Understanding the physics governing primary atomization of high pressure fuel sprays is of paramount importance to accurately model combustion in direct injection engines. The small length and time scales of features that characterize this process falls below the resolution power of typical grids in CFD simulations, which necessitates the inclusion of physical models (sub-models) to account for unresolved physics. Unfortunately current physical models for fuel spray atomization used in engine CFD simulations are based on significant empirical scaling because there is a lack of experimental data to understand the governing physics. The most widely employed atomization sub-model used in current CFD simulations assumes the spray atomization process to be dominated by aerodynamically-driven surface instabilities, but there has been no quantitative experimental validation of this theory to date. The lack of experimental validation is due to the high spatial and temporal resolutions required to simultaneously to image these instabilities, which is difficult to achieve. The present work entails the development of a diagnostic technique to obtain high spatial and temporal resolution images of jet breakup and atomization in the near nozzle region of Gasoline Direct Injection (GDI) sprays. It focuses on the optical setup required to achieve maximum illumination, image contrast, sharp feature detection, and temporal tracking of interface instabilities for long-range microscopic imaging with a high-speed camera. The resolution and performance of the imaging system is characterized by evaluating its modulation transfer function (MTF). The setup enabled imaging of GDI sprays for the entire duration of an injection event (several milliseconds) at significantly improved spatial and temporal resolutions compared to historical spray atomization imaging data. The images show that low to moderate injection pressure sprays can be visualized with a high level of detail and also enable the tracking of features across frames within the field of view (FOV)

The thesis is divided in two parts, corresponding to the two main subjects on which I have worked during my PhD. In the first Part, we introduce many-body long-range interacting systems, such as plasma and self-gravitating systems. We first review the well known properties of isolated systems, which show peculiar behaviors both for what concern the equilibrium and the relaxation to equilibrium. We then consider long-range systems driven away from equilibrium and we show how the techniques developed for isolated systems can be extended to describe these situations. Generalizations to describe simplified models relevant for geophysical flows and two-dimensional turbulence are also discussed. Our work stands at the edge between the study of long-range interacting systems and the study of non-equilibrium systems.The second part of the thesis is devoted to the study of equilibrium properties of Hamiltonian systems with energy landscape techniques. A number of recent results is reviewed and applied to long and short-range interacting systems. One of the scope of my work was to study models whose energy landscape is much more complicated than what previously done. In the case of ferromagnetic short-range O(n) models on hypercubic lattices, our analysis unveiled a striking similarity between the critical energies of the Ising model and the O(n) models defined on the same lattice with the same interaction matrix. Generalizations of the Stillinger and Weber formalism are discussed as preliminary results and future perspectives.

Hemoenzymes are prevalent in nature and participate in a wide range of biological activities. Frequently, high-valence iron intermediates are involved in the catalytic events of these enzymes, especially when the activation of peroxide or dioxygen is involved. Building on the fundamental framework of iron-oxygen chemistry, the mechanistic understandings of these enzymes and their reactive intermediates constantly attract attention from the enzymology community. This dissertation work focused on the mechanistic studies on two hemoenzymes, tryptophan 2,3-dioxygenase (TDO) and MauG, both of which catalyze unique chemical transformations, i.e., tryptophan oxidation. TDO and MauG are structurally distinct from each other; they catalyze different types of oxidization reactions on tryptophan via diverse strategies. TDO catalyzes the ring-cleavage dioxygenation reaction of free L-tryptophan, incorporating both oxygen atoms from dioxygen into the substrate. MauG uses hydrogen peroxide as the oxidant to catalyze a complex posttranslational-modification reaction on two tryptophan residues from a protein substrate. It utilizes radical chemistry to perform a 40-Å long-range catalytic event. Despite the differences in their catalytic behavior, both enzymes are suggested to employ high-valence iron intermediates in their reactions. A collection of biochemical and spectroscopic approaches was employed to obtain detailed insight into the electronic and structural contributions to the formation and stabilization of high-valence iron intermediates, and into the heme-dependent tryptophan-oxidizing mechanisms. In the study TDO, we solved the long-standing mystery of how the active Fe(II) enzyme is generated from the resting Fe(III) form by hydrogen peroxide. A peroxide-driven reactivation mechanism was established based on the identification of a compound ES-type ferryl intermediate. Additional efforts were dedicated to clarify the controversy in the literature regarding the catalytic roles of a distal histidine residue. Chemical-rescue approaches were used to specify the catalytic contributions of the target residue. In the study of MauG, we discovered an unprecedented tryptophan-mediated charge-resonance phenomenon in the bis-Fe(IV) redox state. This discovery provides the molecular basis for the chemical reactivity and stability of the catalytically competent bis-Fe(IV) intermediate. Together with our collaborators, we also outlined the mechanism of the MauG-mediated long-range catalysis by identifying the catalytic functions of several important residues along the reaction pathway.

Fluorinated compounds are environmentally persistent and have been demonstrated to bioaccumulate and contribute to climate change. The focus of this work was to better understand the atmospheric chemistry of poly- and per-fluorinated compounds in order to appreciate their impacts on the environment. Several fluorinated compounds exist for which data on climate impacts do not exist. Radiative efficiencies (REs) and atmospheric lifetimes of two new long-lived greenhouse gases (LLGHGs) were determined using smog chamber techniques: perfluoropolyethers and perfluoroalkyl amines. Through this, it was observed that RE was not directly related to the number of carbon-fluorine bonds. A structure-activity relationship was created to allow the determination of RE solely from the chemical structure of the compound. Also, a novel method was developed to detect polyfluorinated LLGHGs in the atmosphere. Using carbotrap, thermal desorption and cryogenic extraction coupled to GC-MS, atmospheric measurements can be made for a number of previously undetected compounds. A perfluoroalkyl amine was detected in the atmosphere using this technique, which is the compound with the highest RE ever detected in the atmosphere. Perfluorocarboxylic acids (PFCAs) are water soluble and non-volatile, suggesting they are not susceptible to long-range transport. A hypothesis was derived to explain the ubiquitous distribution of these compounds involving atmospheric formation of PFCAs from volatile precursors. Using smog chamber techniques with offline analysis, perfluorobutenes and fluorotelomer iodides were shown to yield PFCAs from atmospheric oxidation. Dehydrofluorination of perfluorinated alcohols (PFOHs) is poorly understood in the mechanism of PFCA atmospheric formation. Using density functional techniques, overtone-induced photolysis was shown to lead to dehydrofluorination of PFOHs. In the presence of water, this mechanism could be a sink of PFOHs in the atmosphere. Confirmation of the importance of volatile precursors was derived from examination of snow from High Arctic ice caps. This provided the first empirical evidence of atmospheric deposition. Through the analytes observed, fluxes and temporal trends, it was concluded that atmospheric oxidation of volatile precursors is an important source of PFCAs to the Arctic.

For a stationary two dimensional random field, we utilize the classical Kolmogorov-Wiener theory to develop prediction methodology which requires minimal assumptions on the dependence structure of the random field. We also provide solutions for several non-standard prediction problems which deals with the "modified past," in which a finite number of observations are added to the past. These non-standard prediction problems are motivated by the network site selection in the environmental and geostatistical applications. Unlike the time series situation, the prediction results for random fields seem to be expressible only in terms of the moving average parameters, and attempts to express them in terms of the autoregressive parameters lead to a new and mysterious projection operator which captures the nature of edge-effects. We put forward an approach for estimating the predictor coefficients by carrying out an extension of the exponential models. Through simulation studies and real data example, we demonstrate the impressive performance of our prediction method. To the best of our knowledge, the proposed method is the first to deliver a unified framework for forecasting random fields both in the time and spectral domain without making a subjective choice of the covariance structure. Finally, we focus on the estimation of the hurst parameter for long range dependence stationary random fields, which draws its motivation from applications in the environmental and atmospheric processes. Current methods for estimation of the Hurst parameter include parametric models like fractional autoregressive integrated moving average models, and semiparametric estimators which are either inefficient or inconsistent. We propose a novel semiparametric estimator based on the fractional exponential spectrum. We develop three data-driven methods which can automatically select the optimal model order for the fractional exponential models. Extensive simulation studies and analysis of Mercer and Hall?s wheat data are used to illustrate the performance of the proposed estimator and model order selection criteria. The results show that our estimator outperforms existing estimators, including the GPH (Geweke and Porter-Hudak) estimator. We show that the proposed estimator is consistent, works for different definitions of long range dependent random fields, is computationally simple and is not susceptible to model misspecification or poor efficiency.

Detailed understanding of electron transfer reactions is important in many aspects of chemistry, biology and solar energy conversion. The main aim of this thesis is to provide further insight into electron transfer through highly conjugated bridge structures. Towards this end, three series of donor-acceptor dyads have been studied, all using an oligo(1,4-phenylene-ethynylene) moiety as the bridge. A common theme in these series is that they explore the effects of having either an ethynylene or phenylene as the attachment group between the bridge and the donor or acceptor. Photophysical characterization of these dyads was carried out by means of time resolved laser spectroscopy. The results show that having an ethynylene as attachment group results in higher rates for bridge mediated electron and energy transfer compared to similar systems, where a phenylene was used. It was also found that most of the investigated systems show a fast back electron transfer. A notable exception is a zinc(II) phthalocyanine- gold(III) porphyrin dyad, where very fast photoinduced electron transfer (kPET = 1.0×1012 s-1) was followed by relatively slow back electron transfer (kBET = 1.0×109 s-1). A complementary DFT investigation indicated that the charge shifted state involves a reduction of the gold ion, rather than the porphyrin ring. This results in lower electronic coupling between the reduced gold porphyrin and the bridge and thus slower back electron transfer. A series of zinc porphyrin platinum acetylide dyads was used to explore the effects on electronic coupling of different attachments points on the porphyrin ring. For the investigated system it was found that linking at the meso-position results in an eight-fold increase in electron transfer rate compared to the β-position. In addition, a series of mixed valence compounds was used to investigate electronic coupling mediated by cross-hyperconjugated or cross-π-conjugated bridges. The results indicate coupling elements of 100-400 cm-1, with the cross-π-conjugated bridge having the largest coupling. A complementary TD-DFT study indicates that both through bond and through space coupling can be active in these systems. The relative contribution of these two mechanisms to the electronic coupling is highly conformer dependent.

Thesis (Ph. D.)--University of California, San Diego, 2000. / Vita. Includes bibliographical references.

Thesis (M.Sc.(Meteorology))--University of Pretoria, 2008. / Summary in English. Includes bibliographical references.

Thesis (Ph. D.)--Rijksuniversiteit te Utrecht, 1946. / Vita. Summary in Dutch. Includes bibliographical references.

The thesis is made up of a number of studies involving long-range dependence (LRD), that is, a slow power-law decay in the temporal correlation of stochastic models. Such a phenomenon has been frequently observed in practice. The models with LRD often yield non-standard probabilistic and statistical results. The thesis includes in particular the following topics: Multivariate limit theorems. We consider a vector made of stationary sequences, some components of which have LRD, while the others do not. We show that the joint scaling limits of the vector exhibit an asymptotic independence property. Non-central limit theorems. We introduce new classes of stationary models with LRD through Volterra-type nonlinear filters of white noise. The scaling limits of the sum lead to a rich class of non-Gaussian stochastic processes defined by multiple stochastic integrals. Limit theorems for quadratic forms. We consider continuous-time quadratic forms involving continuous-time linear processes with LRD. We show that the scaling limit of such quadratic forms depends on both the strength of LRD and the decaying rate of the quadratic coefficient. Behavior of the generalized Rosenblatt process. The generalized Rosenblatt process arises from scaling limits under LRD. We study the behavior of this process as its two critical parameters approach the boundaries of the defining region. Inference using self-normalization and resampling. We introduce a procedure called "self-normalized block sampling" for the inference of the mean of stationary time series. It provides a unified approach to time series with or without LRD, as well as with or without heavy tails. The asymptotic validity of the procedure is established.