Browsing by Subject "Nonlinear dynamics"

This thesis describes the theoretical and experimental investigations on a non-smooth impacting system consisting of a forced oscillating mass with an impacting barrier, which has the ability to impart energy into the vibrating system. The system is also forced by the means of a sinusoidal excitation using a scotch yoke mechanism. Experiments are conducted to obtain the time delay state-space, time series and Poincare sections. Bifurcation diagrams are obtained by conducting forward and reverse frequency sweep. The obtained results are compared with expected linear non-impacting behavior and interesting phenomena including hysteresis, multiple-period orbits, transient and sustained chaos are observed. Numerical simulations were conducted and correlations were obtained between the theoretical and experimental results.

Coherent, large-scale shapes and patterns are evident in many landscapes, and evolve according to climate and hydrological forces. For large-scale, sandy coastlines, these shapes depend on wave climate forcing. The wave climate is influenced by storm patterns, which are expected to change with the warming climate, and the associated changes in coastline shape are likely to increase rates of shoreline change in many places. Humans have historically responded to coastline change by manipulating various coastal processes, consequently affecting long-term, large-scale coastline shape change. Especially in the context of changing climate forcing and increasing human presence on the coast, the interaction of the human and climate-driven components of large-scale coastline evolution are becoming increasingly intertwined.

This dissertation explores how climate shapes coastlines, and how the effects of humans altering the landscape interact with the effects of a changing climate. Because the coastline is a spatially extended, nonlinear system, I use a simple numerical modeling approach to gain a basic theoretical understanding of its dynamics, incorporating simplified representations of the human components of coastline change in a previously developed model for the physical system.

Chapter 1 addresses how local shoreline stabilization affects the large scale morphology of a cuspate-cape type of coastline, and associated large-scale patterns of shoreline change, in the context of changing wave climate, comparing two fundamentally different approaches to shoreline stabilization: beach nourishment (in which sediment is added to a coastline at a long-term rate that counteracts the background erosion), and hard structures (including seawalls and groynes). The results show that although both approaches have surprisingly long-range effects with spatially heterogeneous distributions, the pattern of shoreline changes attributable to a single local stabilization effort contrast greatly, with nourishment producing less erosion when the stabilization-related shoreline change is summed alongshore.

Chapter 2 presents new basic understanding of the dynamics that produce a contrasting coastline type: convex headland-spit systems. Results show that the coastline shapes and spatially-uniform erosion rates emerge from two way influences between the headland and spit components, and how these interactions are mediated by wave climate, and the alongshore scale of the system. Chapter 2 also shows that one type of wave-climate change (altering the proportion of `high-angle' waves) leads to changes in coastline shape, while another type (altering wave-climate asymmetry) tends to reorient a coastline while preserving its shape.

Chapter 3 builds on chapter 2, by adding the effects of human shoreline stabilization along such a convex coastline. Results show that in the context of increasing costs for stabilization, abandonment of shoreline stabilization at one location triggers a cascade of abandonments and associated coastline-shape changes, and that both the qualitative spatial patterns and alongshore speed of the propagating cascades depends on the relationship between patterns of economic heterogeneity and the asymmetry of the wave-climate change--although alterations to the proportion of high-angle waves in the climate only affects the time scales for coupled morphologic/economic cascades.

In a variety of physical systems, slow driving produces self-similar intermittent dynamics known as crackling noise. Barkhausen noise in ferromagnets, acoustic emission in fracture, seismic activities and failure in sheared granular media are few examples of crackling dynamics with substantial differences at the microscopic scale but similar universal laws. In many of the crackling systems, the origin of this universality and the connection between microscopic and macroscopic scales are subjects of current investigations.

We perform experiments to study the microscopic and macroscopic dynamics of a sheared granular medium. In our experiments, a constant speed stage pulls a slider with a loading spring across a 2D granular medium. We measure the pulling force on the spring, and image the medium to extract the local stress and particle displacement. Using novel signal and image analysis methods, we identify fast energy dissipating events, i.e.\ avalanches, and investigate their statistics and dynamics.

The pulling force exhibits crackling dynamics for low driving rates with intermittent slip avalanches. The energy loss in the spring has a power-law distribution with an exponent that strongly depends on the driving rate and is different from $-1.5$ predicted by several models. In our experiments for low driving rate, we find a slip rate power-spectrum of form $\mathcal{P}_v(\omega) \sim \frac{\omega^2}{1+\omega^{2.4}}$, a power-law distribution of the slip rate $P(v) \sim v^{-2.9}$, and average temporal profile of the slider motion (avalanche shape) of form $\mathcal{P}_D(u)=[u(1-u)]^{1.09}$. These findings are different from several theoretical and numerical studies \citep{dahmen2011simple, colaiori2008exactly, Laurson13_natcom}.

Avalanche temporal correlation is also investigated using certain conditional probabilities. At low driving rates, we observe uncorrelated order of the avalanches in terms of Omori-Utsu and B\r{a}th laws and temporal correlation in terms of the waiting time law. At higher driving rates, where the sequence of slip avalanches shows strong periodicity, we observe scaling laws and asymmetrical avalanche shapes that are clearly distinguishable from those in the crackling regime. We provide a novel dynamic phase diagram of granular matter as a function of driving rate and stiffness and characterize the crackling to periodic transition. We also find intermittent fluctuations in internal stress both in the crackling and the periodic regime.

Finally, we observe a narrow shear band with most of particle displacements, but stress fluctuations all over the medium. We identify the spatio-temporal connected components of local stress drops, which we call local avalanches. We find power-law distributions of the local avalanches with an exponent of $-1.7 \pm 0.1$, different from spring energy avalanche distribution with an exponent of $-0.41 \pm 0.05$ for the same experiments.

Our study constrains theoretical frameworks for granular dynamics and crackling noise in sheared granular media. Moreover, it may be relevant for characterizing the role of granular matter in fault gouges during seismic events.

This paper investigates the static and dynamic characteristics of the semi-elliptical rocking disk on which a pendulum pinned. This coupled system’s response is also analyzed analytically and numerically when a vertical harmonic excitation is applied to the bottom of the rocking disk. Lagrange’s Equation is used to derive the motion equations of the disk-pendulum coupled system. The second derivative test for the system’s potential energy shows how the location of the pendulum’s pivotal point affects the number and stability of equilibria, and the change of location presents different bifurcation diagrams for different geometries of the rocking disk. For both vertically excited and unforced cases, the coupled system shows chaos easily, but the proper chosen parameters can still help the system reach and keep the steady state. For the steady state of the vertically excited rocking disk without a pendulum, the variation of the excitation’s amplitude and frequency result in the hysteresis for the amplitude of the response. When a pendulum is pinned on the rocking disk, three major categories of steady states are presently in the numerical way.

One of the key mechanisms that mediate renal autoregulation is the tubuloglomerular feedback (TGF) system, which is a negative feedback loop in the kidney that balances glomerular filtration with tubular reabsorptive capacity. In this dissertation, we develop several mathematical models of the TGF system to study TGF-mediated model dynamics.

First, we develop a mathematical model of compliant thick ascending limb (TAL) of a short loop of Henle in the rat kidney, called TAL model, to investigate the effects of spatial inhomogeneous properties in TAL on TGF-mediated dynamics. We derive a characteristic equation that corresponds to a linearized TAL model, and conduct a bifurcation analysis by finding roots of that equation. Results of the bifurcation analysis are also validated via numerical simulations of the full model equations.

We then extend the TAL model to explicitly represent an entire short-looped nephron including the descending segments and having compliant tubular walls, developing a short-looped nephron model. A bifurcation analysis for the TGF loop-model equations is similarly performed by computing parameter boundaries, as functions of TGF gain and delay, that separate differing model behaviors. We also use the loop model to better understand the effects of transient as well as sustained flow perturbations on the TGF system and on distal NaCl delivery.

To understand the impacts of internephron coupling on TGF dynamics, we further develop a mathematical model of a coupled-TGF system that includes any finite number of nephrons coupled through their TGF systems, coupled-nephron model. Each model nephron represents a short loop of Henle having compliant tubular walls, based on the short-looped nephron model, and is assumed to interact with nearby nephrons through electrotonic signaling along the pre-glomerular vasculature. The characteristic equation is obtained via linearization of the loop-model equations as in TAL model. To better understand the impacts of parameter variability on TGF-mediated dynamics, we consider special cases where the relation between TGF delays and gains among two coupled nephrons is specifically chosen. By solving the characteristic equation, we determine parameter regions that correspond to qualitatively differing model behaviors.

TGF delays play an essential role in determining qualitatively and quantitatively different TGF-mediated dynamic behaviors. In particular, when noise arising from external sources of system is introduced, the dynamics may become significantly rich and complex, revealing a variety of model behaviors owing to the interaction with delays. In our next study, we consider the effect of the interactions between time delays and noise, by developing a stochastic model. We begin with a simple time-delayed transport equation to represent the dynamics of chloride concentration in the rigid-TAL fluid. Guided by a proof for the existence and uniqueness of the steady-state solution to the deterministic Dirichlet problem, obtained via bifurcation analysis and the contraction mapping theorem, an analogous proof for stochastic system with random boundary conditions is presented. Finally we conduct multiscale analysis to study the effect of the noise, specifically when the system is in subcritical region, but close enough to the critical delay. To analyze the solution behaviors in long time scales, reduced equations for the amplitude of solutions are derived using multiscale method.

There is a growing interest among aeroelasticity researchers for insight into large deflection oscillations of aerospace structures. Here, a new beam and plate model is derived using Hamilton's Principle to lay the structural framework for a nonlinear, large deflection aeroelastic model. Two boundary conditions of the beam are explored: cantilevered and free-free. For a plate, the cantilevered boundary condition is considered. In these conditions, the nonlinearity stems from the structure's large curvature rather than from stretching. Therefore, this model makes use of the simplifying assumption that the the structure has no strain along the midplane; thus the model is ``inextensible." Insight into the nonlinearity of this system is gained by applying harmonic loads to the structure, and stability conditions are also investigated by applying nonconservative follower loads.

Upon validating the structural model, the model is then coupled with aerodynamic models to form new, nonlinear aeroelastic models. Using classical aeroelasticity tools such as Piston Theory to model aerodynamic forces on the largely deflected cantilever, new insights are gained into the stability behavior of the system, the post-flutter behavior of the system, and the utility of these classic techniques with these novel configurations. With the large deflection cases, several novel nonlinearities are introduced, and it is shown that the systems are highly sensitive to the inclusion of these nonlinearities. Of course these classical aerodynamic theories are derived assuming small deflections, so attention is given to ensure that the Classical Piston Thoery is applicable in the current configurations. Also a new aerodynamic theory is proposed for pressures on structures undergoing large deflections. In total, this document proposes and explores new methodologies for modeling aeroelastic structures which tend to undergo large elastic deformations.

The physics of complex systems has grown considerably as a field in recent decades, largely due to improved computational technology and increased availability of systems level data. One area in which physics is of growing relevance is molecular biology. A new field, systems biology, investigates features of biological systems as a whole, a strategy of particular importance for understanding emergent properties that result from a complex network of interactions. Due to the complicated nature of the systems under study, the physics of complex systems has a significant role to play in elucidating the collective behavior.

In this dissertation, we explore three problems in the physics of complex systems, motivated in part by systems biology. The first of these concerns the applicability of Boolean models as an approximation of continuous systems. Studies of gene regulatory networks have employed both continuous and Boolean models to analyze the system dynamics, and the two have been found produce similar results in the cases analyzed. We ask whether or not Boolean models can generically reproduce the qualitative attractor dynamics of networks of continuously valued elements. Using a combination of analytical techniques and numerical simulations, we find that continuous networks exhibit two effects -- an asymmetry between on and off states, and a decaying memory of events in each element's inputs -- that are absent from synchronously updated Boolean models. We show that in simple loops these effects produce exactly the attractors that one would predict with an analysis of the stability of Boolean attractors, but in slightly more complicated topologies, they can destabilize solutions that are stable in the Boolean approximation, and can stabilize new attractors.

Second, we investigate ensembles of large, random networks. Of particular interest is the transition between ordered and disordered dynamics, which is well characterized in Boolean systems. Networks at the transition point, called critical, exhibit many of the features of regulatory networks, and recent studies suggest that some specific regulatory networks are indeed near-critical. We ask whether certain statistical measures of the ensemble behavior of large continuous networks are reproduced by Boolean models. We find that, in spite of the lack of correspondence between attractors observed in smaller systems, the statistical characterization given by the continuous and Boolean models show close agreement, and the transition between order and disorder known in Boolean systems can occur in continuous systems as well. One effect that is not present in Boolean systems, the failure of information to propagate down chains of elements of arbitrary length, is present in a class of continuous networks. In these systems, a modified Boolean theory that takes into account the collective effect of propagation failure on chains throughout the network gives a good description of the observed behavior. We find that propagation failure pushes the system toward greater order, resulting in a partial or complete suppression of the disordered phase.

Finally, we explore a dynamical process of direct biological relevance: asymmetric cell division in A. thaliana. The long term goal is to develop a model for the process that accurately accounts for both wild type and mutant behavior. To contribute to this endeavor, we use confocal microscopy to image roots in a SHORTROOT inducible mutant. We compute correlation functions between the locations of asymmetrically divided cells, and we construct stochastic models based on a few simple assumptions that accurately predict the non-zero correlations. Our result shows that intracellular processes alone cannot be responsible for the observed divisions, and that an intercell signaling mechanism could account for the measured correlations.

Rolling Isolation Systems provide a simple and effective means for protecting components from horizontal floor vibrations. In these systems a platform rolls on four steel balls which, in turn, rest within shallow bowls. The trajectories of the balls is uniquely determined by the horizontal and rotational velocity components of the rolling platform, and thus provides nonholonomic constraints. In general, the bowls are not parabolic, so the potential energy function of this system is not quadratic. This thesis presents the application of Gauss's Principle of Least Constraint to the modeling of rolling isolation platforms. The equations of motion are described in terms of a redundant set of constrained coordinates. Coordinate accelerations are uniquely determined at any point in time via Gauss's Principle by solving a linearly constrained quadratic minimization. In the absence of any modeled damping, the equations of motion conserve energy. This mathematical model is then used to find the bowl profile that minimizes response acceleration subject to displacement constraint.

The primary focus of this dissertation is the characterization of snap-through buckling of discrete and continuous systems. Snap-through buckling occurs as the consequence of two factors, first the destabilization, or more often the disappearance of, an equilibrium position under the change of a system parameter, and second the existence of another stable equilibrium configuration at a remote location in state space. In this sense snap-through buckling is a global dynamic transition as the result of a local static instability.

In order to better understand the static instabilities that lead to snap-through buckling, the behavior of mechanical systems in the vicinity of various local bifurcations is first investigated. Oscillators with saddle-node, pitchfork, and transcritical bifurcations are shown analytically to exhibit several interesting characteristics, particularly in relation to the system damping ratio. A simple mechanical oscillator with a transcritical bifurcation is used to experimentally verify the analytical results. The transcritical bifurcation was selected since it may be used to represent generic bifurcation behavior. It is shown that the damping ratio may be used to predict changes in stability with respect to changing system parameters.

Another useful indicator of snap-through is the presence of chaos in the dynamic response of a system. Chaos is usually associated snap-through, as in many systems large amplitude responses are typically necessary to sufficiently engage the nonlinearities that induce chaos. Thus, a pragmatic approach for identifying chaos in experimental (and hence noisy) systems is also developed. The method is applied to multiple experimental systems showing good agreement with identification via Lyapunov exponents.

Under dynamic loading, systems with the requisite condition for snap-through buckling, that is co-existing equilibria, typically exhibit either small amplitude response about a single equilibrium configuration, or large amplitude response that transits between the static equilibria. Dynamic snap-through is the name given to the large amplitude response, which, in the context of structural systems, is obviously undesirable. This phenomenon is investigated using experimental, numerical, and analytical means and the boundaries separating safe (non-snap-through) from unsafe (snap-through) dynamic response in forcing parameter space are obtained for both a discrete and a continuous arch. Arches present an ideal avenue for the investigation of snap-through as they typically have multiple, often tunable, stable and unstable equilibria. They also have many direct applications in both civil engineering, where arches are a canonical structural element, and mechanical engineering, where arches may be used to approximate the behavior of curved plates and panels such as those used on aircraft.

Energy harvesting is a process where self-powered electronic devices scavenge ambient energy and convert it to electrical power. Traditional linear energy harvesters which operate based on linear resonance work well only when excitation frequency is close to its natural frequency. While various control methods applied to an energy harvester realize resonant frequency tuning, they are either energy-consuming or exhibit low efficiency when operating under multi-frequency excitations. In order to overcome these limitations in a linear energy harvester, researchers recently suggested using "nonlinearity" for broad-band frequency response.

Based on existing investigations of nonlinear energy harvesting, this dissertation introduced a novel type of energy harvester designs for space efficiency and intentional nonlinearity: translational-to-rotational conversion. Two dynamical systems were presented: 1) vertically forced rocking elliptical disks, and 2) non-contact magnetic transmission. Both systems realize the translational-to-rotational conversion and exhibit nonlinear behaviors which are beneficial to broad-band energy harvesting.

This dissertation also explores novel methods to overcome the limitation of nonlinear energy harvesting -- the presence of coexisting attractors. A control method was proposed to render a nonlinear harvesting system operating on the desired attractor. This method is based on reinforcement learning and proved to work with various control constraints and optimized energy consumption.

Apart from investigations of energy harvesting, several techniques were presented to improve the efficiency for analyzing generic linear/nonlinear dynamical systems: 1) an analytical method for stroboscopically sampling general periodic functions with arbitrary frequency sweep rates, and 2) a model-free sampling method for estimating basins of attraction using hybrid active learning.

The proper orthogonal decomposition (POD) is a classic method to construct empirical, linear modal bases which are optimal in a mean L2 sense. A subset of these modes can form the basis of a dynamical reduced-order model (ROM) of a physical system, including nonlinear, chaotic systems like fluid flows. While these POD-based ROMs can accurately simulate complex fluid dynamics, a priori model accuracy and stability estimates are unreliable. The work presented in this dissertation focuses on improving the predictability and accuracy of POD-based fluid ROMs. This is accomplished by ensuring several kinematically significant flow characteristics -- both at large scales and small -- are satisfied within the truncated bases. Several new methods of constructing and employing modal bases within this context are developed and tested. Reduced-order models of periodic flows are shown to be predictably accurate with high confidence; the predictable accuracy of quasi-periodic and chaotic fluid flow ROMs is increased significantly relative to existing approaches.

This study focuses on a series of data-driven methods to study nonlinear dynamic systems. First, a new method to estimate the location of unstable equilibria, specifically saddle-points, based on transient trajectories from experiments is proposed. We describe a system in which saddle-points (not easily observed in a direct sense) influence the behavior of trajectories that pass `close-by' them. This influence is used to construct a model and thus identify a more accurate estimate of the location using a number of refinements associated with linearization and regression. The method is verified on a rolling-ball model. Both simulations and experiments were conducted. The experiments consists of a small ball rolling on a relatively shallow curved surface under the influence of gravity: a potential energy surface in two dimensions. Tracking the motion of the ball with a digital camera provides data that compares closely with the output of numerical simulation. The experimental results suggest that this method can effectively locate the saddle equilibria in a system, and the robustness of the approach is assessed relative to the effect of noise, size of the local neighborhood, etc., in addition to providing information on the local dynamics. Given the relative simplicity of the experiment system used and a-priori knowledge of the saddle-points, it is a useful testing environment for system identification in a nonlinear context. Furthermore, a post-buckled beam model is used to test this method. Because in real world applications, continuous elastic structures are more common. The experiment results successfully capture both the stable and unstable configurations. However, the natural frequency provided by this regression method underestimates the natural frequency of the second mode. This is the result of low sampling rate in the experiment which leads to inaccurate estimation of velocity and acceleration from numerical differentiation. Simulation results from finite element method with higher sampling rate do not have this issue.

Then, a method to identify potential energy through probing a force field is presented. A small ball resting on a curve in a gravitational field offers a simple and compelling example of potential energy. The force required to move the ball, or to maintain it in a given position on a slope, is the negative of the vector gradient of the potential field: the steeper the curve, the greater the force required to push the ball up the hill (or keep it from rolling down). We thus observe the turning points (horizontal tangency) of the potential energy shape as positions of equilibrium (in which case the 'restoring force' drops to zero). We appeal directly to this type of system using both one and two-dimensional shapes: curves and surfaces. The shapes are produced to a desired mathematical form generally using additive manufacturing, and we use a combination of load cells to measure the forces acting on a small steel ball-bearing subject to gravity. The measured forces, as a function of location, are then subject to integration to recover the potential energy function. The utility of this approach, in addition to pedagogical clarity, concerns extension and applications to more complex systems in which the potential energy would not be typically known {\it a priori}, for example, in nonlinear structural mechanics in which the potential energy changes under the influence of a control parameter, but there is the possibility of force {\it probing} the configuration space. A brief example of applying this approach to a 1-D simple elastic structure is also presented. For multi-dimensional continuous elastic systems, it would be hard to derive the whole potential energy field. However, it is possible to learn the potential energy difference between different equilibria. This information could help us learn the global stability of the stable equilibria, \textit{i.e.}, how much energy is required to escape from the stable equilibria.

Finally, a case study using the two above-mentioned methods on short square box columns is presented. This case study relies on simulation from the finite element method. The buckling of short square box column is dominated by the local buckling of the panel on each side of the column. Hence, the buckling of short box columns shares strong similarities with the buckling of a rectangular panel under uni-axial load. The primary, secondary and tertiary

bifurcation of a series of square box columns with different height-to-width ratio is presented. Then, we focus on the column with height-to-width ratio of 1.4142, in which the primary and second bifurcation would happen almost simultaneously. And thus, the differences in the energy level between different stable equilibria are important. The simulation results show that after the secondary bifurcation, the energy `well' depth for these stable equilibria are similar initially. With the further increase of buckling load, the energy well for the second mode is deeper and the second mode becomes the more stable configuration. We also study the dynamic snap-through of the post-buckled column. The regression method is used to estimate the equilibria configuration and the natural frequencies with great accuracy. We notice an interesting phenomenon, there can be an energy exchange between different sides of the box column and hence, the real parts of the eigenvalue of the Jacobian matrix are positive if we only take the shape of one surface into account, whereas, if we take two next surfaces into the regression method, the real parts become negative.

Multiterminal Josephson junctions have attracted attention, driven by the promise that they may host synthetic topological phase of matter and provide insight into Floquet states. Indeed, the added complexity of the additional contacts in multiterminal Josephson junctions greatly expands its parameter space, allowing for unexpected results. This work sheds light onto the out of equilibrium superconducting states that can exist within a ballistic multiterminal Josephson junction. The application of a microwave excitation produces unexpected fractional Shapiro steps, which are a consequence of the multiterminal circuit network. The application of a finite voltage reveals a robust cos 2φ supercurrent along the multiplet biasing condition nV1=-mV2. This supercurrent is found to be born from the RCSJ equations and has a stability condition analogous to Kapitza’s pendulum. Finally, the injection of hot carriers poisons supercurrent contributions from the Andreev spectrum, revealing a continuum mediated supercurrent.

This work is concerned with the dynamics and stability of nonlinear systems that roll in a single track, including holonomic and nonholonomic systems. First the classic case of Euler's disk is introduced as an example of a nonholnomic system in three dimensions, and the methodology for deriving equations of motion that is used throughout this work is demonstrated, including use of Lagrange's equations, accommodating constraints with both Lagrange multipliers and with Gauss's Principle.

Next, a disk in two dimensions with an eccentric center of mass is explored. The disk is assumed to roll on a cubic curve, creating the possibility of well-escape behavior, which is examined analytically and numerically, showing regions of multi-periodicity and chaos. This theoretical system is compared to an experiment designed

to demonstrate the same behavior.

The remainder of the present document is concerned with the stability of a bicycle, both on flat ground, and on a type of trainer known as "rollers." The equations of motion are derived using Lagrange's equations with nonholonomic constraints, then the equations are linearized about a constant forward velocity, and a straight path, yielding a two degree of freedom system for the roll and steer angles. Stability is then determined for a variety of different parameters, exploring the roll of bicycle geometry and rider position, along with the effect of adding a steering torque, taking the form of different control laws.

Finally, the system is adapted to that of a bicycle on rollers, and the related equations of motion are derived and linearized. Notable differences with the classic bicycle case are detailed, a new eigenvalue behavior is presented, and configurations for optimal drum spacing are recommended.

Computational simulations of a two-dimensional incompressible regularized lid-driven cavity were performed and analyzed to identify the dynamic behavior of the flow through multiple bifurcations which ultimately result in chaotic flow. Pseudo-spectral numerical simulations were performed at Reynolds numbers from 1,000 to 25,000. Traditional as well as novel methods were implemented to characterize the system's behavior. The first critical Reynolds number, near 10,250, is found in agreement with existing literature. An additional bifurcation is observed near a Reynolds number of 15,500. The largest Lyapunov exponent was studied as a potential perspective on chaos characterization but its accurate computation was found to be prohibitive. Phase space and power spectrum analyses yielded comparable conclusions about the flow's progression to chaos. The flow's transition from quasi-periodicity to chaos between Reynolds numbers of 18,000 and 23,000 was observed to be gradual and of the form of a toroidal bifurcation. The concepts of frequency shredding and power capacity are introduced which, paired with an existing understanding of frequency entrainment, can help explain the system's progression through quasi-periodicity to chaos.

Mechanical oscillators form the primary structure of a wide variety of devices including energy harvesters and vibration absorbers, and also have parallel systems in electrical fields for signal processing. In the area of wave propagation, recent study in periodic chains have focused on active tuning methods to control bandgap regions, bands in the frequency response in which no propagating wave modes exist. In energy harvesting, several coupled systems have been proposed to enhance the peak power or bandwidth of a single harvester through arrays or dynamic magnification. Though there are applications in several fields, the work in this dissertation can all fit into the category of coupled non-linear oscillators. In each sub-field, this study demonstrates means to advance state of the art techniques by adding nonlinearity to a coupled system of linear oscillators, or by adding a coupled device to a nonlinear oscillator.

The first part of this dissertation develops the analytical methods for studying wave propagation in nonlinear systems. A framework for studying rotational systems is presented and used to design an testbed for wave propagation experiments using a chain of axially aligned pendulums. Standard analytical methods are also adapted to allow uncertainty analysis techniques to provide insight into the relative impact of variations in design parameters. Most analytical insight in these systems is derived from a linearlized model and assumes low amplitude oscillations. Additional study on the nonlinear system is performed to analyze the types of deviations from this behavior that would be expected as amplitudes increase and nonlinear effects become more prominent.

The second part of this dissertation describes and demonstrates the first means of passive control of bandgap regions in a periodic structure. By imposing an asymmetrical bistability to an oscillator in each unit cell, it is analytically shown that each potential well has different wave propagation behaviors. Experimental demonstrations are also provided to confirm the simulated results.

The final section performs analytical and numerical analysis of a new system design to improve the performance of a nonlinear energy harvester by adding an excited dynamic magnifier. It is shown that this addition results in higher peak power and wider bandwidth than the uncoupled harvester. Unlike standard dynamic magnifiers, this performance does not come at the expense of power efficiency, and unlike harvester arrays, does not require the added cost of multiple energy harvesters.