelvin-Helmholtz/Rayleigh-Taylor (KH-RT) for Code 2) had a significant impact on the transient liquid penetration.

A wide-ranging investigation into the sensitivity of the hybrid RANS-LES based OpenFOAM CFD process at Audi was undertaken. For a range of cars (A1, TT, Q3 & A4) the influence of the computational grid resolution, turbulence model formulation and spatial & temporal discretization is assessed. It is shown that SnappyHexMesh, the Cartesian-prismatic built-in OpenFOAM mesher is unable to generate low y+ grids of sufficient quality for the production Audi car geometries. For high y+ grids there was not a consistent trend of additional refinement leading to improved correlation between CFD and experimental data. Similar conclusions were found for the turbulence models and numerical schemes, where consistent improvements over the baseline setup for all aerodynamic force coefficients were in general not possible. The A1 vehicle exhibited the greatest sensitivity to methodology changes, with the TT showing the least sensitivity.

In-cylinder flow motion has a significant effect on mixture preparation and combustion. Therefore, it is vital that CFD engine simulations are capable of accurately predicting the in-cylinder velocity fields. High-speed planar Particle Image Velocimetry (PIV) experiments have been performed on a single-cylinder GDI optical engine in order to validate CFD simulations for a range of engine conditions. Novel metrics have been developed to quantify the differences between experimental and simulated velocity fields in both alignment and magnitude. The Weighted Relevance Index (WRI) is a variation of the standard Relevance Index that accounts for the local velocity magnitudes to provide a robust comparison of the alignment between two vector fields. Similarly, the Weighted Magnitude Index (WMI) quantifies the differences in the local magnitudes of the two velocity fields.

Accurate modelling for spray vapour fields is critical to enable adequate predictions of spray ignition and combustion characteristics of non-premixed reacting diesel sprays. Spray vapour characteristics are in turn controlled by liquid atomization and the KH-RT liquid jet break-up model is regularly used to predict this: with the KH model used for predicting primary break-up given its definition as a surface wave growth model, and the RT model used for predicting secondary break-up due to it being a drag based, stripping model. This paper investigates how the alteration of the switching position of the KH and RT sub-models within the KH-RT model impacts the resulting vapour field and ignition characteristics. The combustion prediction is handled by the implementation of a 54 species, 269 reaction skeletal mechanism utilising a Well Stirred Reactor model within the Star-CD CFD code.

In-cylinder temperatures and their cyclic variations strongly influence many aspects of internal combustion engine operation, from chemical reaction rates determining the production of NOx and particulate matter to the tendency for auto-ignition leading to knock in spark ignition engines. Spatially resolved measurements of temperature can provide insights into such processes and enable validation of Computational Fluid Dynamics simulations used to model engine performance and guide engine design. This work uses a combination of Two-Colour Planar Laser Induced Fluorescence (TC-PLIF) and Laser Induced Grating Spectroscopy (LIGS) to measure the in-cylinder temperature distributions of a firing optically accessible spark ignition engine. TC-PLIF performs 2-D temperature measurements using fluorescence emission in two different wavelength bands but requires calibration under conditions of known temperature, pressure and composition.

The flows in-cylinder have a profound effect on the mixture preparation and subsequent combustion in all engines. These flows are highly three-dimensional in nature and information from multiple planes is required to characterise the flow dynamics. The flow measurements reported here are from three orthogonal planes in an optical access engine that is based on the Jaguar Land Rover AJ200 Gasoline Direct Injection (GDI) engine. Particle Image Velocimetry (PIV) measurements have been taken every 5°CA from the start of induction to the end of compression. Data have been obtained from 300 cycles for separate experiments measuring flows in the tumble plane, the swirl plane and the cross-tumble plane. Vector comparison metrics are used to quantitatively compare ensemble averaged PIV flow fields to Computational Fluid Dynamics (CFD) simulations across each plane in terms of both the velocity magnitude and direction.