2020 - Mines Theses & Dissertationshttp://hdl.handle.net/11124/1212023-03-24T12:18:10Z2023-03-24T12:18:10ZSampling combinatorial energy landscapes by classical and quantum computationJones, Eric B.http://hdl.handle.net/11124/1763422022-06-21T08:10:22Z2020-01-01T00:00:00ZSampling combinatorial energy landscapes by classical and quantum computation
Jones, Eric B.
Combinatorial and, by extension, non-convex optimization problems are among the most difficult to solve computationally due to the inadequacy of local search methods alone to find global optima. The notion of an energy landscape provides a unified language to describe the origin of combinatorial complexity across a wide variety of fields including physics, materials science, and artificial intelligence. This thesis utilizes probabilistic techniques for efficiently sampling energy landscapes that rely on classical high-performance computers and near-term quantum computers. Such sampling techniques not only provide effective heuristics for solving combinatorial optimization problems, but also enable an explanation of physical phenomena that rely on features of the energy landscape other than the global optimum. Six use cases are considered that are of relevance to the design of future clean energy systems: i) a predictive theory of materials polymorphism based on the partitioning of the continuous energy landscape into structurally equivalent regions, ii) a theory of the structure of functional glasses based on thermally averaging structurally inequivalent regions, iii) solution of the minimum dominating set variant of the optimal phasor measurement unit placement problem on the power grid by quantum-annealing over a discrete, combinatorial solution landscape, iv) a reformulation and solution of the Markov decision process formalism underlying optimal control via quantum annealing, v) a prescription for the variational preparation of fractional quantum Hall states on a digital quantum computer that accommodates the size of the Hilbert space on quantum hardware while shifting the burden of variational minimization to classical, global optimization heuristics, and vi) the simulation of quantum cellular automata on a digital quantum computer and establishment thereby as primitives that could help design noise-resilient classically-parameterized unitary circuits such as those used in quantum machine learning. Through these domain examples, the outlook established herein is that efficient methods for exploring combinatorial energy landscapes, combined with resilience-minded near-term quantum algorithm construction and intelligent division of labor between quantum and classical resources, provide a promising path towards solving some of the most challenging problems in renewable energy science.
Includes bibliographical references.; 2020 Fall
2020-01-01T00:00:00ZFunctional resilience evaluation of road tunnels through stochastic event simulation and data analysisKhetwal, Sandeep Singhhttp://hdl.handle.net/11124/1763412022-06-21T08:09:53Z2020-01-01T00:00:00ZFunctional resilience evaluation of road tunnels through stochastic event simulation and data analysis
Khetwal, Sandeep Singh
Resilience of tunnels can have significant impact on the efficiency of the entire transportation network. The ability to assess resilience of tunnels accurately is important for tunnel owners and stakeholders when they evaluate the cost-benefit of the investment made and the monetary value of future maintenance and upgrade activities. In this thesis, a simple and direct measurement metric for tunnel functionality was proposed with the focus on the usage of road tunnels. An ideal data collection framework for tunnels was proposed to support the calculation of tunnel functionality, as well as additional data-driven analysis that can be conducted to seek correlation between tunnel design and operation parameters with its resilience. As an example, existing tunnel operational data collection practice in a large tunnel in Colorado was summarized and compared with the proposed framework. Data analysis was performed for Eisenhower Johnson Memorial Tunnel (EJMT), Colorado. Since the data for the tunnels was found to be insufficient and incomplete to perform a completely data-driven analysis, a stochastic simulation model to predict tunnel resilience over time was developed by simulation of individual disruptive events. The model was a combination of modules representing disruptive events namely, accident, vehicle fire, hazmat platooning, maintenance and operations. This model was validated to the extent that is realistic using limited data from EJMT. Further, a parametric sensitivity analysis was performed to identify the impact of tunnel parameters, associated with disruptive events, on the tunnel functionality loss and resilience. The parametric study was also expanded to conduct a preliminary correlation assessment of tunnel key parameters and their performances using 22 major road tunnels in the United States.
Includes bibliographical references.; 2020 Fall
2020-01-01T00:00:00ZMathematical modeling of glucose and insulin dynamics in adolescent girls to quantify measures of insulin sensitivityBartlette, Kaihttp://hdl.handle.net/11124/1763432022-06-21T08:02:22Z2020-01-01T00:00:00ZMathematical modeling of glucose and insulin dynamics in adolescent girls to quantify measures of insulin sensitivity
Bartlette, Kai
The regulation of plasma glucose is a key component of human metabolism and is largely regulated by insulin that facilitates glucose uptake by tissues. When tissues become more resistant to insulin, glucose concentrations remain elevated longer and more insulin is required to elicit the same physiologic response. Insulin resistance (IR) is a crucial element of the pathology of the metabolic syndrome, which includes increased risk of stroke, heart disease, type 2 diabetes mellitus, and nonalcoholic fatty liver disease (NAFLD). Decreased insulin sensitivity (SI) is associated with pubertal changes, is more prevalent in teenage girls, and obesity is known to further decrease SI. The Oral Minimal Model (OMM) is a differential-equations based model that describes glucose-insulin dynamics during an oral glucose tolerance test (OGTT) to quantify SI . However, the OMM framework was developed for adult data and practical identifiability issues create challenges with applying the models to diverse metabolic phenotypes. This research focuses on extending the OMM framework to describe OGTT data from a group of adolescent girls with obesity. Initial application of OMM in this cohort established OGTT protocol duration dependence of estimates of SI . To better understand which features of the data facilitate robust model parameter identification, we conducted a local sensitivity analysis of the OMM. We found that the model was least sensitive to changes in a subset of parameters and, therefore, these parameters could be difficult to estimate reliably. This finding was confirmed in an uncertainty quantification of OMM whereby we used a Markov Chain Monte Carlo approach to obtain the precision on key parameter estimates. The addition of glucose tracers in the OGTT enables estimation of the rate of appearance of exogenous glucose (Ra_exo), a key input of OMM-type models developed for separately assessing total and hepatic SI. Published methods for approximating Ra_exo had a significant impact on estimates of both total and hepatic SI. To overcome this limitation, we developed an Ra_exo model-independent method to estimate hepatic SI in this population. These methodologies may inform the analysis and adaptation of physiological models for other applications.
Includes bibliographical references.; 2020 Fall
2020-01-01T00:00:00ZStudy of excited halo states in ¹⁰Be and ¹²Be using one-neutron transfer reactions from ¹¹Be on ⁹Be at TRIUMF ISAC-IIBraid, Ryan A.http://hdl.handle.net/11124/1763402022-06-21T08:07:43Z2020-01-01T00:00:00ZStudy of excited halo states in ¹⁰Be and ¹²Be using one-neutron transfer reactions from ¹¹Be on ⁹Be at TRIUMF ISAC-II
Braid, Ryan A.
The structures of beryllium isotopes display a complex interplay between Shell Model and cluster configurations. From ${}^{8}\mathrm{Be}$ on, the structures of Be isotopes is expected to be built on the $\alpha-\alpha$ cluster configuration with an increasing number of valence neutrons.
Interestingly, the ground state of ${}^{11}\mathrm{Be}$ and ${}^{14}\mathrm{Be}$ are also well-known halo nuclei, hence the apparent competition between cluster configurations and more traditional shell-model like structures.
For ${}^{10}\mathrm{Be}$, the ground state may retain some cluster properties, but the most developed cluster states are expected to be found near 6 MeV very close to the ${}^{9}\mathrm{Be}+n$ threshold.
Those states are therefore good candidates to study the competition of cluster and single particle configurations. To this end, the ${}^{11}\mathrm{Be}$(${}^{9}\mathrm{Be}$,${}^{10}\mathrm{Be}$)${}^{10}\mathrm{Be}$ transfer reaction was studied at 30.14 MeV at TRIUMF's ISAC-II facility utilizing a combination of charged particles ((PCB)$^2$) and $\gamma$-ray (TIGRESS) detectors.This Thesis seeks to answer if the resulting ${}^{10}\mathrm{Be}$ excited states are molecular-like, shell-model-like, or some exotic combination.
The $\gamma$-tagged angular distributions for the 2$^+_2$, $2^-$, and $1^-$ states in ${}^{10}\mathrm{Be}$ were successfully extracted and normalized to the ${}^{11}\mathrm{Be}$(${}^{9}\mathrm{Be}$,${}^{9}\mathrm{Be}$)${}^{11}\mathrm{Be}$ elastic scattering.
The transfer reaction code FRESCO was utilized to model and fit angular distributions considering the transfer of the valence $2s_{1/2}$ halo neutron in ${}^{11}\mathrm{Be}$, which couples to the unpaired $1p_{3/2}$ in the ${}^{9}\mathrm{Be}$ ground state.
This transfer was $\ell = 0$ for the negative parity states, and $\ell = 1$ for the $2^+_2$. The spectroscopic factors were found to be 0.63 $\pm$ 0.33 for the 2$^-$, 0.52 $\pm$ 0.27 for the 1$^-$, and 1.4 $\pm$ 0.7 for the 2$^+_2$ states. Given the clustered nature of ${}^{9}\mathrm{Be}$(3/2$^-$, gs) and the predicted clustered nature of the 6 MeV states in ${}^{10}\mathrm{Be}$, we conclude that the $1^-$ and $2^-$ states have a ${}^{9}\mathrm{Be}$(gs) $\otimes$ s$_{1/2}$ structure.
This makes these states potential hybrid states where clustered and halo structures (especially for the $2^-$, which lies closer to the one-neutron separation energy) appear to coexist. The 2$^+_2$ state may also display a molecular configuration with the s$_{1/2}$ halo neutron transferring as a $\ell=1$ neutron, likely filling a p$_{1/2}$ orbit in the final state. This work is partially supported by the US Department of Energy through Grant/Contract No. DE-FG03-93ER40789 (CSM).
Includes bibliographical references.; 2020 Fall
2020-01-01T00:00:00Z