Studies of spatial clustering of inertial particles in turbulence

We present studies of the spatial clustering of inertial particles embedded in turbulent flow. A major part of the thesis is experimental, involving the technique of Phase Doppler Interferometry (PDI). The thesis also includes significant amount of simulation studies and some theoretical considerations. We describe the details of PDI and explain why it is suitable for study of particle clustering in turbulent flow with a strong mean velocity. We introduce the concept of the radial distribution function (RDF) as our chosen way of quantifying inertial particle clustering and present some original works on foundational and practical considerations related to it. These include methods of treating finite sampling size, interpretation of the magnitude of RDF and the possibility of isolating RDF signature of inertial clustering from that of large scale mixing. In experimental work, we used the PDI to observe clustering of water droplets in a turbulent wind tunnel. From that we present, in the form of a published paper, evidence of dynamical similarity (Stokes number similarity) of inertial particle clustering together with other results in qualitative agreement with available theoretical prediction and simulation results. We next show detailed quantitative comparisons of results from our experiments, direct-numerical-simulation (DNS) and theory. Very promising agreement was found for like-sized particles (mono-disperse). Theory is found to be incorrect regarding clustering of different-sized particles and we propose a empirical correction based on the DNS and experimental results. Besides this, we also discovered a few interesting characteristics of inertial clustering. Firstly, through observations, we found an intriguing possibility for modeling the RDF arising from inertial clustering that has only one (sensitive) parameter. We also found that clustering becomes saturated at high Reynolds number.

ANALYSIS OF POPULUS TREMULOIDES CLONAL VARIATION AND DELINEATION IN THE OTTAWA NATIONAL FOREST

The technique of delineating Populus tremuloides (Michx.) clonal colonies based on morphology and phenology has been utilized in many studies and forestry applications since the 1950s. Recently, the availability and robustness of molecular markers has challenged the validity of such approaches for accurate clonal identification. However, genetically sampling an entire stand is largely impractical or impossible. For that reason, it is often necessary to delineate putative genet boundaries for a more selective approach when genetically analyzing a clonal population. Here I re-evaluated the usefulness of phenotypic delineation by: (1) genetically identifying clonal colonies using nuclear microsatellite markers, (2) assessing phenotypic inter- and intraclonal agreement, and (3) determining the accuracy of visible characters to correctly assign ramets to their respective genets. The long-term soil productivity study plot 28 was chosen for analysis and is located in the Ottawa National Forest, MI (46° 37'60.0" N, 89° 12'42.7" W). In total, 32 genets were identified from 181 stems using seven microsatellite markers. The average genet size was 5.5 ramets and six of the largest were selected for phenotypic analyses. Phenotypic analyses included budbreak timing, DBH, bark thickness, bark color or brightness, leaf senescence, leaf serrations, and leaf length ratio. All phenotypic characters, except for DBH, were useful for the analysis of inter- and intraclonal variation and phenotypic delineation. Generally, phenotypic expression was related to genotype with multiple response permutation procedure (MRPP) intraclonal distance values ranging from 0.148 and 0.427 and an observed MRPP delta value=0.221 when the expected delta=0.5. The phenotypic traits, though, overlapped significantly among some clones. When stems were assigned into phenotypic groups, six phenotypic groups were identified with each group containing a dominant genotype or clonal colony. All phenotypic groups contained stems from at least two clonal colonies and no clonal colony was entirely contained within one phenotypic group. These results demonstrate that phenotype varies with genotype and stand clonality can be determined using phenotypic characters, but phenotypic delineation is less precise. I therefore recommend that some genetic identification follow any phenotypic delineation. The amount of genetic identification required for clonal confirmation is likely to vary based on stand and environmental conditions. Further analysis, however, is needed to test these findings in other forest stands and populations.