VictorJuiz/thesis huggingface dataset:
Multifidelity Framework for Uncertainty Quantification with Multiple Quantities of Interest

A systematic framework, involving ﬂow simulation and model selection at many ﬁdelity (resolution) levels, is introduced to accurately quantify the impact of geological uncertainty on multiple output quantities of interest (QoIs). The methodology considers large numbers of realizations (O(1000) in the cases presented), though very few (O(10)) simulations are performed at the highest resolutions. We proceed from coarser to ﬁner resolution levels, and at each stage simulation results are used to select a subset of realizations to simulate at the next (higher) ﬁdelity level. Models are constructed at all resolution levels through upscaling of the underlying ﬁne-scale realizations. A global transmissibility upscaling procedure is applied for this purpose. Approximate cumulative distribution functions (CDFs) are constructed for all QoIs considered. The QoI values themselves are always computed at the ﬁnest scale, but corresponding percentile values are determined using results at a rank-preserving (coarser) ﬁdelity level. Detailed results are presented for oil-water ﬂow in two channelized system examples. Simulations at seven diﬀerent ﬁdelity levels are used, and eight QoIs are evaluated. Results for the examples considered demonstrate accurate reconstruction of ﬁne-scale CDFs for all QoIs, with a speedup factor of about 18 relative to performing all simulations on the ﬁne scale.

Keywords: reservoir simulation
multilevel
multifidelity
uncertainty quantification
representative models
Thesis
Advisor: Durlofsky Louis J.
Mallison Bradley T.
Multifunctional energy storage composites with built-in health monitoring capabilities

Vehicle electrification provides a means to transition away from fossil fuels. However, the widespread adoption of electric vehicles requires sustainable solutions to their short driving range, slow charging, high purchase cost, and safety concerns. Traditional research efforts have focused on developing new battery materials with higher energy densities which are inherently more mechanically fragile, undergo large volume expansion, and are difficult to monitor. These batteries in turn require proportionally larger weight overhead in the form of protection, restraining devices, and a contingency reserve capacity at the vehicle level. Thus, to maximize the performance of existing and new battery chemistries, it is desirable to i) make batteries more mechanically robust while maintaining minimal volume expansion and ii) accurately measure physical changes inside the battery and monitor battery health using built-in sensors. The first part of this work proposed and investigated a novel structurally-integrated Li-ion battery, called multifunctional energy storage composites (MESCs). MESCs encapsulate lithium-ion battery materials inside high-strength carbon-fiber composites using interlocking polymer rivets to mechanically stabilize the electrode layer stack. These rivets enable load transfer between battery layers, allowing them to contribute to load carrying capabilities. First-generation MESCs showed comparable electrochemical performance to standard lithium-ion cells, while also demonstrating significantly higher mechanical stiffness and the ability to restrain intercalation-induced expansion of electrodes. MESCs were also capable of maintaining their structural integrity and energy-storage capabilities under realistic repeated loading. The second part of this thesis developed and evaluated an acousto-ultrasonic system that measures battery state of charge and, in particular, its state of health using a built-in, low-profile piezoelectric transducer system. A diagnostic method was proposed that relates changes in the guided wave signals to the charge, discharge, and aging processes, via electrochemically-induced changes in mechanical properties. A matching-pursuit-based feature extraction scheme was developed to allow an efficient, in-operando decomposition of signals into a set of predictors correlated with battery states. A particle filter framework was established which provides state estimation and remaining life prognostics to allow ultrasonic features to be used as measurements. It was shown on several types of off-the-shelf batteries and MESCs that the ultrasonic technique significantly improved the prediction performance and contained uncertainties.

Keywords: Aeronautics and Astronautics.
Advisor: Chang Fu-Kuo 
Senesky Debbie 
Springer George S.
Multi-functional protective coatings for plastics using open-air spray plasma deposition

Transparent plastics are increasingly important to emerging technologies such as light-weight transportation, flexible electronics, and display technologies. However, due to the low surface hardness, plastics can be easily scratched and degraded which significantly reduce their optical qualities and lifetimes. In this dissertation, I will focus on the development of durable functional protective coatings for plastics and new understandings of their mechanical properties including adhesion, stiffness, and moisture-assisted cracking behavior. I will demonstrate two scalable processing strategies for synthesizing these coatings, namely, spray deposition of sol-gel precursors and open-air plasma deposition. Firstly, I will focus on the processing of an organosilicate-based bilayer coating with unprecedented combination of adhesion and stiffness using open-air spray and plasma depositions. The bilayer coating exhibited a > 90% transparency in the visible wavelengths, 8-fold the adhesion energy and 4-fold the Young's modulus of commercial sol-gel polysiloxane coatings. The coating deposition rate, elastic modulus, hardness and adhesion to poly methyl methacrylate (PMMA) substrates will be discussed and correlated to the molecular structures and chemical compositions of the coatings. Secondly, I will demonstrate the molecular design strategies for engineering coating's deformation rate sensitivity and fracture resistance in a moist environment. With increasing non-hydrolysable organic network connectivity, the mechanical behavior of the coatings can vary from almost perfectly elastic to increasingly viscoelastic in a controlled fashion. The related fracture resistance was also found to be significantly improved. New insights into the fundamental molecular-scale relaxation and cracking mechanisms of the coatings will also be highlighted. Finally, I will describe a novel and versatile dual-source deposition method involving ultrasonic spraying and open-air plasma deposition for making durable multifunctional nanocomposite coatings. Previous work for making nanocomposites focused on incorporating nanoparticles by either in-situ growth in the matrix or by dispersing into the matrix precursor before deposition. However, in this new method, the nanoparticles and coating matrix are independently deposited which eliminate the potential difficulties associated with preparing high mass fraction composites with well-dispersed nanoparticles. The capability of incorporating several different functional nanoparticles into durable coating matrix with good nanoparticle dispersity, uniformity and strong matrix-nanoparticle interfacial interactions will be highlighted. The effect of nanoparticle concentration, size, and film thicknesses on coatings surface morphology, optical properties and mechanical properties will also be discussed.

Keywords: Materials Science and Engineering.
Advisor: Dauskardt R. H. (Reinhold H.) 
Salleo Alberto
Stebbins Jonathan Farwell
Multimodal imaging of immune cell therapies against cancer

Immunotherapies focus on reprogramming a patient's immune system to better recognize and target tumor cells. In particular, T-cells can be engineered ex vivo to either target a specific tumor antigen (via a chimeric antigen receptor) or a diverse tumor antigen repertoire (via a dendritic cell vaccine). As novel adoptive T-cell strategies progress through preclinical development and clinical trials, the ability to accurately monitor therapeutic response becomes of even greater need. Molecular imaging allows for real-time insight of the local and systemic patient response to immunotherapies, providing more dynamic information than anatomic tumor volume alone. Here I will discuss molecular imaging strategies for the in vivo monitoring and visualization of immunotherapies and their impact to elucidate the therapeutic efficacy of clinically-relevant adoptive T-cell therapies. First, I will discuss the PET reporter gene imaging and drug-induced ablation of chimeric antigen receptor (CAR) T-cells in solid tumors through the HSV1-sr39tk gene. This dual-function system can provide insight into systemic CAR T-cell migration and proliferation during clinical trials while serving as a suicide switch to limit potential toxicities. Secondly, I will present the first longitudinal fluorescence-based intravital microscopy imaging of CAR T-cells within an orthotopic glioblastoma preclinical model to illustrate the necessity of radiation therapy for complete therapeutic response. This preclinical imaging technique can help us understand immune cell dynamics within the tumor microenvironment with a high-level of spatial and temporal resolution. Third, I will utilize intravital imaging to understand the potential for dendritic cell vaccines in the treatment of glioblastoma. These strategies highlight the potential of molecular imaging both to lend insight on fundamental adoptive T-cell biology and to translate these therapies into the clinic.

Keywords: Bioengineering.
Advisor: Gambhir Sanjiv Sam 
Fordyce Polly 
James Michelle (Michelle Louise)
Multimodal modeling and uncertainty quantification for robot planning and decision making

Advances in mobile robot autonomy are poised to transform society: there is enormous demand for robots that can handle our commutes, manage our homes, provide assistance to our loved ones, and explore places too dangerous or too distant for us humans to set foot. Before this potential may be realized, however, robots must be able to contend with uncertainties arising from the unstructured, unpredictable, and often unforgiving world they aim to enter. This dissertation develops concepts, algorithms, and modeling frameworks for quantifying uncertainty in how a robot plans its course of action, how it carries out that plan, and how it interacts with its environment (in particular, with the humans around it). In each of these cases, these tools are motivated by the purpose of yielding actionable insights that improve the quality and computational efficiency of robot planning and decision making.

Advisor: Pavone Marco
Gerdes J. Christian 
Schwager Mac
A multimodal understanding of allergic disease

Allergic diseases such as allergic rhinitis, food allergies, and allergic asthma are characterized by an inappropriate immune response towards otherwise harmless environmental substances. Food allergies are a particularly extreme form of allergic disease as exposure to minute amounts of an allergen can lead to the rapid onset of potentially fatal anaphylaxis. In this thesis I address outstanding questions related to food allergies and their practical consequences using multiple modalities. First, I discuss the use of targeted mass spectrometry to answer a recurring question that plagues allergic consumers: is a food with precautionary allergen labeling, such as "may contain, " safe to consume? Second, I discuss the use of single-cell RNA sequencing to isolate and characterize rare B cells in a manner that informs our mechanistic understanding of allergic memory while also providing insight into individual IgE antibodies that directly mediate allergic reactivity.

Keywords: Bioengineering.
Advisor: Quake Stephen Ronald 
Altman Russ 
Wang Bo (Researcher in bioengineering)
Multiple testing with structure and exploration

The last couple decades have seen the proliferation of high-throughput biological assays as well as the use of electronic medical records for research purposes. For example, the UK Biobank data set contains both genotype and electronic medical record data for half a million individuals. Such data give scientists an unprecedented ability to probe large numbers of scientific hypotheses simultaneously. The statistical field of multiple testing addresses the question of how to sort through all these potential associations without making too many false discoveries. However, modern data sets create new multiple testing challenges for which existing tools are insufficient. In this thesis, we explore some such challenges in the context of two themes: structure and exploration. While many traditional multiple testing methods implicitly treat their hypotheses exchangeably, structure is ubiquitous in hypotheses of interest for biomedical applications. These structures should be accounted for by multiple testing procedures for better power and interpretability. Additionally, most traditional testing procedures formally prohibit exploration of the data, as this would invalidate their inferential guarantees. On the other hand, the analysis of scientific data often involves at least some exploration, which leads to the need for procedures that can provide inferential guarantees while accommodating exploration. In this dissertation, we elaborate on these new challenges, review some existing work to address them, and present new proposals towards this end.

Keywords: Statistics.
Advisor: Sabatti Chiara 
Candès Emmanuel J. (Emmanuel Jean) 
Montanari Andrea
Multipoint optimal control with applications to space flight

Pontryagin's Maximum Principle is generalized to multipoint optimal control with a proof given that is based entirely on the original principle. Accommodations are made for interdependency of constraints and parametric representation of the dynamics and cost function. The approach naturally applies to impulsive as well as continuous control. Periodic optimal control is an important consequence. Cost sensitivity of the performance index is also proven and demonstrated to be useful in understanding and solving optimal control problems. Three applications from space flight are solved to demonstrate the theory: optimal attitude scheduling of an imaging satellite, optimization of impulsive orbital transfer, and finding periodic orbits near the Earth-Moon Lagrange points.

Keywords: Aeronautics and Astronautics.
Advisor: Lall Sanjay 
West Matthew
D'Amico Simone
A multi-scale examination of protein surface layer assembly and function in bacteria and archaea

Surface layers (S-layers) are nanoporous shells of crystalline protein surrounding a great diversity of bacteria and nearly all known archaea. As the outermost component of the cell envelope, S-layers are one of the most abundant biopolymers on earth and are implicated in functions ranging from providing the structural integrity of the cell to mediating host-pathogen interactions. In this thesis, I report a multi-scale analysis of S-layers from the model bacterium Caulobacter crescentus and a more recently cultivated thaumarchaeote, Nitrosoarchaeum limnia. By first biophysically characterizing the S-layer protein (SLP) from C. crescentus, RsaA, I discovered that environmental calcium mediates multiple physical states of the S-layer. I leveraged this knowledge to reconstitute and specifically image S-layer assembly in living cells. Super-resolution fluorescence microscopy and single-molecule tracking demonstrated that remarkably fast and efficient continuous 2D protein crystallization governs S-layer self-assembly. I further examined the rapid 2D crystallization of RsaA using a combination of time-resolved small angle x-ray scattering (SAXS) and electron cryo-microscopy (Cryo-EM). These observations revealed that a multi-step crystallization pathway involving a short-lived crystalline intermediate is responsible for rapid self-assembly of RsaA. Robust S-layer lattice formation has implications for essential cell functions such as energy production, which in the ammonia-oxidizing archaeaon N. limnia likely occurs within the pseudo-periplasmic space between the cell's only lipid membrane and the extracellular S-layer. Electrodiffusion simulations of the N. limnia cell envelope suggest that the S-layer facilitates diffusion of its main energy source, ammonium ions, through the nanopores of the S-layer by creating a charged protein surface. As such, we propose ion transport as an evolutionary basis for conservation of charged amino acids among archaeal SLPs. Taken together, these findings inform the development of antibiotics mediating S-layer biology and provide insight into possible avenues to design biologically inspired self-assembling macromolecular nanomaterials.

Keywords: Structural Biology.
Advisor: Wakatsuki Soichi 
Francis Christopher 
Shapiro Lucy
Multiscale geomechanical and geochemical studies of unconventional shale reservoirs

With the advancement of horizontal drilling and hydraulic fracturing, unconventional shale reservoirs are now capable of being drilled faster and produced economically at commercial rates. Although these shale resources are massive in size and globally abundant, they are still being produced with low recovery factors (less than 5\% for shale oil and less than 20\% for shale gas). This low recovery could be attributed to an incomplete understanding of the complex intrinsic properties of shale rocks. In this thesis, I focused on investigating the main factors that control pore volume (porosity) and pore-size distribution of different shale reservoirs and how this variability in pore space can be related to measured permeability and well production. I present in this thesis a laboratory workflow highlighting a series of fluid penetration and permeability measurements performed on multiple shale reservoir samples. My approach looks at characterizing and imaging the nanoscale porosity first to better understand the pore space distribution and building upwards in scale through the permeability measurements. Next, I apply my previous findings towards a specific geochemical application setting involving the hydraulic fracturing fluid composition and its effect on the shale permeability. Lastly, understanding how porosity is distributed across the shale matrix and altered during hydraulic fracturing and throughout production is crucial to identify beforehand as it will have a potential impact on enhancing the recovery factors of producing shales.

Keywords: Geophysics.
Advisor: Zoback Mark D. 
Beroza Gregory C. (Gregory Christian) 
Kovscek Anthony R. (Anthony Robert)
Multi-scale soft matter physics of biological systems with applications in models of human disease

Biological systems are regulated by active forces that must be coordinated over a vast hierarchy of scales in length and time. However, developing a physical understanding of how these forces are integrated across scales to give rise to the emergent collective behavior of organisms remains a formidable task. In this thesis, I explore how theoretical polymer physics models can be integrated with multi-scale experimental characterization techniques to develop a physical description of biological systems that spans disparate length and time scales.

Keywords: Chemical Engineering.
Advisor: Heilshorn Sarah 
Spakowitz Andrew James 
Dunn Alexander Robert
Musculoskeletal simulation and optimization for predicting human movement

Human movement requires complex coordination between the muscular, skeletal, and neural systems. When these systems are impaired, gait pathologies can occur. Previous research has studied how neuromuscular and skeletal deficits result in abnormal, inefficient, gait patterns. However, while these studies have suggested relationships between musculoskeletal parameters and observed gait, they have been limited in understanding the cause-effect relationship between these variables. Other previous work has focused on developing devices to augment human performance, both for individuals with and without impairments, but results have been mixed, likely due to the complex human dynamics and human-device interactions. This thesis describes two musculoskeletal simulation and optimization frameworks that were developed to explore if simulations can be used to 1) probe the cause-effect relationship between muscle deficits and commonly observed pathological gait patterns and 2) help design assistive devices. For each study, the frameworks generated predictive simulations, or simulations in which movement trajectories were created without tracking any experimental data. In the first study, the framework could generate realistic simulations of walking. Plantarflexor muscle weakness or contracture, commonly observed in individuals with stroke or cerebral palsy, was then added to the model, and the model adopted gait patterns that are seen in pathologic gait. In the second study, the framework could generate realistic simulations of a standing long jump. Potential active and passive assistive devices were then added to the model, and the framework tuned the devices to increase jump distance. This work shows how simulation frameworks can be used to predict how movement would change under various conditions, leading to a deeper understanding of mechanisms behind gait pathologies and a framework to aid in designing devices to augment human performance.

Keywords: Bioengineering.
Advisor: Delp Scott 
Mitiguy Paul
Okamura Allison
Musical modernism and the search for second-person lyric

Why and how did lyric persist in the seemingly hostile conditions of musical modernism? Although modernist music is often accused of turning its back on human relationality, certain canonical works hinge on lyric moments in which one senses a voice trying to initiate second-person address. By putting lyric in the mouths of those who lack agency and voice, these moments simultaneously respond to anxieties about lyric's viability in modernity that had already begun in Schubert's time and express a hope that lyric, in its very thinglike gratuitousness, might be able to open communicative space when other modes fail. Contextualizing the modernist lyric of Schoenberg's Pierrot lunaire (1912), Berg's Wozzeck (1914--22), and Britten's Peter Grimes (1942--45) in the shifts in lyric reception around the turn of the century, I show how these works pleaded for a revision—not only of lyric form or style, but of the ethical ideals that underpinned contemporary lyric reception. Modernist lyric sought to escape the idealization of the integrated self, I argue, instead seek-ing to understand the self as always already given over to second-person relation. Yet this idea, which is latent in the rhetorical figure of apostrophe that Jonathan Culler places at the core of Romantic lyric, was in a certain sense nothing new. By mediating between schools of thought that view Schoenberg as either the last gasp of Romanticism or the pioneer of a New Music divorced from its past, my approach offers a new angle from which we might see the ethical significance of Schoenberg's legacy. While Adorno perhaps felt only despair about lyric's ethical or redemptive powers in modernity, a despair encapsulated in his famous statement that "to write poetry after Auschwitz is barbaric, " the works I study invite some-thing like hope—not in the sense of an expectation of a divinely mediated redemption, but an awakening to the un-idealized truth that lyric always retains: that I am not you, and yet I must relate to you. They show how, by opening a momentary, fragile, but real common space, lyric can create the preconditions of repair for those suffering from trauma and moral injury—precisely because it accomplishes and means nothing but is devoted only to the possibility of relationality itself.

Keywords: Music.
Advisor: Hinton Stephen
Daub Adrian 
Kronengold Charles (Charles Stewart)