Experimental measurements of the spatial distribution of 3-D Lagrangian dispersion rates

被引:0
|
作者
Choi, WC
Guezennec, YG
机构
[1] FloCo Tec Inc, Columbus, OH 43212 USA
[2] Ohio State Univ, Dept Mech Engn, Columbus, OH 43210 USA
关键词
flow field measurement; internal combustion engine; mixing; dispersion rate; Lagrangian data; image processing; 3-D particle tracking velocimetry (3-PTV);
D O I
10.1299/jsmeb.40.583
中图分类号
O414.1 [热力学];
学科分类号
摘要
The mixing phenomenon in fluid flow fields has two major components: the advective mixing process driven by the large scale fluid motions and the diffusive mixing process driven by small scale molecular interactions. It is well accepted and amply demonstrated that, in many flows of interest to engineering the overall mixing can be strongly enhanced by an efficient advective mixing, i.e. by bringing the different species involved in close proximity to each other for molecular diffusion to take place over a short period of time. Over the past several years, we have developed an experimental 3-D fluid measurement technique, namely 3-D particle tracking velocimetry (PTV), in which the 3-D fluid velocities are determined by establishing (by photographic means) the 3-D trajectories of flow tracer particles. This paper describes a method for extracting 3-D Lagrangian dispersion rates from such 3-D PTV measurements. Specifically, a quantitative measure of the advective mixing is obtained by evaluating the normal dispersion rate of instantaneous nearby physical trajectories (in direction normal to the instantaneous local velocity vector). Then the magnitude of the root mean square (rms) of the instantaneous local dispersion rate is computed (in the ensemble averaged sense) over many realizations throughout the entire volume of the fluid being studied. This technique is applied to an in-cylinder Row field in an internal combustion (IC) engine in order to promote a better understanding of mixing characteristics by comparing the spatial distribution of the normal dispersion to the 3-D flow patterns.
引用
收藏
页码:583 / 591
页数:9
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