Unstructured mesh based models for incompressible turbulent flows

A development of high resolution NFT model for simulation of incompressible flows is presented. The model uses finite volume spatial discretisation with edge based data structure and operates on unstructured meshes with arbitrary shaped cells. The key features of the model include non-oscillatory advection scheme Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) and non-symmetric Krylov-subspace elliptic solver. The NFT MPDATA model integrates the Reynolds Average Navier Stokes (RANS) equations. The implementation of the Spalart-Allmaras one equations turbulence model extends the development further to turbulent flows. An efficient non-staggered mesh arrangement for pressure and velocity is employed and provides smooth solutions without a need of artificial dissipation. In contrast to commonly used schemes, a collocated arrangement for flow variables is possible as the stabilisation of the NFT MPDATA scheme arises naturally from the design of MPDATA. Other benefits of MPDATA include: second order accuracy, strict sign-preserving and full multidimensionality. The flexibility and robustness of the new approach is studied and validated for laminar and turbulent flows. Theoretical developments are supported by numerical testing. Successful quantitative and qualitative comparisons with the numerical and experimental results available from literature confirm the validity and accuracy of the NFT MPDATA scheme and open the avenue for its exploitation for engineering problems with complex geometries requiring flexible representation using unstructured meshes

Characteristics of GDI engine flow structures

The benefits of the gasoline direct injection engine over the more traditional gasoline port-fuel injection engine are well known and include the ability to operate lean of stoichiometric for fuel efficiency improvements, reduced knock propensity and reduced unburned hydrocarbons during cold start and transients. Nevertheless, a number of key challenges still remain including cyclic variability, abnormal combustion phenomena and increased particulate emissions. Our progress in each of these challenges is intrinsically linked to our understanding of the flow field formed within the cylinder. This paper presents the development, validation and subsequent utilisation of a 3D-CFD gasoline direct injection engine model for making predictions of the in-cylinder flow field through the intake and compression strokes. An extensive validation exercise was completed using experimental data from a single cylinder optical research engine to validate both the intake runner, intake valve jet and in-cylinder flow fields. Validation results showed the model to generally compare well against experimental data including indicating data, intake runner velocities and flow momentum, valve jet and in-cylinder flow structures. Differences were identified in the timing of the detachment of the intake valve jet from the cylinder head and a subsequent reduction in effective flow area was hypothesised as contributing to an over prediction of the valve jet and in-cylinder flow velocities. A comparison of the spatial and temporal development of the in-cylinder flow field identified the model to well predict the flow structures through the intake and compression stroke. The model was then exercised with a view to evaluate the impact of solid boundaries on the spatial and temporal development of the in-cylinder flow structure. An analysis on the impact of using a pent-roof optical access window in research engines on the flow structure is also provided, indicating that significant asymmetry and additional recirculation zones in the corners of the access window should be considered when evaluating experimental results from a research engine of this configuration