VictorJuiz/thesis huggingface dataset:
Optimization Tools for Constrained Energy Markets

This dissertation develops an interdisciplinary approach to integrating renewable energy resources into energy markets, using tools from optimization theory, power systems, and economics. It advances prior work with the development of a set of tools for securing distributed and fully-decentralized optimization problems, including both algorithmic guards against attacks by malicious nodes, and system architectures which can enable decentralized security checks. Leveraging the emerging technologies of blockchains and smart contracts, it develops a new paradigm of blockchain-secured distributed optimization, demonstrated with simulation of a microgrid which is able to securely operate without oversight from a utility or central operator./nAs the goal of interdisciplinary research is to show mastery of each field and extend current knowledge by exploring their intersection, the chapters of this dissertation are designed to support that goal:/n• Chapter 1 provides background on the technical challenges of integrating high amounts of renewable energy into the electricity system, and discusses technologies and policies which can address those challenges./n• Chapter 2 introduces the idea of applying optimization tools to energy systems by studying a small-scale energy harvesting system in which batteries and capacitors are used to meet a defined load, and constraints force the use of nonlinear optimization techniques./n• Chapter 3 explores how large-scale energy storage systems can be designed and sited to maximize profits from participating in wholesale energy markets, using a linear program which demonstrates how convex optimization tools can be united with energy market data to create scalable tools for modeling large networks./n• Chapter 4 expands the study of market-based models by examining the strategic operation of generation resources on a congested network. We use game theory to model participants’ behavior, power flow models to reflect the underlying constraints of the physical network, and robust convex optimization to explore how uncertainty is integrated into decision-making./n• Chapter 5 discusses how decentralized optimization models can facilitate scalable optimization tools, and explores the security risks which these optimization models introduce. Tools for detection and mitigation of attacks are explored and tested on a simple problem. Potential architectures for securing decentralized optimization are explored, including blockchains and smart contracts./n• Chapter 6 extends this approach by developing a blockchain-secured fully-decentralized optimization for a microgrid dispatch problem, coordinating distributed energy resources. By demonstrating the usefulness of this blockchain-secured optimization model, this culminating chapter shows how difficult optimization models can be scalably solved in a manner which respects privacy while guaranteeing security./n• The Appendices present tutorial material on the tools used throughout the paper, and are supplemented by the code in the author’s github repository: https://github.com/emunsing/tutorials

Advisor: Moura, Scott
Essays On The Competitive Commodity Storage Model

This dissertation consists of three essays on the competitive commodity storage model. This model provides a basis for rationalizing many of the observed qualitative features of the behavior of prices of storable commodities. I attempt to make a contribution to this model in three dimensions: empirical (chapter 1), numerical (chapter 2), and theoretical (chapter 3)./nIn the first chapter, I analyze the ability of the standard commodity storage model to replicate serial correlation in annual prices. Calendar year averages of prices induce spurious smoothing of price spikes, a fact that has been surprisingly overlooked in several empirical studies of the annual commodity storage model for agricultural commodities. I present an application of a maximum likelihood estimator of the storage model for maize prices, correcting for the spurious smoothing. My results, using this data set, imply serious differences in magnitudes of interest. These differences include the location and skewness of the empirical distribution of prices relative to the cutoff price of zero stocks, the likelihood of stockouts, and the fit to data on stocks-to-use ratios./nIn the second chapter, I propose an alternative numerical strategy for solving nonlinear rational expectation models with inequality constraints. It addresses three problems observed in the standard solution method: lack of robustness to scaling transformation of the stationary rational expectation function, errors of approximation due to extrapolation within the ergodic set, and interpolation around the kink implied by the inequality constraint. In comparison with the standard solution method, my findings suggest that the numerical strategy I propose is robust to scaling transformation, removes the approximation errors due to extrapolation, and avoids interpolation above the kink./nFinally in the third chapter, I present a critique of a theoretical version of the competitive commodity storage model that assumes a support for the speculative storage that is bounded from below at zero, and above at a exogenous predetermined maximum capacity. By proposing a counter-example, I show that the fixed point iteration operator proposed by Oglend and Kleppe (2017) to solve this version of the model does not converge in general, as they claim.

Advisor: Wright, Brian Darven
Quantum Simulation of the Bose-Hubbard Model with Ultracold Atoms in Triangular Optical Superlattices

Quantum simulation is the study of one quantum mechanical system via analog with another. In this thesis we explore a simple model of interacting bosons on a lattice, known as the Bose-Hubbard model, by experimental investigation of ultracold rubidium atoms in an optical lattice made from laser light./nWe describe the construction and stabilization of an optical superlattice with threefold symmetry, and its use in studying the Bose-Hubbard model on triangular and trimerized kagome lattices. We study the short range phase coherence of a Mott insulator on the triangular lattice, and develop a scheme to mitigate out-of-equilibrium effects arising from the state preparation. We show the first experimental realization of an optical trimerized kagome lattice for cold atoms, and discuss experiments characterizing this lattice. Finally, we provide evidence for a Mott insulating state with fractional average particle number per site with measurements of the nearest-neighbor phase coherence of strongly interacting atoms in the trimerized kagome lattice.

Advisor: Stamper-Kurn, Dan M
Planning and Control of Drift Maneuvers with the Berkeley Autonomous Race Car

In competitive sporting events, drivers operate vehicles at the limits of handling, with near full rear tire saturation. Expert drivers intentionally drift their vehicles around corners to turn the vehicle quickly. These drivers operate their vehicles in a way that is contrary to the way safety system in automotive electronic control units are designed. By investigating and understanding the physics and operating principles of these maneuvers, it may be possible to enhance safety features in automotive control systems for collision avoidance, as well as enable sports cars to autonomously perform drift within the context of racing. The main focus of this dissertation is on planning and control of drift maneuvers, in particular, steady state drift, drift parking, and drift cornering./nSecondly, with the growth of research and engineering in the domain of autonomous vehicles, the dissertation also focuses on the design and development of a robotic platform called the Berkeley Autonomous Race Car (BARC). The platform is based on a 1/10-scale remote control vehicle equipped with computing hardware and a suite of sensors that make it suitable for research and instruction. The project aims to provide a low-cost, open-source testbed option for researchers and instructors interested in autonomous vehicles. The methods and algorithms provided in the first part of the dissertation are experimentally validated on the BARC platform.

Advisor: Borrelli, Francesco
Visual Learning Beyond Direct Supervision

Deep learning has made great progress in solving many computer vision tasks for which labeled data is plentiful. But progress has been limited for tasks where labels are difficult or impossible to obtain. In this thesis, we propose alternative methods of supervised learning that do not require direct labels. Intuitively, although we do not know what the labels are, we might know various properties they should satisfy. The key idea is to formulate these properties as objectives for supervising the target task. We show that this kind of “meta-supervision” on how the output behaves, rather than what it is, turns out to be surprisingly effective in learning a variety of vision tasks./nThe thesis is organized as follows. Part I proposes to use the concept of cycle-consistency as supervision for learning dense semantic correspondence. Part II proposes to use the task of view synthesis as supervision for learning different representations of scene geometry. Part III proposes to use adversarial supervision for learning gradual image transformations. Finally, we discuss the general concept of meta-supervision and how it can be applied to tasks beyond those presented in this thesis.

Advisor: Efros, Alexei A
On Monsters, Patterns and Appendages

The diversity of animals is a topic of childlike fascination, poetic wonder, and scientific discovery; but how did such great diversity of form and function come to be? To uncover the possible mechanisms by which diverse new body plans are generated over evolutionary time, we turn to understanding the patterns and processes behind how individual bodies are constructed — and deviated — during embryonic development. Critically important to the specification of body plan diversity is the patterning of the anterior-posterior axis and establishment of regional identities by the Hox genes./nHox genes have a revolutionizing history, complete with striking transformation of form upon their mutation. The rapid discovery of orthologous sets of Hox genes in a diversity of species led to the exciting realization that not only are individual Hox genes conserved across Bilateria, so too are their patterns of expression, mutation, arrangement, and properties in aggregate—changes to which have been implicated as important generators of evolutionary diversification. This apparent conservation enabled many useful generalizations to be gleaned from a limited number of representative species, and paradigms such as posterior prevalence became widespread. Increasingly, however, new technologies enable us to expand the scope of our study to a wider array of species and cases breaking the “rules” of these models are accumulating. This warrants the comprehensive study of Hox genes in aggregate in a greater number of representative species to resolve a fuller picture of the Hox complex and its interactions during the specification of regionalized bodies and the diversification of specialized forms./nBy resolving Hox expression patterns in transformed individuals following Hox gene knockout in the appendage-diverse amphipod crustacean Parhyale hawaiensis, we have revealed a number of cross-regulatory interactions among Hox genes that influence the patterning of Hox domains. Furthermore, by amassing a fuller picture of the Hox expression underlying the appendage transformations, we make a more informed model of the functional roles and interactions of the different Hox genes in the designation of limb identities. We have shown that posterior prevalence is not sufficient to predict the appendage transformations in Parhyale and that a modular ‘Hox code’ expressed in individual segments functions to establish segmental identity. We believe this study demonstrates that interactions among Hox genes provide a mechanism for the diversification of appendage morphologies and arrangements over evolutionary time.

Advisor: Patel, Nipam H
Do Non-GAAP Earnings Influence Real Activities and Accounting Choices?

It is now common for firms to emphasize non-GAAP earnings metrics that exclude certain GAAP-based expenses, such as acquisition and restructuring expenses, intangible asset amortization, asset write-downs, and stock compensation expense. This study hypothesizes that managers become focused on non-GAAP earnings, causing them to underweight excluded expenses when making investment and accounting decisions. Consistent with the underweighting of acquisition-related expenses, firms with a history of reporting non-GAAP earnings over-invest relative to their peers, and engage in more acquisitions. With respect to accounting choices, excluded expenses such as write-downs and stock option expense are recorded and measured more conservatively when excluded from non-GAAP earnings. Using SFAS 141(R) and SFAS 123(R) as difference-in-differences settings, firms’ choices are found to be less sensitive to accounting standard changes when the affected expense is excluded from non-GAAP earnings. The evidence suggests that the use of non-GAAP earnings can influence real activities and accounting choices.

Advisor: Sloan, Richard G
Advanced Quadrature Selection for Monte Carlo Variance Reduction

Neutral particle radiation transport simulations are critical for radiation shielding and deep penetration applications. Arriving at a solution for a given response of interest can be computationally difficult because of the magnitude of particle attenuation often seen in these shielding problems. Hybrid methods, which aim to synergize the individual favorable aspects of deterministic and stochastic solution methods for solving the steady-state neutron transport equation, are commonly used in radiation shielding applications to achieve statistically meaningful results in a reduced amount of computational time and effort. The current state of the art in hybrid calculations is the Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted CADIS (FW-CADIS) methods, which generate Monte Carlo variance reduction parameters based on deterministically-calculated scalar flux solutions. For certain types of radiation shielding problems, however, results produced using these methods suffer from unphysical oscillations in scalar flux solutions that are a product of angular discretization. These aberrations are termed “ray effects”./nThe Lagrange Discrete Ordinates (LDO) equations retain the formal structure of the traditional discrete ordinates formulation of the neutron transport equation and mitigate ray effects at high angular resolution. In this work, the LDO equations have been implemented in the Exnihilo parallel neutral particle radiation transport framework, with the deterministic scalar flux solutions passed to the Automated Variance Reduction Generator (ADVANTG) software and the resultant Monte Carlo variance reduction parameters’ efficacy assessed based on results from MCNP5. Studies were conducted in both the CADIS and FW-CADIS contexts, with the LDO equations’ variance reduction parameters seeing their best performance in the FW-CADIS method, especially for photon transport.

Advisor: Slaybaugh, Rachel N
Characterization of evolutionary trends in the protein energy landscape

The process of molecular evolution has produced the diversity of proteins observed across life. The function and properties of proteins are chemically encoded by their amino acid sequence and can be described as a multi-dimensional energy landscape. A major effort in the field of biology has been to decode this information and to apply that knowledge to understand and manipulate protein function. Because the energy landscape fundamentally determines the behavior of a protein, there are likely evolutionary pressures on various features of the landscape. However, a detailed investigation into how the energy landscape of a protein changes over evolutionary time has been lacking./nIn this work, we use ancestral sequence reconstruction (ASR) to access the evolutionary history of the ribonuclease H (RNase H) family. We reconstruct and study the properties of seven ancestral RNases H connecting the lineages of two homologs: a mesophilic RNase H from E. coli and a thermophilic RNase H from T. thermophilus. We characterize how the energetics, rates, and conformations of the RNase H energy landscape, and particularly, its folding pathway, evolved over time using a global analysis of ensemble relaxation kinetics, hydrogen exchange monitored by mass spectrometry (HX-MS), and fragment models of high-energy partially folded conformations. The folding trajectory of RNase H is remarkably robust to mutations over evolutionary time, with the major folding intermediate being energetically and structurally conserved over three billions years of evolution. There are notable trends in the folding and unfolding rates, and RNase H becomes more kinetically stable over time. We observe how the conserved folding intermediate enables distinct trends in the thermodynamic and kinetic properties of the folding landscape. Additionally, we used HX-MS to obtain near-site-resolved structural resolution into the conformations of ancestral RNase H during folding. The earliest events in the folding trajectory are malleable over evolutionary time, and we use the evolutionary trends to identify the mechanisms that drive the folding of this protein./nIn addition to revealing the evolutionary history of the RNase H family, these ancestral proteins can be used to understand protein fitness in the cellular context, and be compared to consensus proteins to investigate how evolutionary sequence information can be used to engineer protein properties. Lastly, the evolutionary trends in the RNase H family can be extended towards other protein families to identify general principles that guide protein evolution.

Advisor: Marqusee, Susan
A Search for Lightly Ionizing Particles in the LUX Detector and Research and Development For Future Liquid Xenon Time Projection Chambers

The nature of dark matter is one of the most compelling mysteries of modern physics. Liquid xenon detectors have been at the forefront of the attempt to directly detect dark matter particles for the last decade. The Large Underground Xenon (LUX) experiment recently concluded its operations at the Sanford Underground Research Facility in Lead, South Dakota. During its tenure, LUX set world-leading limits on WIMP dark matter, and paved the way for novel calibration techniques. Due in part to experiments like LUX, the available WIMP parameter space has been dwindling, making experimentalists look to other dark matter candidates. While new technologies will no doubt be needed in the hunt for dark matter, the well-understood detector technology of liquid xenon can be leveraged to search for non-WIMP dark matter. One such candidate, from the general class of dark sector theories, is the Lightly Ionizing Particle (LIP). LIPs interact with regular matter with an effective fractional charge, and the LUX detector is capable of detecting such interactions. New analysis techniques were developed to search for cosmogenic LIPs in the LUX detector, the first such analysis of its kind in liquid xenon./nLarger, more sensitive successors to the LUX experiment are already in planning and construction phases. As detectors become more sensitive, previously subdominant effects become more important. Under the umbrella of detector R\&D for LUX's more sensitive successor, LZ, a test bed was built to investigate issues that may threaten the sensitivity of future xenon dark matter detectors. Radon backgrounds and the phenomenon of delayed electron noise were studied, revealing new behavior that may help control backgrounds. Delayed electron noise is of special interest, as this phenomenon is the main background for the LIP search.

Advisor: McKinsey, Daniel
Characterizing the Fatigue Behavior of the High-Entropy ‘Cantor’ Alloy CrCoMnFeNi

High-entropy alloys (HEAs) have spurred great interested in the in the materials community in recent years, primarily due to the intriguing properties certain members have been shown to display and due to the novel approach to alloy design they represent. Of this family of multi-component alloy systems, the near-equiatomic five component “Cantor” alloy CrCoMnFeNi is of particular note due to the remarkable mechanical properties this alloy has been found to display which are only enhanced as the temperature is lowered into the cryogenic regime. Despite the interest in this alloy system, little work has to date been conducted that characterize the cyclic fatigue loading behavior of this alloy or of its compositional variants. Here I examine the damage-tolerant fatigue behavior of the Cantor alloy as well as the effect temperature and load ratio have in changing this behavior and the underlying mechanisms that may be responsible for the observed shifts. These testing conditions encompassed three temperature regimes: 293 K, 198 K, and 77 K; additionally, the impact of increased load ratio R was surveyed within each temperature regime. Fatigue testing in the threshold and linear portion of the Paris regime revealed a temperature dependence of the fatigue behavior of the Cantor alloy; as temperature was decreased into the cryogenic regime, the fatigue curve was found to shift toward higher ΔK, indicating a higher resistance to fatigue-crack propagation at lower temperature. Additionally, it was observed that higher load ratios impacted this resistance negatively, causing a shift towards lower ΔK with increasing R-ratio. Post-testing, a series of mechanistic studies were conducted to investigate the underlying cause for this observed shift. Analyses of crack closure measurements, crack-path morphology, and fractography provided strong evidence for roughness-induced crack closure as the dominant mechanism at play.

Advisor: Robert, Ritchie O
Algebraic Modular Forms on SO5(Q) and the Computation of Paramodular Forms

This dissertation describes a result that compares two level subgroups on different inner forms of GSp(4), and then uses this result and a conjecture of Ibukiyama’s to compute paramodular forms for all prime levels below 400. In the process 78 generic forms were computed, of which 47 had not been previously computed.

Advisor: Ribet, Kenneth