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This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

The presented paper deals with a methodology to model cycle-to-cycle variations (CCV) in 0-D/1-D simulation tools. This is achieved by introducing perturbations of combustion model parameters. To enable that, crank angle resolved data of individual cycles (pressure traces) have to be available for a reasonable number of engine cycles. Either experimental data or 3-D CFD results can be applied. In the presented work, experimental data of a single-cylinder research engine were considered while predicted LES 3-D CFD results will be tested in the future. Different engine operating points were selected - both stable ones (low CCV) and unstable ones (high CCV). The proposed methodology consists of two major steps. First, individual cycle data have to be matched with the 0-D/1-D model, i.e., combustion model parameters are varied to achieve the best possible match of pressure traces - an automated optimization approach is applied to achieve that.

The present paper deals with the application of the LES approach to in-cylinder flow modeling. The main target is to study cycle-to-cycle variability (CCV) using 3D-CFD simulation. The engine model is based on a spark-ignited single-cylinder research engine. The results presented in this paper cover the motored regime aiming at analysis of the cycle-resolved local flow properties at the spark plug close to firing top dead center. The results presented in this paper suggest that the LES approach adopted in the present study is working well and that it predicts CCV and that the qualitative trends are in-line with established knowledge of internal combustion engine (ICE) in-cylinder flow. The results are evaluated from a statistical point of view based on calculations of many consecutive cycles (at least 10).

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

This paper presents calculations of external car aerodynamics by using the finite volume (FV) immersed-boundary method. The FV numerical codes primarily employ Reynolds-Averaged Navier-Stokes (RANS) models. In recent years, and due to possibility to run very large computational meshes, these models are usually used in conjunction with the advanced near-wall models. Moreover, it has been often demonstrated that the accuracy of RANS near-wall models relies on the mesh quality near the wall so by the rule, larger number of wall body-fitted cell-layers are employed. An immersed boundary (IB) method becomes an attractive alternative to the ‘standard’ FV approaches especially when applied to low quality CAD data. In general, the IB method is less investigated and validated for the car aerodynamics, particularly in conjunction with advanced near-wall turbulence models and an adaptive mesh refinement (AMR).

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the finite volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1]. In that work, it was shown that the same accuracy of predicted aerodynamic forces can be achieved by using Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model on both types of meshes, the standard body-fitted (BF), and on the immersed boundary (IB) mesh. Due to all well-known shortcomings of the steady state approach, in this work we deal with the Partially Averaged Navier-Stokes (PANS), which belongs to the hybrid RANS-LES (scale resolving / high fidelity) methods. This approach was developed to resolve a part of the turbulence spectrum adjusting seamlessly from RANS to DNS (Direct Numerical Simulation).

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the Finite Volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1, 2]. In that work, it was shown that the same accuracy of predicted aerodynamic forces could be achieved for both types of computational meshes, the standard body-fitted mesh and the immersed boundary (IB) Cartesian mesh, by using the Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model as well as by using the Partially-Averaged Navier-Stokes (PANS) method. Based on the accuracy achieved, Basara et al. [2] concluded that further work could focus on evaluating the turbulence modelling on the immersed boundary meshes only.