Simulation of four stroke engine cycle for a 4 - valve pentroof engine in KIVA 3VR2

The main purpose of this project is to understand the process of engine simulation using the open source CFD code called KIVA. This report mainly discusses the simulation of the 4-valve Pentroof engine through KIVA 3VR2. KIVA is an open source FORTRAN code which is used to solve the fluid flow field in the engines with the transient 2D and 3D chemically reactive flow with spray. It also focuses on the complete procedure to simulate an engine cycle starting from pre- processing until the final results. This report will serve a handbook for the using the KIVA code.

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.

Speciation with gene-flow in eastern North American red oaks (Quercus section Lobatae)

As foundational species, oaks (Quercus : Fagaceae) support the activities of both humans and wildlife. However, many oaks in North America are declining, a crisis exacerbated by the previous disappearance of other hard mast-producing trees. In addition, the economic demands placed on this drought-tolerant group may intensify if climate change extirpates other, relatively mesophytic species. Genetic tools can help address these management challenges. To this end, we developed a suite of 27 microsatellite markers, of which 22 are derived from expressed sequence tags (ESTs). Many of these markers bear significant homology to known genes and may be able to directly assay functional genetic variation. Markers obtained from enriched microsatellite libraries, on the other hand, are typically located in heterochromatic regions and should reflect demographic processes. Considered jointly, genic and genomic microsatellites can elucidate patterns of gene-flow and natural selection, which are fundamental to both an organism's evolutionary ecology and conservation biology. To this end, we employed the developed markers in an FST-based genome scan to detect the signature of divergent selection among the red oaks (Quercus section Lobatae). Three candidate genes with putative roles in stress responses demonstrated patterns of diversity consistent with adaptation to heterogeneous selective pressures. These genes may be important in both local genetic adaptation within species and divergence among them. Next, we used an isolation-with-migration model to quantify levels of gene-flow among four red oaks species during speciation. Both speciation in allopatry and speciation with gene-flow were found to be major drivers of red oak biodiversity. Loci playing a key role in speciation are also likely to be ecologically important within species