A computational model is developed to investigate fundamental flow physics and transport phenomena of evaporating wavy-laminar falling liquid films of water and black liquor. The computational model is formulated from first principles based on the conservation laws for mass, momentum, energy and species in addition to a phase transport equation for capturing interface deformation and evolution. Free surface waves are generated by monochromatic perturbation of velocity. Continuum models for interfacial evaporation define source terms for liquid vaporization and species enrichment in the conservation laws. A phenomenological crystallization model is derived to account for species depletion due to salt precipitation during black liquor falling film evaporation. Using highly resolved numerical grids on parallel computers, the computational model is implemented to analyze the dynamics of capillary separation eddies in low Reynolds number falling films, investigate the dominant mechanisms of heat transfer enhancement in falling films at moderately high Reynolds numbers and study the fundamental wave structures and wave induced transport in black liquor falling films on flat and cylindrical walls. From simulation results, a theory based on the dynamics of wavefront streamwise pressure gradient is proposed to explain interfacial waves interaction that give rise to multiple backflow regions in films dominated by solitary-capillary waves. The study shows that the mechanism of heat transfer enhancement in moderately high Reynolds number films follows from relatively lower conduction thermal resistance and higher crosswise convective transport at newly formed intermediate wavefronts. Interfacial phenomena such as wave-breaking and vapor entrainment observed in black liquor falling films is explained in terms of a mechanistic theory based on evolution of secondary instabilities and large amplitude wave force imbalances.

Complex networks are employed as a mathematical description of complex systems in many different fields, ranging from biology to sociology, economy and ecology. Dynamical processes in these systems often display phase transitions, where the dynamics of the system changes qualitatively. In combination with these phase transitions certain components of the system might irretrievably go extinct. In this case, we talk about absorbing transitions. Developing mathematical tools, which allow for an analysis and prediction of the observed phase transitions is crucial for the investigation of complex networks. In this thesis, we investigate absorbing transitions in dynamical networks, where a certain amount of diversity is lost. In some real-world examples, e.g. in the evolution of human societies or of ecological systems, it is desirable to maintain a high degree of diversity, whereas in others, e.g. in epidemic spreading, the diversity of diseases is worthwhile to confine. An understanding of the underlying mechanisms for emergence and persistence of diversity in complex systems is therefore essential. Within the scope of two different network models, we develop an analytical approach, which can be used to estimate the prerequisites for diversity. In the first part, we study a model for opinion formation in human societies. In this model, regimes of low diversity and regimes of high diversity are separated by a fragmentation transition, where the network breaks into disconnected components, corresponding to different opinions. We propose an approach for the estimation of the fragmentation point. The approach is based on a linear stability analysis of the fragmented state close to the phase transition and yields much more accurate results compared to conventional methods. In the second part, we study a model for the formation of complex food webs. We calculate and analyze coexistence conditions for several types of species in ecological communities. To this aim, we employ an approach which involves an iterative stability analysis of the equilibrium with respect to the arrival of a new species. The proposed formalism allows for a direct calculation of coexistence ranges and thus facilitates a systematic analysis of persistence conditions for food webs. In summary, we present a general mathematical framework for the calculation of absorbing phase transitions in complex networks, which is based on concepts from percolation theory. While the specific implementation of the formalism differs from model to model, the basic principle remains applicable to a wide range of different models.

Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system\'s collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects\' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge. Moreover, we show what minimal microscopic interaction rules determine whether the transition to collective motion is continuous or discontinuous. Second, we consider a model of opinion formation in groups of individuals, where we focus on the effect of directed links in adaptive networks. Extending the adaptive voter model to directed networks, we find a novel fragmentation mechanism, by which the network breaks into distinct components of opposing agents. This fragmentation is mediated by the formation of self-stabilizing structures in the network, which do not occur in the undirected case. We find that they are related to degree correlations stemming from the interplay of link directionality and adaptive topological change. Third, we discuss a model for the evolution of cooperation among self-interested agents, in which the adaptive nature of their interaction network gives rise to a novel dynamical mechanism promoting cooperation. We show that even full cooperation can be achieved asymptotically if the networks\' adaptive response to the agents\' dynamics is sufficiently fast.

Untersuchungen zum statistischen Verhalten von Polymerketten auf anziehenden Oberflächen stellen ein spannendes Forschungsgebiet dar aufgrund des Wechselspiels zwischen dem Entropiegewinn bei Ablösung von der einschränkenden Oberfläche und dem Energiegewinn bei der Bildung von Oberflächenkontakten. Für gute und Theta-Lösungen und lange Ketten ist dieses Gebiet recht alt und gut verstanden, doch gibt es immer noch eine Reihe von offenen Fragen, insbesondere zu endlich langen Polymeren, die gerade im Zeitalter zunehmender Miniaturisierung und experimenteller Auflösung Klärung bedürfen, aber nicht zuletzt auch von prinzipiellem Interesse sind. Die vorliegende Arbeit beschäftigt sich mit dem Gleichgewichtsverhalten einer endlich langen Polymerkette in Lösung in der Nähe einer anziehenden Oberfläche. Die Anziehungsstärke wird dabei systematisch variiert und der Einfluss auf die Konformation des Homopolymers studiert. Dies geschieht im kanonischen und im mikrokanonischen Ensemble, die im betrachteten endlichen System nicht identisch sind. Da die Lösungsmittelstärke des selbstwechselwirkenden Polymers durch die Temperatur variiert werden kann, gelang so eine systematische Studie einer Reihe von Konformationsübergängen. Ob das Polymer an einem Ende irreversibel mit der Oberfläche verbunden ist oder sich zu einem gewissen Grad von ihr entfernen kann, spielt für insbesondere den Adsorptionsübergang eine Rolle, die untersucht wird. Anschließend wurde der Einfluss nicht homogener Oberflächenanziehung in Form von attraktiven Streifenpotentialen auf der Oberfläche auf die zuvor beschriebenen Konformationsübergänge studiert. Die Natur der so forcierten Mustererkennung konnte unter anderem abhängig von Streifenbreite und -stärke detailliert beleuchtet und mit dem Verhalten an homogenen Oberflächen in Bezug gesetzt werden. Sämtliche Daten wurden mit Monte-Carlo-Computersimulationen in generalisierten Ensemblen und einem Polymermodell, das atomare Details vernachlässigt, gewonnen.

Fundamental aspects of turbulence and turbulent mixing are investigated using direct numerical simulations (DNS) of stationary isotropic turbulence, with Taylor-scale Reynolds numbers ranging from 8 to 650 and Schmidt numbers from 1/8 to 1024. The primary emphasis is on important scaling issues that arise in the study of intermittency, mixing and turbulence under solid-body rotation. Simulations up to 2048^3 in size have been performed using large resource allocations on Terascale computers at leading supercomputing centers. Substantial efforts in algorithmic development have also been undertaken and resulted in a new code based on a two-dimensional domain decomposition which allows the use of very large number of processors.Benchmark tests indicate very good parallel performance for resolutions up to 4096^3 on up to 32768 processors. Investigation of intermittency through the statistics of dissipation and enstrophy in a series of simulations at the same Reynolds number but different resolution indicate that accurate results in high-order moments require a higher degree of fine-scale resolution than commonly practiced. At the highest Reynolds number in our simulations (400 and 650) dissipation and enstrophy exhibit extreme fluctuations of O(1000) the mean which have not been studied in the literature before and suggest a universal scaling of small scales. Simulations at Reynolds number of 650 on 2048^3 grids with scalars at Sc=1/8 and 1 have allowed us to obtain the clearest evidence of attainment of inertial-convective scaling in the scalar spectrum in numerical simulations to date whereas results at high Sc support k^{-1} viscous-convective scaling. Intermittency for scalars as measured by the tail of the PDF of scalar dissipation and moments of scalar gradient fluctuations is found to saturate at high Sc. Persistent departures from isotropy are observed as the Reynolds number increases. However, results suggest a return to isotropy at high Schmidt numbers, a tendency that appears to be stronger at high Reynolds numbers. The effects of the Coriolis force on turbulence under solid-body rotation are investigated using simulations on enlarged solution domains which reduce the effects of periodic boundary conditions.

Shock compaction experiments were performed on soft magnetic phases Fe₄N and Fe₁₆N₂, and hard magnetic phases Nd₂Fe₁₄B and Sm₂Fe₁₇N₃ in order to determine their thermo-mechanical stability during shock loading and explore the possibility of fabricating a textured nanocomposite magnet. Gas gun experiments performed on powders pressed in a three capsule fixture showed phase transformations occurring in Fe₄N, Fe₁₆N₂, and Nd₂Fe₁₄B, while Sm₂Fe₁₇N₃ was observed to be relatively stable. Shock compaction of FCC Fe₄N resulted in a partial transformation to HCP Fe₃N, consistent with previous reports of the transition occurring at a static pressure of ~3 GPa. Shock compaction of Fe₁₆N₂ produced decomposition products alpha-Fe, Fe₄N, and FeN due to a combination of thermal effects associated with dynamic void collapse and plastic deformation. Decomposition of Nd-Fe-B, producing alpha-Fe and amorphous Nd-Fe-B, was observed in several shock consolidated samples and is attributed to deformation associated with shock compaction, similar to decomposition reported in ball milled Nd-Fe-B. No decomposition was observed in shock compacted samples of Sm-Fe-N, which is consistent with literature reports showing decomposition occurring only in samples compacted at a pressure above ~15 GPa. Nd-Fe-B and Sm-Fe-N were shown to accommodate deformation primarily by grain size reduction, especially in large grained materials. Hard/Soft composite magnetic materials were formed by mixing single crystal particles of Nd-Fe-B with iron nanoparticles, and the alignment-by-magnetic-field technique was able to introduce significant texture into green compacts of this mixture. While problems with decomposition of the Nd₂Fe₁₄B phase prevented fabricating bulk magnets from the aligned green compacts, retention of the nanoscale morphology of the alpha-Fe particles and the high alignment of the green compacts shows promise for future development of textured nanocomposite magnets through shock compaction.

One of the most important design issues for phase change materials is to engineer the phase transition process. The challenge of accurately predicting a phase transition is estimating the true value of transition rate, which is determined by the saddle point with the minimum energy barrier between stable states on the potential energy surface (PES). In this thesis, a new algorithm for searching the minimum energy path (MEP) is presented. The new algorithm is able to locate both the saddle point and local minima simultaneously. Therefore no prior knowledge of the precise positions for the reactant and product on the PES is needed. Unlike existing pathway search methods, the algorithm is able to search multiple transition paths on the PES simultaneously, which gives us a more comprehensive view of the energy landscape than searching individual ones. In this method, a Bézier curve is used to represent each transition path. During the searching process, the reactant and product states are located by minimizing the two end control points of the curve, while the shape of the transition pathway is refined by moving the intermediate control points of the curve in the conjugate directions. A curve subdivision scheme is developed so that multiple transitions paths can be located. The algorithm is demonstrated by examples of LEPS potential, LEPS plus harmonic oscillator potential, and PESs defined by Rastrigin function and Schwefel function.

Many seemingly simple systems can display extraordinarily complex dynamics which has been studied and uncovered through nonlinear dynamical theory. The leitmotif of this thesis is changing phase-space structures and their (linear or nonlinear) stabilities by adding control functions (which act on the system as external perturbations) to the relevant Hamiltonians. These phase-space structures may be periodic orbits, invariant tori or their stable and unstable manifolds. One-electron systems and diatomic molecules are fundamental and important staging ground for new discoveries in nonlinear dynamics. In past years, increasing emphasis and effort has been put on the control or manipulation of these systems. Recent developments of nonlinear dynamical tools can provide efficient ways of doing so. In the first subtopic of the thesis, we are adding a control function to restore tori at prescribed locations in phase space. In the remainder of the thesis, a control function with parameters is used to change the linear stability of the periodic orbits which govern the processes in question. In this thesis, we report our theoretical analyses on multiphoton ionization of Rydberg atoms exposed to strong microwave fields and the dissociation of diatomic molecules exposed to bichromatic lasers using nonlinear dynamical tools. This thesis is composed of three subtopics. In the first subtopic, we employ local control theory to reduce the stochastic ionization of hydrogen atom in a strong microwave field by adding a relatively small control term to the original Hamiltonian. In the second subtopic, we perform periodic orbit analysis to investigate multiphoton ionization driven by a bichromatic microwave field. Our results show quantitative and qualitative agreement with previous studies, and hence identify the mechanism through which short periodic orbits organize the dynamics in multiphoton ionization. In addition, we achieve substantial time savings with this approach. In the third subtopic we extend our periodic orbit analysis to the dissociation of diatomic molecules driven by a bichromatic laser. In this problem, our results based on periodic orbit analysis again show good agreement with previous work, and hence promise more potential applications of this approach in molecular physics.

Drastic changes in aircraft operational requirements and the emergence of new enabling technologies often occur symbiotically with advances in technology inducing new requirements and vice versa. These changes sometimes lead to the design of vehicle concepts for which no prior art exists. They lead to revolutionary concepts. In such cases the basic form of the vehicle geometry can no longer be determined through an ex ante survey of prior art as depicted by aircraft concepts in the historical domain. Ideally, baseline geometries for revolutionary concepts would be the result of exhaustive configuration space exploration and optimization. Numerous component layouts and their implications for the minimum external dimensions of the resultant vehicle would be evaluated. The dimensions of the minimum enclosing envelope for the best component layout(s) (as per the design need) would then be used as a basis for the selection of a baseline geometry. Unfortunately layout design spaces are inherently large and the key contributing analysis i.e. collision detection, can be very expensive as well. Even when an appropriate baseline geometry has been identified, another hurdle i.e. vehicle scaling has to be overcome. Through the design of a notional Cessna C-172R powered by a liquid hydrogen Proton Exchange Membrane (PEM) fuel cell, it has been demonstrated that the various forms of vehicle scaling i.e. photographic and historical-data-based scaling can result in highly sub-optimal results even for very small O(10-3) scale factors. There is therefore a need for higher fidelity vehicle scaling laws especially since emergent technologies tend to be volumetrically and/or gravimetrically constrained when compared to incumbents. The Configuration-space Exploration and Scaling Methodology (CESM) is postulated herein as a solution to the above-mentioned challenges. This bottom-up methodology entails the representation of component or sub-system geometries as matrices of points in 3D space. These typically large matrices are reduced using minimal convex sets or convex hulls. This reduction leads to significant gains in collision detection speed at minimal approximation expense. (The Gilbert-Johnson-Keerthi algorithm is used for collision detection purposes in this methodology.) Once the components are laid out, their collective convex hull (from here on out referred to as the super-hull) is used to approximate the inner mold line of the minimum enclosing envelope of the vehicle concept. A sectional slicing algorithm is used to extract the sectional dimensions of this envelope. An offset is added to these dimensions in order to come up with the sectional fuselage dimensions. Once the lift and control surfaces are added, vehicle level objective functions can be evaluated and compared to other designs. For each design, changes in the super-hull dimensions in response to perturbations in requirements can be tracked and regressed to create custom geometric scaling laws. The regressions are based on dimensionally consistent parameter groups in order to come up with dimensionally consistent and thus physically meaningful laws. CESM enables the designer to maintain design freedom by portably carrying multiple designs deeper into the design process. Also since CESM is a bottom-up approach, all proposed baseline concepts are implicitly volumetrically feasible. Furthermore the scaling laws developed from custom data for each concept are subject to less design noise than say, regression based approaches. Through these laws, key physics-based characteristics of vehicle subsystems such as energy density can be mapped onto key system level metrics such as fuselage volume or take-off gross weight. These laws can then substitute some historical-data based analyses thereby improving the fidelity of the analyses and reducing design time.

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (p. [153]-167).