Cold-Flow Investigation of the Darmstadt Engine with Focus on Statistical Convergence: Experimental and Large Eddy Simulation Analysis

The paper analyses particle image velocimetry (PIV) measurements and multi-cycle Large Eddy Simulation (LES) of the in-cylinder flow of the well-known Darmstadt engine, operated in motored condition. This engine is representative of currently made four-valve pent-roof GDI production engines. The so-called operating-point A (OP. A) is investigated hereafter, with focus being made on statistical convergence and relevance of the two datasets. A comparison between the available experimental dataset and author-designed subsets is made using both qualitative observation of the flow fields and quantitative estimates through comparative indices. Besides well-established indices, a new index is introduced, based on the statistical relevance of the k-th experimental ensemble average velocity vector; it is applied to evaluate the influence of the population of cycles on the representation of flow patterns. Simulated fields are then compared to the experimental counterparts using the previously mentioned comparative indices and Proper Orthogonal Decomposition. In particular, POD is employed to characterize the Cycle-to-Cycle Variability (CCV) of the analysed operation and its possible causes. The comparison between experimental flow fields and simulated ones provides an insight of both strengths and weaknesses of the adopted modelling approach.