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Proper orthogonal decomposition has been utilized for well over a decade to study turbulence and cyclic variation of flow and combustion properties in internal combustion engines. In addition, proper orthogonal decomposition is useful to quantitatively compare multi-cycle in-cylinder measurements with numerical simulations (large-eddy simulations). However, the application can be daunting, and physical interpretation of proper orthogonal decomposition can be ambiguous. In this paper, the mathematical procedure of proper orthogonal decomposition is described conceptually, and a compact MATLAB® code is provided. However, the major purpose is to empirically illustrate the properties of the proper orthogonal decomposition analysis and to propose practical procedures for application to internal combustion engine flows. Two measured velocity data sets from a motored internal combustion engine are employed, one a highly directed flow (each cycle resembles the ensemble average), and the other an undirected flow (no cycle resembles the average). These data are used to illustrate the degree to which proper orthogonal decomposition can quantitatively distinguish between internal combustion engine flows with these two extreme flow properties. In each flow, proper orthogonal decomposition mode 1 is an excellent estimate of ensemble average, and this study illustrates how it is thus possible to unambiguously quantify the cyclic variability of Reynolds-averaged Navier–Stokes ensemble average and turbulence. In addition, this study demonstrates the benefits of comparing two different samples of cycles using a common proper orthogonal decomposition mode set derived by combining the two samples, the effect of spatial resolution, and a method to evaluate the number of snapshots required to achieve convergence.

The proper orthogonal decomposition (POD) has found increasing application for the comparison of measured and computed data as well as the identification of instantaneous and time varying flow structures, particularly cyclic variability in reciprocating internal combustion engines. The patterns observed in the basis functions or modes are sometimes interpreted as coherent structures, though justification of this is not obvious from the mathematical derivations. Similarly, there is no consensus about whether or not the ensemble mean should be subtracted prior to performing POD on a data set. Synthetic flow fields are used here to reveal POD properties otherwise ambiguous in real stochastic flow data. In particular, each POD mode includes elements of all flow structures from all input snapshots and in general, several modes are needed to reconstruct physical flow structures. POD analysis of two experimental in-cylinder engine data is done: one flow condition where every cycle resembles the ensemble-averaged flow pattern, and the other with large cyclic variability such that no cycles resemble the ensemble average. The energy and flow patterns of the POD modes, derived with and without first subtracting the mean, are compared to each other and to the Reynolds decomposed flow to reveal properties of the POD modes.

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-A collaborative effort is described to benchmark the TCC-III engine, and to illustrate the application of this data for the evaluation of sub-grid scale models and valve simulation details on the fidelity of Large-Eddy Simulations (LES). The TCC-III is a spark ignition 4-stroke 2-valve engine with a flat head and piston and is equipped with a full quartz liner for maximum optical access that allows high-speed flow measurements with Particle Image Velocimetry (PIV); the TCC-III has new valve seats and a modified intake-system compared to previous configurations. This work is an extension of a previous study at an engine speed of 800 RPM and an intake manifold pressure (MAP) of 95 kPa, where a one-equation eddy viscosity LES model yielded accurate qualitative and quantitative predictions of ensemble averaged mean and RMS velocities during the intake and compression stroke. Here, experimental data were acquired with parametric variation of engine speed and intake manifold absolute pressure to assess the capability of LES models over a range of operating conditions of practical relevance. This paper focuses on the repeatability and accuracy of the measured PIV data, acquired at 1 300 RPM, at two different MAP (95 kPa and 40 kPa), and imaged at multiple data planes and crank angles. Two examples are provided, illustrating the application of this data to LES model development. In one example, the experimental data are used to distinguish between the efficacies of a one-equation eddy viscosity model versus a dynamic structure one-equation model for the sub-grid stresses. The second example addresses the effects of numerical intake-valve opening strategy and local mesh refinement in the valve curtain.Résumé -Benchmark de moteur de référence TCC-III pour la simulation aux grandes échelles (Large-Eddy Simulations, LES) de l'écoulement dans les moteurs à combustion interne -Un projet collaboratif est décrit, visant à caractériser le moteur TCC-III et à illustrer l'application de ces données pour l'évaluation de modèles de sous-maille et des détails de simulation des soupapes sur la fidélité de simulations aux grandes échelles. Le TCC-III est un moteur à allumage commandé 4 temps à deux