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Proper Orthogonal Decomposition (POD) is a useful statistical tool for analyzing the cycle-to-cycle variation of internal combustion engine in-cylinder flow field. Given a set of flow fields (also known as snapshots) recorded over multiple engine cycles, the POD analysis optimally decomposes the snapshots into a series of flow patterns (known as POD modes) and corresponding coefficients of successively maximum flow kinetic energy content. These POD results are therefore strongly dependent on the kinetic energy content of the individual snapshots, which may vary over a wide range. However, there is as yet no algorithm in the literature to define, detect, and then remove outlier snapshots from the dataset in a systematic manner to ensure reliable POD results.

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.