Three-dimensional models of mantle convection : influence of phase transitions and temperature-dependent viscosity

Two of the most important questions in mantle dynamics are investigated in three separate studies: the influence of phase transitions (studies 1 and 2), and the influence of temperature-dependent viscosity (study 3).

(1) Numerical modeling of mantle convection in a three-dimensional spherical shell incorporating the two major mantle phase transitions reveals an inherently three-dimensional flow pattern characterized by accumulation of cold downwellings above the 670 km discontinuity, and cylindrical 'avalanches' of upper mantle material into the lower mantle. The exothermic phase transition at 400 km depth reduces the degree of layering. A region of strongly-depressed temperature occurs at the base of the mantle. The temperature field is strongly modulated by this partial layering, both locally and in globally-averaged diagnostics. Flow penetration is strongly wavelength-dependent, with easy penetration at long wavelengths but strong inhibition at short wavelengths. The amplitude of the geoid is not significantly affected.

(2) Using a simple criterion for the deflection of an upwelling or downwelling by an endothermic phase transition, the scaling of the critical phase buoyancy parameter with the important lengthscales is obtained. The derived trends match those observed in numerical simulations, i.e., deflection is enhanced by (a) shorter wavelengths, (b) narrower up/downwellings (c) internal heating and (d) narrower phase loops.

(3) A systematic investigation into the effects of temperature-dependent viscosity on mantle convection has been performed in three-dimensional Cartesian geometry, with a factor of 1000-2500 viscosity variation, and Rayleigh numbers of 10^5-10^7. Enormous differences in model behavior are found, depending on the details of rheology, heating mode, compressibility and boundary conditions. Stress-free boundaries, compressibility, and temperature-dependent viscosity all favor long-wavelength flows, even in internally heated cases. However, small cells are obtained with some parameter combinations. Downwelling plumes and upwelling sheets are possible when viscosity is dependent solely on temperature. Viscous dissipation becomes important with temperature-dependent viscosity.

The sensitivity of mantle flow and structure to these various complexities illustrates the importance of performing mantle convection calculations with rheological and thermodynamic properties matching as closely as possible those of the Earth.

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Revealing, illuminating, and modifying proteins in human diseases using noncanonical amino acids

To better understand human diseases, much recent work has focused on proteins to either identify disease targets through proteomics or produce therapeutics via protein engineering. Noncanonical amino acids (ncAAs) are tools for altering the chemical and physical properties of proteins, providing a facile strategy not only to label proteins but also to engineer proteins with novel properties. My thesis research has focused on the development and applications of noncanonical amino acids in identifying, imaging, and engineering proteins for studying human diseases. Chapter 1 introduces the concept of ncAAs and reveals insights to how I chose my thesis projects.

ncAAs have been incorporated to tag and enrich newly synthesized proteins for mass spectrometry through a method termed BONCAT, or bioorthogonal noncanonical amino acid tagging. Chapter 2 describes the investigation of the proteomic response of human breast cancer cells to induced expression of tumor suppressor microRNA miR-126 by combining BONCAT with another proteomic method, SILAC or stable isotope labeling by amino acids in cell culture. This proteomic analysis led to the discovery of a direct target of miR-126, shedding new light on its role in suppressing cancer metastasis.

In addition to mass spectrometry, ncAAs can also be utilized to fluorescently label proteins. Chapter 3 details the synthesis of a set of cell-permeant cyclooctyne probes and demonstration of selective labeling of newly synthesized proteins in live mammalian cells using azidohomoalanine. Similar to live cell imaging, the ability to selectively label a particular cell type within a mixed cell population is important to interrogating many biological systems, such as tumor microenvironments. By taking advantage of the metabolic differences between cancer and normal cells, Chapter 5 discusses efforts to develop selective labeling of cancer cells using a glutamine analogue.

Furthermore, Chapter 4 describes the first demonstration of global replacement at polar amino acid positions and its application in developing an alternative PEGylation strategy for therapeutic proteins. Polar amino acids typically occupy solvent-exposed positions on the protein surface, and incorporation of noncanonical amino acids at these positions should allow easier modification and cause less perturbation compared to replacements at the interior positions of proteins.

Modifying Bulk Metallic Glasses: Composites and Configurational States

Bulk metallic glasses (BMGs) maybe be considered to share some of the same inherent trade-offs as engineering ceramics. While BMGs typically exhibit high yield strengths, and while some have surprising fracture toughness, they exhibiting little to no tensile ductility, and fail in a brittle manner under uniaxial loading. Speaking broadly, there are two complimentary approaches to improving on these shortcomings: 1) create bulk metallic glass matrix composites (BMGMCs) and 2) improve the properties of a monolithic BMG. The structure of this thesis mirrors this division, with chapters 2-7 focusing on creating and processing amorphous metal matrix composites, and chapter 8 focusing on modifying the properties of a monolithic BGM by altering its configurational state through irradiation.