VictorJuiz/thesis huggingface dataset:
Fast data assimilation and optimal control methods and applications [electronic resource]

With recent advances in environmental monitoring technology and remote sensing capabilities for data collection continually increasing, interest in data assimilation techniques for improving our understanding and predictive abilities related to natural systems has been mounting. One of the most popular data assimilation methods is Kalman filter (KF) which gives the minimum mean square error estimate for linear systems. Also, for nonlinear systems, the nonlinear KF variants can provide reasonably accurate estimation with the uncertainty of the estimation. However, application of KF for large-scale problems is computationally expensive. The computational cost of conventional Kalman filters scales quadratically with the number of unknowns, due to the cost of computing and storing covariance and Jacobian matrices, along with their matrix-vector products. In this work, we have developed new KF methods, the Spectral Kalman filter, and the Modified Compressed State Kalman Filter, that exploit the formulation of the state space models as well as the covariance structures to achieve computational efficiency while maintaining the quality of uncertainty quantification. Also, we have combined the SpecKF method with a fast optimization algorithm to simultaneously estimate the unknown parameters and state of the system and generate an optimal policy to control the system. This new fast optimization technique is called Rapid Feedback Control (RFC). The fast data assimilation and optimization algorithms developed here are for combined characterization, monitoring, and control of large-scale nonlinear systems. The proposed methods address the current lack of algorithms for reliable and cost-effective real-time estimation and optimization. The developed algorithms are tested and validated for three different hydrological applications. However, These methods can be extended to perform data assimilation for problems with similar characteristics in a wide range of applications.

Keywords: Mechanical Engineering.
Advisor: Darve Eric primary advisor. Thesis advisor
Kitanidis P. K. (Peter K.) advisor. Thesis advisor
Kokkinaki Amalia advisor. Thesis advisor
A FAST data mining approach for similar earthquake detection

Seismology, a data-driven science where breakthroughs often come from improved observations, is experiencing rapid growth in the quantity of data. Many recent advances in computing technologies enable the automatic detection of hidden patterns in massive data volumes: increased computing power, parallel processing, more memory, vast disk storage, and the development of new scalable data mining and machine learning algorithms. Seismologists can leverage these technological advances to extract more useful information from these data sets. This thesis employs advances in data-driven technology to improve a fundamental operation for observational seismology: earthquake detection. It introduces a new algorithm called Fingerprint And Similarity Thresholding (FAST), adapted from a data mining technique originally developed for audio recognition, to detect small earthquake signals within continuous time series seismic data. FAST efficiently performs a comprehensive blind search for similar earthquake signals at all possible times in the continuous data, without requiring previous knowledge about the earthquake waveform. FAST is scalable to continuous data sets up to a decade long, and can detect earthquake signals over a network of multiple seismic stations. FAST can identify new earthquake sources that produce only small, previously undetected earthquakes; it is especially useful for detecting new earthquakes in sparse seismic networks, but can also find previously unknown earthquakes even with relatively complete catalogs. Three separate investigations in this thesis reveal that earthquakes newly detected with FAST, followed by their relative location, magnitude estimation, and source characterization, provide a more complete understanding of the underlying earthquake process: 1) The 1999 magnitude 7.1 Hector Mine, California, earthquake was triggered by a cascade of stress transfer from its foreshocks; 2) Microseismicity near the Diablo Canyon nuclear power plant in California from 2007-2017 confirmed that nearby faults are active; 3) Many microearthquakes in the initial stages of the 2010 Guy-Greenbrier, Arkansas, earthquake sequence were induced by hydraulic fracturing. The open-source FAST software, developed in an interdisciplinary collaborative effort, successfully detects earthquakes in a diverse range of seismic data sets, and it can be a useful tool to enable other seismologists to discover small earthquake signals of interest.

Keywords: Geophysics.
Advisor: Beroza Gregory C. (Gregory Christian) 
Dunham Eric 
Ellsworth William L.
Fault and fracture identification and characterization in 3D seismic data from unconventional reservoirs

Unconventional reservoirs are becoming increasingly important on the world energy stage. Such reservoirs are hydrocarbon sources that need stimulation of some kind in order to be produced in an economically viable way, unlike conventional sources, where oil or gas readily flows into producing wells through more permeable strata. In recent years, unconventional reservoirs have proven to be highly important in North America and have, despite some setbacks and shutdowns, survived reductions in oil and gas prices. A big part of this can be attributed to exploration companies' ability to extract unconventional hydrocarbons with good efficiency, which is in turn attributed to enhanced understanding of the physical dynamics of such reservoirs due to a large body of work done by researchers. Nevertheless, unconventional recovery factors are still considerably low, and further research contributions are needed to better understand how these reservoirs work and interact with stimulation. In this thesis, I focus on the role that faults and fractures play in low permeability reservoirs' response to stimulation, particularly hydraulic fracturing. I analyzed three data sets acquired from and around injection and monitoring wells in the Barnett Shale in Texas. In two of these data sets, I identified small-scale faults and integrated faulting information with other data from wells (e.g. microseismic recordings) to understand how the presence of faults affects injected fluid flow. Results showed that even small-scale faults can have significant effects on hydraulic fracturing progress by providing corridors for fluid flow along them (a high permeability path due to fractures surrounding faults) or by dissipating fluid pressure across them, preventing fluids from effectively crossing to the other side of the fault. For one data set with different seismic surveys acquired before and after stimulation and gas production, I used 3D seismic attribute analysis to identify fractures in and around injection wells to evaluate the methods used, namely azimuth-dependent Amplitude Vs. Offset (AzAVO) and Velocity Vs. Azimuth (VVAz), and to understand how stimulation and production affected fractures in this area of the Barnett. Results showed that fracture density, rather than orientation, is more affected by the pressure introduced during stimulation and by pressure reduction with injected fluid removal and production. I also used well logs to determine the effects of mineral and organic matter content on important rock properties such as porosity. I compared results obtained on small samples (cores) in the laboratory with my results obtained from well logs which are significantly dimensionally larger than cores analyzed in labs. I concluded from analyzing well logs that porosity, for example, is proportional to organic content. This conclusion is similar to that derived from laboratory findings: porosity in many shales resides in organic material such as Kerogen.

Keywords: Geophysics.
Advisor: Zoback Mark D. 
Graham S. A. (Stephan Alan)
Mavko Gary
Feasibility study of additive manufacturing for metallic façade components

The state-of-the-art analysis of additive manufacturing (AM), popularly known as 3D printing, shows that the coexistence of AM and conventional manufacturing (CM) currently used in the practice, is a reality today. However, since Architecture-Engineering-Construction (AEC) practitioners are not informed about the value of AM through transparent metrics like cost and schedule they are unable to make well-informed decisions about the application of AM in the building sector. To address the lack of information about the value of AM for AEC and the lack of well-documented studies of AM vs. CM for building components, I developed and conducted a feasibility study in collaboration with Permasteelisa Group, the global leading façade contractor. The Feasibility Study was designed to determine the applicability, costs, and the duration of manufacturing of two metallic curtain wall (CW) components using AM and to compare these figures with CM. The study demonstrated that AM for building components is technologically feasible, but is cost-prohibitive today. For all cases, the manufacturing cost and duration were about 90% higher or 90% longer, respectively, than for the related CM components. The applicability analysis showed that two of the analyzed AM technologies with small-scale platforms, direct metal laser sintering (DMLS) and electron beam melting (EBM), produced by EOS and Arcam, are suitable for AM of building components in geometric size that fit in their build chambers. Large-scale metallic components can be produced with large-scale metallic deposition technologies, produced by Sciaky Inc., DM3D, Optomec, and Fabrisonic. Further AM cost and manufacturing time reductions are expected with ongoing AM technological development. Future work includes analysis of other performance criteria such as environmental impact of AM vs. CM to provide more comprehensive conclusions about the AM's potential for AEC.

Advisor: Fischer Martin
Filter Bubbles And Music Streaming: The Influence of Personalization And Recommendation Algorithms on Music Discovery Via Streaming Platforms

As music streaming continues to rise in popularity, researchers should analyze the implications of streaming personalization and recommendation algorithms. This study explores how streaming algorithms influence the way that users discover and appreciate music, with a hypothesis that streaming platforms operate as filter bubbles that limit the user’s exposure to diversity. I surveyed over 100 people on their streaming discovery habits. I found that participants were likely to discover music via curated and/or recommended playlists. I also found that respondents with different language abilities searched for, encountered, and reacted to non-English songs differently. My observations, alongside the available literature, suggest that filter bubbles cause music discovery on streaming platforms to differ from music discovery in a public sphere. Furthermore, due to the opacity of streaming personalization algorithms, streaming users may not realize that their discovery is limited to such filter bubbles.

Keywords:  Department of Communication
music streaming
discovery
filter bubbles
Spotify
public sphere
media studies
music media
diversity
Stanford University
Stanford University Department of Communication and Journalism
Thesis
Advisor: Christin Angèle
First direct measurements of dissipation mechanisms in MEMS resonators

Microelectromechanical systems (MEMS) have become ubiquitous and are used in all modern electronics, from cell phones to satellites. With the never-ending demand for smaller, lighter, faster electronics that consume less power, designing MEMS components that dissipate less energy, i.e., have a higher Quality Factor (Q), has become even more crucial. This dissertation presents a novel methods of measuring the Q of microelectromechanical systems (MEMS) at low temperature that enables the elimination of the thermal expansion coefficient (CTE). At in-depth investigation of the CTE using families of DETF resonators created by means of the epi-seal encapsulation process with different crystal orientations was performed. Experiments were performed with the purpose of eliminating CTE, and, consequently, rendering negligible the effects from thermoelastic dissipation (TED). Our results demonstrate that this measurement method enabled the first direct examination of the strength of anchor damping in tuning fork resonators, which allowed us to study the effect of anchor design and other factors on anchor damping. Our results reveal an unanticipated impact that structures far away from the anchor have on anchor damping, which is contradictory to many predictions of conventional models for anchor damping. A second finding about anchor damping, presented for the first time, is that not only can this damping term be clearly seen in WE mode devices, but it also shows a clear temperature dependence. Furthermore, Lame-mode resonators at low temperature enabled the first direct detection of Akhiezer damping in a MEMS resonator. Akhiezer damping, first identified by Akhiezer in 1965, has been the focus of extensive research. Several theoretical studies have focused on Akhiezer damping near room temperature; however, direct detection of Akhiezer damping has proved difficult because other, stronger dissipation mechanisms have precluded experimental analysis over a wide range of temperatures. For this work a novel apparatus and methods were developed that enabled us to do the first direct examination of Akhiezer damping in MEMS resonators by measuring the f*Q product. Our results provide the first clear, direct detection of Akhiezer dissipation in MEMS resonator, which is widely considered to be the ultimate limit to Q in MEMS devices.

Keywords: Mechanical Engineering.
Advisor: Kenny Thomas William 
Harris J. S. (James Stewart)
Howe Roger Thomas
Fitness genome-wide association study identifies five novel loci that are related to metabolic and immune pathways

The decrease in costs associated with genetic sequencing and the recent growth in large-scale data collection have resulted in the increasing prevalence of genome-wide association studies. The United Kingdom Biobank is an organization that has collected numerous pieces of phenotypic data from approximately 500,000 participants, which includes time series data from a sub-maximal exercise test. In conjunction with their genetic sequencing data, our study extracted two direct measures of physical fitness, which were then used as fitness scores in two GWAS. Our results identify 33 distinct genomic regions associated with physical fitness, which have upregulated genes in the muscle and heart tissues and have significant overlaps with gene sets responsible for muscular and cardiac function and development. In addition, our study finds five novel regions that have not been associated with previous GWAS. These loci are associated with metabolic and immune pathways and include mappings to the THRB, CADM2, and DLEU2 genes.

Keywords:  Department of Biology
Biology
Genetics
GWAS
Fitness
Physical Activity
UKBB
SNP
Thesis
Advisor: Ashley Euan
Bergmann Dominique
Skotheim Jan
Flawed assumptions, robust evidence [electronic resource] : on the role of theoretical presuppositions in grounding empirical evidence in science

A number of perennial issues in philosophy of science, including underdetermination and the rationality of theory change, hinge on the provisional or "local" character of scientific knowledge. I investigate the role of the theoretical presuppositions that ground good empirical evidence in two historical cases: Newton's Principia and Cecilia Payne's landmark 1925 dissertation on stellar atmospheres. I show, in both cases, how provisionally adopted presuppositions were crucial to acquiring strong evidence and characterize the sort of justification that was available for them.

Keywords: Philosophy.
Advisor: Friedman Michael
Longino Helen E. advisor. Thesis advisor
Ryckman Thomas advisor. Thesis advisor
Smith George
The flexibility of caustics [electronic resource]

In this thesis we establish a full h-principle for the simplification of singularities of Lagrangian and Legendrian fronts. More precisely, we show that if the obvious homotopy theoretic obstruction to the simplification of singularities vanishes, then the simplification can be achieved by means of an ambient Hamiltonian isotopy. The h-principle is full in that it holds in C^0-close, relative and parametric versions. Among several applications of the h-principle we obtain a generalization of the Reidemeister theorem for Legendrian knots in the standard contact R^3, which allows for the simplification of the singularities of the front of a family of Legendrian knots parametrized by a space of arbitrary dimension. To prove our result we use two well-known tools in the philosophy of the h-principle: the holonomic approximation lemma and the wrinkled embeddings theorem. However, both of these tools need to be upgraded in order to be applicable to the situation at hand. For this purpose we refine the holonomic approximation lemma to a version in which cutoffs can be carefully controlled and we adapt the wrinkled embeddings theorem to the setting of Lagrangian and Legendrian embeddings.

Keywords: Mathematics.
Advisor: Eliashberg Y.
Ionel Eleny advisor. Thesis advisor
Starkston Laura
Flexible organic transistors for bioinspired mechanosensory systems and image sensor arrays

Organic semiconductors are mechanically flexible or even stretchable, and their properties, such as electronic, optical, mechanical, chemical properties, are tunable via modification of their chemical structures. We can utilize organic semiconductors for flexible electronics, such as displays, wearable sensors, and electronic skins. When making flexible organic thin-film transistors, we need to have a good understanding of organic thin-film growth and avoid the damages of organic semiconductors from organic solvents, water, UV light, and high temperatures during fabrication. The growth and characterization of thin films of two thienoacene dimers are discussed first. Depending on alkylation, dimerization, and fusion, thienoacenes showed different thin-film morphologies and electronic properties. Then, organic thin-film transistors are fabricated on flexible substrates and used for two different bioinspired applications: artificial mechanosensory systems and hemispherical optical sensor arrays. Our artificial mechanosensory system consisted of pressure sensors, organic ring oscillators, and organic ion-gel transistors. Our artificial mechanosensory system processed pressure information in a way the biological somatosensory system does. Our artificial mechanosensory system can be used to build neurorobots and neuroprosthetics. The other application of organic thin-film transistors was hemispherical optical sensor arrays mimicking eyeballs. Photolithographic processes were used for high density, but photoresist residues contaminated gate dielectric surfaces. The photoresist residue was avoided using an aluminum sacrificial layer. The transfer process of flexible organic thin-film transistors onto a hemisphere was also described. Keywords: flexible electronics, organic thin-film transistors, bioinspired systems, neuromorphic, transfer processes.

Keywords: Electrical Engineering.
Advisor: Bao Zhenan 
Nishi Yoshio
Wong Hon-Sum Philip
Flexural Modeling of Foreland Basins

This contribution focuses on the e↵ect of laterally varying elastic thickness in the un- derlying lithosphere and thrust loading on foreland basin subsidence. I use numerical models to compare flexural subsidence patterns expected in basins with little lateral variation in crustal thickness (e.g., Chaco Basin in Bolivia) with those typical of strong lateral variations in this property (Magallanes-Austral Basin in Chile/Argentina). In the Chaco Basin case, the observed basin geometry is well modeled using an elastic beam with uniform rigidity. In contrast, the Magallanes-Austral Basin contains rem- nants of the Rocas Verdes backarc basin proximal to the Patagonian fold-and-thrust belt and transitions to unattenuated continental crust in the distal plate segment from the thrust front. As a result of this strong lateral variation in crustal thickness, flexural subsidence predicted by an uniform-rigidity elastic beam model is inconsis- tent with measured subsidence. Instead, a model with varying elastic thickness better reconciles the bathyal foredeep and the relatively long wavelength deflection observed in the Magallanes-Austral case. I further this analysis with non-dimensionalizing the varying rigidity model and explore the evolution of basin geometry as the thrust front horizontally expands. I find that the initial phases of basin development are flexurally driven, but as the topographic load expands horizontally, isostatic forces take over and the basin depth becomes dependent on the crustal loading configurations rather than on the properties of the underlying lithosphere. The modeled basin history also has implications for sediment patterns, as rigidity variations in the lithosphere can result in hinge-like subsidence that localizes deposition spatially instead of relative to the thrust front.

Keywords:  Department of Geological Sciences
Geological Sciences
Stanford Tectonic Geomorphology Lab (STGL)
Stanford University
Earth Energy &amp; Environmental Sciences
Thesis
Advisor: Hilley George
Malkowski Matthew
Fluid-induced seismicity and fully dynamic earthquake rupture in fractured poroelastic media : models, discretization and computation

This thesis establishes a computational modeling framework for earthquakes induced by anthropogenic fluids. The medium of interest is a fault-hosting porous elastic solid saturated with a single-phase compressible fluid and subjected to external fluid perturbations. The fluid and solid interact in a fully coupled manner (namely poroelastic coupling) to produce changes and drive a source fault through the inter-seismic quasi-static earthquake triggering and toward the subsequent co-seismic dynamic earthquake rupture. In modeling these subprocesses, I first resolve fault-related model additions in the mathematical formulations and then develop accordingly some new discretization and computational procedures for efficiently finding the numerical solutions. Specifically, in Chapter 2, I establish a single-phase, nonlinear, transient, quasi-static and fully coupled poromechanical modeling framework in the presence of an arbitrary network of hydraulically conductive faults. A hybrid-dimensional two-field mixed low-order finite element method is developed for efficient space discretization. Chapters 3 and 4, both drawing inputs from Chapter 2, are dedicated to the modeling of fluid-induced earthquakes. In Chapter 3, I am concerned with the modeling of large numbers of events and the associated source characteristics (seismicity). To do so, I utilize (1) the fracture-poro-mechanical modeling technique from Chapter 2 for the inter-seismic triggering and (2) a physics-based stochastic stress drop modeling technique to statically approximate the co-seismic failure. A new computational procedure is then developed to couple the two and advance them through seismic cycles. In Chapter 4, I focus on a single earthquake event and closely examine the associated co-seismic fully dynamic spontaneous rupture, after first resolving the pre-seismic triggering following Chapter 2. I then address how the fluid effect enters the model formulation and discretization and how it impacts the computational procedures ranging from preconditioner design to solver selection. In each chapter, I also conduct numerical experiments and investigate the effects of faults and/or poroelastic coupling on model responses. This thesis provides new insights into various aspects of fluid-induced earthquakes and the presented computational modeling framework offers a first step toward a more comprehensive and capable tool for modeling this type of seismic event in the future.

Keywords: Geophysics.
Advisor: Zoback Mark D. 
Borja Ronaldo I. (Ronaldo Israel)
Dunham Eric 
Sleep Norman H.