On The Validation of LES Applied to Internal Combustion Engine Flows: Part 1: Comprehensive Experimental Database

Improved understanding of in-cylinder flows requires knowledge from well-resolved experimental velocimetry measurements and flow simulation modeling. Engine simulations using large eddy simulations (LES) are making large progress and the need for well documented velocimetry measurements for model va...

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Veröffentlicht in:Flow, turbulence and combustion turbulence and combustion, 2014, Vol.92 (1-2), p.269-297
Hauptverfasser: Baum, E., Peterson, B., Böhm, B., Dreizler, A.
Format: Artikel
Sprache:eng
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Zusammenfassung:Improved understanding of in-cylinder flows requires knowledge from well-resolved experimental velocimetry measurements and flow simulation modeling. Engine simulations using large eddy simulations (LES) are making large progress and the need for well documented velocimetry measurements for model validation is high. This work presents velocimetry measurements from PIV, high-speed PIV, stereoscopic PIV, and tomographic PIV to extensively describe the in-cylinder flow field in a motored optical engine operating at 800 RPM. These measurements also establish a comprehensive database designed for LES model development and validation. Details of the engine, engine accessory components, and well-controlled boundary conditions and engine operation are presented. The first two statistical moments of the flow field are computed and show excellent agreement among the PIV database. Analysis of statistical moments based on limited sample size is presented and is important for modeling validation purposes. High-speed PIV resolved the instantaneous flow field throughout entire engine cycles (i.e. 719 consecutive crank-angles), while tomographic PIV images are further used to investigate the 3D flow field and identify regions of strong vortical structures identified by the Q-criterion. Principle velocity gradient components are computed and emphasize the need to resolve similar spatial scales between experimental and modeling efforts for suitable model validation.
ISSN:1386-6184
1573-1987
DOI:10.1007/s10494-013-9468-6