Turbulent flows and turbulent flames are inherently multi-dimensional in space and transient in time. Therefore, multidimensional diagnostics that are capable of resolving such spatial and temporal dynamics have long been desired; and the purpose of this dissertation is to investigate three such diagnostics both for the fundamental study of flow and combustion processes and also for the applied research of practical devices. These multidimensional optical diagnostics are a 2D (two dimensional) two-photon laser-induced fluorescence (TPLIF) technique, a 3D hyperspectral tomography (HT) technique, and a 4D tomographic chemiluminescence (TC) technique. The first TPLIF technique is targeted at measuring temporally-resolved 2D distribution of fluorescent radicals, the second HT technique is targeted at measuring temperature and chemical species concentration at high speed, and the third TC technique is targeted at measuring turbulent flame properties. This dissertation describes the numerical and experimental evaluation of these techniques to demonstrate their capabilities and understand their limitations. The specific aspects investigated include spatial resolution, temporal resolution, and tomographic inversion algorithms. It is expected that the results obtained in this dissertation to lay the groundwork for their further development and expanded application in the study of turbulent flow and combustion processes. / Ph. D.

The scientific consensus has for long been that residential segregation is best conceived of as a multidimensional phenomenon that can exist on several geographical scales (Massey & Denton, 1988; Lee et al., 2008; Reardon & O’Sullivan, 2004; Reardon et al., 2008). Despite this deepened understanding of residential segregation and how to best measure it, theoretical models of segregation processes have tended to disregard the diversity of dimensions and scales of segregation. Moreover, while residential segregation is broadly defined as the spatial separation of people of different social groups (Timberlake & Ignatov, 2014), the frequently used Schelling model is aspatial (Schelling, 1971). In contrast, the lesser-known Sakoda model incorporates a distance-decay effect and is thus explicitly spatial (Sakoda, 1971). The aim of this thesis was to evaluate two theoretical agent-based models of segregation processes—the Schelling- and Sakoda model—by measuring the segregation patterns they generate under different parameter settings across four dimensions and six spatial scales of segregation, ranging from the micro- to the macro-scale. Thus, providing an assessment of the capacity of these models to generate (grow) different forms of residential segregation. Results from simulation experiments showed that the popular Schelling model was limited in its capacity to generate different forms of segregation. In its standard configuration it could generate micro-segregation along two out of four dimensions: Evenness and Exposure. The spatially explicit Sakoda model was able to generate segregation patterns which varied substantially across all scales on the Evenness and Exposure dimensions. In addition, it was able to generate varied patterns of Concentration and Centralization under certain parameter settings. These findings contribute new insights to the possibilities afforded by these two models in modeling processes of residential segregation. If the goal for theoretical models is to generate segregation patterns which vary across all dimensions and scales of residential segregation, then the standard configuration of the Schelling model is not enough. This thesis suggest that the Sakoda model is a promising candidate for this purpose. In addition, this thesis shows the importance of using a comprehensive measurement framework in theoretical modeling of segregation processes.