VictorJuiz/thesis huggingface dataset:
Computation in constrained stochastic model predictive control of linear systems [electronic resource]
Keywords: Aeronautics and Astronautics

Despite its sub-optimality, Model Predictive Control (MPC) has received much attention over the recent decades due to its ability to handle constraints. In particular, stochastic MPC, which includes uncertainty in the system dynamics, is one of the most active recent research topics in MPC. In this dissertation, we focus on (1) increasing computation speed of constrained stochastic MPC of linear systems with additive noise and, (2) improving the accuracy of an approximate solution involving systems with additive and multiplicative noise. Constrained MPC for linear systems with additive noise has been successfully formulated as a semidefinite programming problem (SDP) using the Youla parameterization or innovation feedback and linear matrix inequalities. Unfortunately, this method can be prohibitively slow even for problems with moderate size state. Thus, in this thesis we develop an interior point algorithm which can more efficiently solve the problem. This algorithm converts the stochastic problem into a deterministic one using the mean and the covariance matrix as the system state and using affine feedback. A line search interior point method is then directly applied to the nonlinear deterministic optimization problem. In the process, we take advantage of a recursive structure that appears when a control problem is solved via the line search interior point method in order to decrease the algorithmic complexity of the solution. We compare the computation time and complexity of our algorithm against an SDP solver. The second part of the dissertation deals with systems with additive and multiplicative noise under probabilistic constraints. This class of systems differs from the additive noise case in that the probability distribution of a state is neither Gaussian nor known in closed form. This causes a problem when the probability constraints are dealt with. In previous studies, this problem has been tackled by approximating the state as a Gaussian random variable or by approximating the probability bound as an ellipsoid. In this dissertation, we use the Cornish-Fisher expansion to approximate the probability bounds of the constraints. Since the Cornish-Fisher expansion utilizes quantile values with the first several moments, the probabilistic constraints have the same form as those in the additive noise case when the constraints are converted to deterministic ones. This makes the procedure smooth when we apply the developed algorithm to a linear system with multiplicative noise. Moreover, we can easily extend the application of the algorithm to a linear system with additive plus multiplicative noise.
Computational fluid dynamic simulations investigating the diagnosis, treatment, and long term outcomes associated with aortic coarctation [electronic resource]
Keywords: Bioengineering.

Coarctation of the aorta is a congenital heart defect where a narrowing occurs in the thoracic aorta. Aortic coarctation accounts for approximately 5-10% of all congenital heart defects, affecting approximately 1 in 3000 newborns. While the condition has been recognized for over 70 years, many clinical questions still remain about the management of patients with aortic coarctation. There exists a need to investigate the complex hemodynamics associated with this disease using computational fluid dynamics to improve the diagnosis, treatment, and long-term management of these patients. First, computational simulations were used to determine the hemodynamic significance of various aortic arch obstructions, specifically to determine the significance of aortic hypoplasia, defined as long segment aortic narrowing, compared with aortic coarctation, defined as discrete narrowing. Ventricular workload was used as a metric for the degree of significance imposed by the narrowing. Results indicated that aortic hypoplasia was more significant that aortic coarctation when the same percent narrowing was considered. In addition, the simulations revealed that aortic hypoplasia consisting of 25-50% narrowing is not likely to be hemodynamically significant under resting conditions. Next, various treatment options were investigated by using simulations to compare surgical and stent-based treatment. In particular, stents placed in the aorta create a compliance mismatch because the stent is rigid and the aorta is deformable, so computational simulations were used to determine the significance of the mismatch. The results showed that the compliance mismatch associated with a rigid stent did not produce a clinically significant change in the required ventricular workload. This study refuted the claim that the compliance mismatch associated with stenting in aortic coarctation patients negatively impacts patient hemodynamics. Finally, patients with corrected aortic coarctation often suffer from hypertension and associated cardiovascular problems in the coronary and cerebral vessels. Computational simulations were used to determine the hemodynamics in the aorta, coronary, and cerebral vessels associated with hypertension and subsequent vascular remodeling. The results showed that hypertension induced with aortic coarctation is associated with nearly equal increases in mean pressure but different increases in pulse pressure throughout the model. This study revealed interesting and important information related to the hemodynamics in a large vascular model under the effects of hypertension and vascular wall remodeling. These studies showed the power of computational simulations to aid in the investigation of clinical questions regarding aortic coarctation.
Computational methods for the analysis of musical structure [electronic resource]
Keywords: Music

Music is an art form which is realized in time. This dissertation presents computational methods for examining the temporality of music at multiple time-scales so that both short-term surface features and deeper long-term structures can be studied and related to each other. The methods are applied in particular to musical key analysis (Chapters 2-4) and also adapted for use in performance analysis (Chapters 5-6). The essential methodology is to examine all sequential time-scales within a piece using some analytic process and then arrange a summary of the analytic results into a maximally overlapped arrangement. Chapter 2 defines a two-dimensional plotting domain for displaying musical features at all possible time-scales which forms a basis for further analysis methods. The resulting structures in the plots can be examined subjectively as a navigational aid in the music as illustrated in Chapters 3 and 5. They can also be used to extract musically relevant information as discussed in Chapters 4 and 6.
Computational models of blood flow in deformable arteries incorporating viscoelastic wall properties [electronic resource]
Keywords: Mechanical Engineering

It is well known that blood vessels exhibit viscoelastic properties. Vessel wall viscoelasticity is an important source of physical damping and dissipation in the cardiovascular system. There is a growing need to incorporate viscoelasticity of arteries in computational models of blood flow which are utilized for applications such as disease research, treatment planning and medical device evaluation. However, thus far the use of viscoelastic wall properties in blood flow modeling has been limited. As part of the present work, arterial wall viscoelasticity was incorporated into two computational models of blood flow: (1) a nonlinear one-dimensional (1-D) model and (2) a three-dimensional (3-D) fluid-solid interaction (FSI) model of blood flow. 1-D blood flow model: In blood flow simulations different viscoelastic wall models may produce significantly different flow, pressure and wall deformation solutions. To highlight these differences a novel comparative study of two viscoelastic wall models and an elastic model is presented in this work. The wall models were incorporated in a nonlinear 1-D model of blood flow, which was solved using a space-time finite element method. The comparative study involved the following applications: (i) Wave propagation in an idealized vessel with reflection-free outflow boundary condition; (ii) Carotid artery model with non-periodic boundary conditions; (iii) Subject-specific abdominal aorta model under rest and exercise conditions. 3-D FSI blood flow model: 3-D blood flow models enable physiologic simulations in complex, subject-specific anatomies. In the present work, a viscoelastic constitutive relationship for the arterial wall was incorporated in the 3-D Coupled Momentum Method for Fluid-Solid Interaction problems (CMM-FSI). Results in an idealized carotid artery stenosis geometry show that higher frequency components of flow rate, pressure and vessel wall motion are damped in the viscoelastic case. These results indicate that the dissipative nature of viscoelastic wall properties has an important impact in 3-D simulations of blood flow. Future work will include simulations of blood flow in patient-specific geometries such as aortic coarctation (a congenital disease) to assess the impact of wall viscoelasticity in clinically relevant scenarios. In the present work, arterial viscoelasticity has been incorporated in 1-D and 3-D computational models of blood flow. The biomechanical effects of wall viscoelasticity have been investigated through idealized and subject-specific blood flow simulations. These contributions are significant and suggest the potential importance of wall viscoelasticity in blood flow simulations for clinically relevant applications.
Computed tomography based estimation of bone rigidity and strength under combined bending and torsion [electronic resource]
Keywords: Mechanical Engineering

A new method to evaluate bone rigidity and strength using tomographic bone images obtained via QCT (Quantitative Computed Tomography) is introduced. A newly developed computer program named VA-BATTS is used for image processing, bone segmentation, mesh creation, material assignment and calculation of far field normal and shear stresses as well as other cross sectional properties. In order to calculate torsional and transverse shear stresses in prismatic bodies having inhomogenous material properties, a new two-dimensional finite element formulation to estimate is presented. The formulation combines the torsional and transverse shear problem solutions and adds terms to account for the material inhomogeneity into one Weak Form of the problem, further discretized to yield a numerical approximation of the shear stresses problem. Results were validated using analytical models as well as three dimensional commercial code test cases yielding mean errors over the entire domain of less than 1%. This semi-automated application is publicly distributed and can be downloaded from https://simtk.org/home/va-batts. VA-BATTS implements an elliptical stress failure criterion to predict bone strength. To validate, fifty-two fresh frozen femurs were tested under combined three-point bending and torsion to failure. VA-BATTS was able to predict bone failure under combined bending and torsion (R2=0.68) as well as bone torsional (R2=0.80) and bending (R2=0.50) rigidity. Using multivariate analysis that combined the elliptical stress failure and the torsional and bending rigidities, the prediction confidence level was raised (R2=0.87), comparable to existing more complex three dimensional finite element studies. The elliptical stress criterion suggests that the distal femur is weaker, in absolute terms, than the midshaft femur suggesting an explanation of the increased rate of distal femur fractures in patients with Spinal Cord Injury. In general, the newly introduced method proved to yield more accurate predictions compared to DXA derived Bone Mineral Density measurements (R2=0.56). Fracture patterns were analyzed to show mostly spiral patterns where torsional loads were applied. In addition, the accuracy of three point bending experiments was examined. Three parameters that may introduce errors in the predictions - transverse shear, local deformation (indentation) as well as cross sectional deformation effect -- were studied using a parametric finite element model. The model shows that depending on the geometric properties of the bone, errors as high as 75% may be introduced in the estimation of the bone elastic modulus. Bone rigidity estimates may now be corrected using the correction factors supplied in this study.
Computing rare-event probabilities for affine models and general state space Markov processes [electronic resource]
Keywords: Management Science and Engineering

Rare-event simulation concerns computing small probabilities, i.e. rare-event probabilities. This dissertation investigates efficient simulation algorithms based on importance sampling for computing rare-event probabilities for different models, and establishes their efficiency via asymptotic analysis. The first part discusses asymptotic behavior of affine models. Stochastic stability of affine jump diffusions are carefully studied. In particular, positive recurrence, ergodicity, and exponential ergodicity are established for such processes under various conditions via a Foster-Lyapunov type approach. The stationary distribution is characterized in terms of its characteristic function. Furthermore, the large deviations behavior of affine point processes are explicitly computed, based on which a logarithmically efficient importance sampling algorithm is proposed for computing rare-event probabilities for affine point processes. The second part is devoted to a much more general setting, i.e. general state space Markov processes. The current state-of-the-art algorithm for computing rare-event probabilities in this context heavily relies on the solution of a certain eigenvalue problem, which is often unavailable in closed form unless certain special structure is present (e.g. affine structure for affine models). To circumvent this difficulty, assuming the existence of a regenerative structure, we propose a bootstrap-based algorithm that conducts the importance sampling on the regenerative cycle-path space instead of the original one-step transition kernel. The efficiency of this algorithm is also discussed.
Conditioning surface-based models to well and thickness data [electronic resource]
Keywords: Energy Resources Engineering

Surface-based models imitate a sequence of depositional events in time. By considering sedimentation processes, these algorithms produce highly realistic subsurface structures from a variety of environments. However, since depositional events are forward-modeled, they cannot be directly conditioned to data. Therefore, conditioning requires solving a possibly expensive inverse problem. In this study, an optimization scheme is developed that allows conditioning turbidite simulation to thickness information and well data. The methodology is applied to three real data sets.
"Confio / I trust", surrounding the limits of time [electronic resource] : a cycle of pieces for different instrumental combinations and voices
Keywords: Music

"Confío / I trust", surrounding the limits of time is a cycle of pieces in the form of modular movements, which also function as independent works and it is for different combinations of instruments and voices. This project is the result of different stages of research and direct work with performers in some cases. The cycle is focused on a reflection concerning musical language and different types of connection with poetic expression. It is engaged with a vast conception of early Western music and its spirituality and sense of poetic melancholy --sometimes also of joy-- viewed from a contemporary perspective. This project entails a non-antagonistic reflection about the relationship between composers and performers, and creators with their work. This approach to early music could contribute to an understanding of music as a vehicle of emotions, text as the principal tool to express passions, and notation as a result of a practical human tradition. Academic contemporary music, after extensive expansions through different avant-garde movements, new instrumental techniques, extreme integration of instrumental sounds and technological means, would find a creative source in this space of encounter with early music, as a way to question, reaffirm, and spread out its potentiality.
Conformational transitions in RNA probed in riboswitch systems [electronic resource]
Keywords: Applied Physics

Conformational transitions are a key phenomenon in biological processes; proteins and nucleic acids require structural malleability that not only enables them to adopt specific three-dimensional structures that impart activity, but also accommodates conformational transitions that enhance their functions and allow them to communicate with their surrounding environment. Protein conformational transitions have been extensively studied for a large number of systems, but RNA conformational transitions are less well understood. In this dissertation, I have studied conformational transitions in RNA occurring at the levels of both secondary and tertiary structure. A thiamine pyrophosphate and an adenine riboswitch have been used to follow the folding of RNA from an ensemble of partially structured heterogeneous conformers in the ligand-free state to fully folded native states in the ligand-bound state. Small angle X-ray scattering and two-dimensional chemical footprinting have been used as the primary experimental techniques to query the conformational transitions occurring in these two RNA systems. Being solution techniques, these methods are particularly suitable for probing heterogeneous ensembles of RNA structures that exist at thermodynamic equilibrium in variable salt and ligand concentrations. The results provide detailed characterization of partially folded RNA structures and the conformational transitions that mediate their conversion to natively folded forms.
Consequences of rewards [electronic resource] : the creation, perpetuation, and erosion of social inequality
Keywords: Sociology.

This dissertation focuses on how status and rewards jointly impact the creation, perpetuation and erosion of social inequality. Rewards are objects or positions that come to have differential levels of prestige when they are affiliated with groups of varying status, such as certain types of educational degrees, technologies, awards, and the like. Expectations about who we are and what we should be able to achieve are formed based on a combination of both our characteristics and displayed status markers. The first study experimentally tests whether rewards have the power to create entirely new status characteristics and bases of inequality. The second study is an examination of how assessments of competence and trustworthiness systematically bias the distribution of rewards and, thereby, the perpetuation of inequality, by examining how lenders perceive loan applicants and make funding decisions in experimentally created lending markets. The third study explores whether rewards have the power to neutralize status-based inequality when low status individuals are rewarded with markers of a much higher honorific value than members of high status groups.
A conservative meshless framework for conservation laws with applications in computational fluid dynamics [electronic resource]
Keywords: Aeronautics and Astronautics

Mesh generation, which is essential to most traditional numerical discretizations, often remains the bottleneck of the simulation process. Many researchers have developed meshless algorithms to circumvent mesh generation. Unfortunately, almost all existing meshless methods suffer from the lack of formal discrete conservation, which can lead to unpredictable numerical errors in the presence of discontinuities. This thesis addresses the issue of non-conservation in existing meshless methods. It focuses on the formulation and implementation of a novel conservative meshless scheme and its applications in computational fluid dynamics (CFD). The scheme, first of such nature documented in the literature, is formulated based on obtaining derivative approximations using function values and generated coefficients satisfying a set of reciprocity and polynomial consistency conditions. The required coefficients are generated by the solution of a global quadratic program. They minimize an upper bound of a representation of the global discretization error in addition to satisfying the necessary conditions. A generalization of the derivative approximation allows the use of arbitrary consistent interface values in the derivative operator while maintaining discrete conservation. This creates a flexible framework within which a wide variety of numerical flux schemes, such as those previously developed for finite volume discretization, can be used with no additional costs. The practicality of this new framework is demonstrated by solving compressible flow problems using, without modifications, a piece of software designed for finite volume discretization. The meshless numerical results show superconvergence and compare well with those obtained using meshed finite volume discretizations and other meshless schemes, highlighting the validity of the new framework and its potential to be applied to problems of greater complexity and scale.
Consistency and convergence rate of Markov chain quasi Monte Carlo with examples [electronic resource]
Keywords: Statistics

Markov Chain Monte Carlo methods have been widely used in various scientific disciplines for generation of samples from distributions that are difficult to simulate directly. The random numbers driving Markov Chain Monte Carlo algorithms are modeled as independent $\mathcal{U}[0,1)$ random variables. The class of distributions that could be simulated are largely broadened by using Markov Chain Monte Carlo. Quasi-Monte Carlo, on the other hand, aims to improve the accuracy of estimation of an integral over the multidimensional unit cube. By using more carefully balanced inputs, under some smoothness conditions the estimation error is converging at a higher rate than plain Monte Carlo. We would like to combine these two techniques, so that we can sample more accurately from a larger class of distributions. This method, called Markov Chain quasi-Monte Carlo (MCQMC), is the main topic of this work. We are going to replace the IID driving sequence used in MCMC algorithms by a deterministic sequence which is designed to be more uniform. Previously the justification for MCQMC is proved only for finite state space case. We are going to extend those results to some Markov Chains on continuous state spaces. We also explore the convergence rate of MCQMC under stronger assumptions. Lastly we present some numerical results for demonstration of MCQMC's performance. From these examples, the empirical benefits of more balanced sequences are significant.