Generalized modal identification of linear and nonlinear dynamic systems

This dissertation is concerned with the problem of determining the dynamic characteristics of complicated engineering systems and structures from the measurements made during dynamic tests or natural excitations. Particular attention is given to the identification and modeling of the behavior of structural dynamic systems in the nonlinear hysteretic response regime. Once a model for the system has been identified, it is intended to use this model to assess the condition of the system and to predict the response to future excitations.

A new identification methodology based upon a generalization of the method of modal identification for multi-degree-of-freedom dynaimcal systems subjected to base motion is developed. The situation considered herein is that in which only the base input and the response of a small number of degrees-of-freedom of the system are measured. In this method, called the generalized modal identification method, the response is separated into "modes" which are analogous to those of a linear system. Both parametric and nonparametric models can be employed to extract the unknown nature, hysteretic or nonhysteretic, of the generalized restoring force for each mode.

In this study, a simple four-term nonparametric model is used first to provide a nonhysteretic estimate of the nonlinear stiffness and energy dissipation behavior. To extract the hysteretic nature of nonlinear systems, a two-parameter distributed element model is then employed. This model exploits the results of the nonparametric identification as an initial estimate for the model parameters. This approach greatly improves the convergence of the subsequent optimization process.

The capability of the new method is verified using simulated response data from a three-degree-of-freedom system. The new method is also applied to the analysis of response data obtained from the U.S.-Japan cooperative pseudo-dynamic test of a full-scale six-story steel-frame structure.

The new system identification method described has been found to be both accurate and computationally efficient. It is believed that it will provide a useful tool for the analysis of structural response data.

Isotopic proxies for microbial and environmental change : insights hydrogen isotopes and the Ediacaran Khufai Formation

Microbes have profoundly influenced the Earth’s environments through time. Records of these interactions come primarily from the development and implementation of proxies that relate known modern processes to chemical signatures in the sedimentary record. This thesis is presented in two parts, focusing first on novel proxy development in the modern and second on interpretation of past environments using well-established methods. Part 1, presented in two chapters, builds on previous observations that different microbial metabolisms produce vastly different lipid hydrogen isotopic compositions. Chapter 1 evaluates the potential environmental expression of metabolism-based fractionation differences by exploiting the natural microbial community gradients in hydrothermal springs. We find a very large range in isotopic composition that can be demonstrably linked to the microbial source(s) of the fatty acids at each sample site. In Chapter 2, anaerobic culturing techniques are used to evaluate the hydrogen isotopic fractionations produced by anaerobic microbial metabolisms. Although the observed fractionation patterns are similar to those reported for aerobic cultures for some organisms, others show large differences. Part 2 changes focus from the modern to the ancient and uses classical stratigraphic methods combined with isotope stratigraphy to interpret microbial and environmental changes during the latest Precambrian Era. Chapter 3 presents a detailed characterization of the facies, parasequence development, and stratigraphic architecture of the Ediacaran Khufai Formation. Chapter 4 presents measurements of carbon, oxygen, and sulfur isotopic ratios in stratigraphic context. Large oscillations in the isotopic composition of sulfate constrain the size of the marine sulfate reservoir and suggest incorporation of an enriched isotopic source. Because this data was measured in stratigraphic context, we can assert with confidence that these isotopic shifts are not related to stratigraphic surfaces or facies type but instead reflect the evolution of the ocean through time. This data integrates into the chemostratigraphic global record and contributes to the emerging picture of changing marine chemistry during the latest Precambrian Era.

The Role of Fucose in Learning and Memory: The Identification of a Fucosylprotein, Synapsin I, in the Rat Brain and the Characterization of its Fucosylation

Previous studies have shown that the glycoproteins containing the fucose moiety are involved in neuronal communication phenomena such as long-term potentiation and memory formation. These results imply that fucose containing glycoproteins might play an important role in learning and memory. To understand the role of fucose in neuronal communication, and the mechanisms by which fucose may be involved in information storage, the identification of fucosylproteins is essential. This report describes the identification and characterization of fucosylproteins in the brain, which will provide new insights into the role of the fucose involved molecular interactions.

Sulfur-Cycling in Methane-Rich Ecosystems: Uncovering Microbial Processes and Novel Niches

Microbial sulfur cycling communities were investigated in two methane-rich ecosystems, terrestrial mud volcanoes (TMVs) and marine methane seeps, in order to investigate niches and processes that would likely be central to the functioning of these crucial ecosystems. Terrestrial mud volcanoes represent geochemically diverse habitats with varying sulfur sources and yet sulfur-cycling in these environments remains largely unexplored. Here we characterized the sulfur-metabolizing microorganisms and activity in 4 TMVs in Azerbaijan, supporting the presence of active sulfur-oxidizing and sulfate-reducing guilds in all 4 TMVs across a range of physiochemical conditions, with diversity of these guilds being unique to each TMV. We also found evidence for the anaerobic oxidation of methane coupled to sulfate reduction, a process which we explored further in the more tractable marine methane seeps. Diverse associations between methanotrophic archaea (ANME) and sulfate-reducing bacterial groups (SRB) often co-occur in marine methane seeps, however the ecophysiology of these different symbiotic associations has not been examined. Using a combination of molecular, geochemical and fluorescence in situ hybridization coupled to nano-scale secondary ion mass spectrometry (FISH-NanoSIMS) analyses of in situ seep sediments and methane-amended sediment incubations from diverse locations, we show that the unexplained diversity in SRB associated with ANME cells can be at least partially explained by preferential nitrate utilization by one particular partner, the seepDBB. This discovery reveals that nitrate is likely an important factor in community structuring and diversity in marine methane seep ecosystems. The thesis concludes with a study of the dynamics between ANME and their associated SRB partners. We inhibited sulfate reduction and followed the metabolic processes of the community as well as the effect of ANME/SRB aggregate composition and growth on a cellular level by tracking 15N substrate incorporation into biomass using FISH-NanoSIMS. We revealed that while sulfate-reducing bacteria gradually disappeared over time in incubations with an SRB inhibitor, the ANME archaea persisted in the form of ANME-only aggregates, which are capable of little to no growth when sulfate reduction is inhibited. These data suggest ANME are not able to synthesize new proteins when sulfate reduction is inhibited.

Identification of fucose-α(1-2)-galactose binding proteins in the mammalian brain

Fucose-α(1-2)-galactose (Fucα(1-2)Gal) carbohydrates have been implicated in cognitive functions. However, the underlying molecular mechanisms that govern these processes are not well understood. While significant progress has been made toward identifying glycoconjugates bearing this carbohydrate epitope, a major challenge remains the discovery of interactions mediated by these sugars. Here, we employ the use of multivalent glycopolymers to enable the proteomic identification of weak affinity, low abundant Fucα(1-2)Gal-binding proteins (i.e. lectins) from the brain. End-biotinylated glycopolymers containing photoactivatable crosslinkers were used to capture and enrich potential Fucα(1-2)Gal-specific lectins from rat brain lysates. Candidate lectins were tested for their ability to bind Fucα(1-2)Gal, and the functional significance of the interaction was investigated for one such candidate, SV2a, using a knock-out mouse system. Our results suggest an important role for this glycan-lectin interaction in facilitating synaptic changes necessary for neuronal communication. This study highlights the use of glycopolymer mimetics to discover novel lectins and identify functional interactions between fucosyl carbohydrates and lectins in the brain.

Identification of thermally-tagged coherent structures in the zero pressure gradient turbulent boundary layer

A zero pressure gradient boundary layer over a flat plate is subjected to step changes in thermal condition at the wall, causing the formation of internal, heated layers. The resulting temperature fluctuations and their corresponding density variations are associated with turbulent coherent structures. Aero-optical distortion occurs when light passes through the boundary layer, encountering the changing index of refraction resulting from the density variations. Instantaneous measurements of streamwise velocity, temperature and the optical deflection angle experienced by a laser traversing the boundary layer are made using hot and cold wires and a Malley probe, respectively. Correlations of the deflection angle with the temperature and velocity records suggest that the dominant contribution to the deflection angle comes from thermally-tagged structures in the outer boundary layer with a convective velocity of approximately 0.8U∞. An examination of instantaneous temperature and velocity and their temporal gradients conditionally averaged around significant optical deflections shows behavior consistent with the passage of a heated vortex. Strong deflections are associated with strong negative temperature gradients, and strong positive velocity gradients where the sign of the streamwise velocity fluctuation changes. The power density spectrum of the optical deflections reveals associated structure size to be on the order of the boundary layer thickness. A comparison to the temperature and velocity spectra suggests that the responsible structures are smaller vortices in the outer boundary layer as opposed to larger scale motions. Notable differences between the power density spectra of the optical deflections and the temperature remain unresolved due to the low frequency response of the cold wire.

From lakes to lungs : assessing microbial activity in diverse environments

All major geochemical cycles on the Earth’s surface are mediated by microorganisms. Our understanding of how these microbes have interacted with their environments (and vice versa) throughout Earth's history, and how they will respond to changes in the future, is primarily based on studying their activity in different environments today. The overarching questions that motivate the research presented in the two parts of this thesis -- how do microorganisms shape their environment (and vice versa)? and how can we best study microbial activity in situ? -- have arisen from the ultimate goal of being able to predict microbial activity in response to changes within their environments both past and future.

Part one focuses on work related to microbial processes in iron-rich Lake Matano and, more broadly, microbial interactions with the biogeochemical cycling of iron. Primarily, we find that the chelation of ferrous iron by organic ligands can affect the role of iron in anoxic environmental systems, enabling photomixotrophic growth of anoxygenic microorganisms with ferrous iron, as well as catalyzing the oxidation of ferrous iron by denitrification intermediates. These results imply that the ability to grow photomixotrophically on ferrous iron might be more widespread than previously assumed, and that the co-occurrence of chemical and biological processes involved in the coupled biogeochemical cycling of iron and nitrogen likely dominate organic-rich environmental systems.

Part two switches focus to in situ measurements of growth activity and comprises work related to microbial processes in the Cystic Fibrosis lung, and more broadly, the physiology of slow growth. We introduce stable isotope labeling of microbial membrane fatty acids and whole cells with heavy water as a new technique to measure microbial activity in a wide range of environments, demonstrate its application in continuous culture in the laboratory at the population and single cell level, and apply the tool to measure the in situ activity of the opportunistic pathogen Staphylococcus aureus within the environment of expectorated mucus from cystic fibrosis patients. We find that the average in situ growth rates of S. aureus fall into a range of generation times between ~12 hours and ~4 days, with substantial heterogeneity at the single-cell level. These data illustrate the use of heavy water as a universal environmental tracer for microbial activity, and highlight the crucial importance of studying the physiology of slow growth in representative laboratory systems in order to understand the role of these microorganisms in their native environments.

Physical, Metabolic, and Energetic Investigations of Methane-Metabolizing Microbial Communities

Understanding the roles of microorganisms in environmental settings by linking phylogenetic identity to metabolic function is a key challenge in delineating their broad-scale impact and functional diversity throughout the biosphere. This work addresses and extends such questions in the context of marine methane seeps, which represent globally relevant conduits for an important greenhouse gas. Through the application and development of a range of culture-independent tools, novel habitats for methanotrophic microbial communities were identified, established settings were characterized in new ways, and potential past conditions amenable to methane-based metabolism were proposed. Biomass abundance and metabolic activity measures – both catabolic and anabolic – demonstrated that authigenic carbonates associated with seep environments retain methanotrophic activity, not only within high-flow seep settings but also in adjacent locations exhibiting no visual evidence of chemosynthetic communities. Across this newly extended habitat, microbial diversity surveys revealed archaeal assemblages that were shaped primarily by seepage activity level and bacterial assemblages influenced more substantially by physical substrate type. In order to reliably measure methane consumption rates in these and other methanotrophic settings, a novel method was developed that traces deuterium atoms from the methane substrate into aqueous medium and uses empirically established scaling factors linked to radiotracer rate techniques to arrive at absolute methane consumption values. Stable isotope probing metaproteomic investigations exposed an array of functional diversity both within and beyond methane oxidation- and sulfate reduction-linked metabolisms, identifying components of each proposed enzyme in both pathways. A core set of commonly occurring unannotated protein products was identified as promising targets for future biochemical investigation. Physicochemical and energetic principles governing anaerobic methane oxidation were incorporated into a reaction transport model that was applied to putative settings on ancient Mars. Many conditions enabled exergonic model reactions, marking the metabolism and its attendant biomarkers as potentially promising targets for future astrobiological investigations. This set of inter-related investigations targeting methane metabolism extends the known and potential habitat of methanotrophic microbial communities and provides a more detailed understanding of their activity and functional diversity.

Identification and characterization of the egg-laying hormone from the neurosecretary bag cells of Aplysia

This investigation has resulted in the chemical identification and isolation of the egg-laying hormone from Aplysia californica, Aplysia vaccaria, and Aplysia dactylomela. The hormone, which was originally identified as the Bag Cell-Specific protein (BCS protein) on polyacrylamide gels, is a polypeptide of molecular weight ≈ 6000, which is localized in the neurosecretory bag cells of the parietovisceral ganglion and the surrounding connective tissue sheath which contains the bag cell axons. All three species produce a hormone of similar molecular weight, but varying electrophoretic mobility as determined on polyacrylamide gels. As tested, the hormone is completely cross-reactive among the three species.

Although the bag cells of sexually immature animals contain the active hormone, sexual maturation of the animal results in a 10-fold increase in the BCS protein content of these neurons.

A seasonal variation in the BCS protein content was also observed, with 150 times more hormone contained in the bag cells of Aplysia californica in August than in January. This correlates well with the variation in the animals' ability to lay eggs throughout the year (Strumwasser et al., 1969). There are some indications that the receptivity of the animal to the available hormone also fluctuates during the year, being lower in winter than in swmner. The seasonal rhythm of the other species, Aplysia vaccaria and Aplysia dactylomela, has not been investigated.

A polyacrylamide gel electrophoresis analysis of water-soluble proteins in Aplysia californica revealed several other nerve-specific proteins. One of these is also located in the bag cell somas and stains turquoise with Amido Schwarz. The function of this protein has not been investigated.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.