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Computational Exploration of Thermodynamic Models of Geological CO₂ Injection
No full textThis thesis investigates the behavior of carbon dioxide flow in porous media through high-fidelity computational modeling, with a specific focus on the impact of the Span-Wagner equation of state (EOS). Accurate modeling of CO₂ transport in subsurface environments is essential for applications such as carbon capture and storage (CCS). We model the entire flow from injection, down throughout a vertical pipe and into a porous reservoir. To this end, we utilize the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework developed by Idaho National Laboratory to perform finite element simulations. A key contribution of this work is the successful coupling of a porous rock domain with a one-dimensional pipe flow simulation in Julia, enabling a broader representation of injection scenarios. The study examines how the thermodynamic accuracy of the Span-Wagner Equation of State influences flow characteristics, in comparison to the Ideal Gas Equation of State. Through a series of coupled pipe-reservoir simulations, we assess variations in pressure and density as CO₂ is injected from the pipe into the porous medium. The model can detect phase change conditions, allowing us to predict the maximum mass flux that can be achieved below the liquefaction threshold, as defined by the binodal curve in the CO₂ phase diagram at a given temperature. The results highlight the importance of EOS selection in predicting multiphase flow behavior, especially under conditions relevant to geological storage. Furthermore, we find that the Ideal Gas EOS underpredicts injection rates under the same conditions. This integrated modeling approach advances the understanding of thermodynamic effects in coupled subsurface flow systems and supports the development of reliable tools for large-scale carbon storage applications.M.Eng
Pyrosome: Verified Compilation for Modular Metatheory
No full textWe present Pyrosome, a generic framework for modular language metatheory that embodies a novel approach to extensible semantics and compilation, implemented in Coq. Common techniques for semantic reasoning are often tied to the specific structures of the languages and compilers that they support. Contextual equivalence is difficult to work with directly, and both logical relations and transition system-based approaches typically fix a specific notion of effect globally. While modular transition systems have been effective in imperative settings, they are suboptimal for functional code. These limitations restrict the extension and composition of semantics in these systems. In Pyrosome, verified compilers are fully extensible, meaning that to extend a language simply requires defining and verifying the compilation of the new feature, reusing the old correctness theorem for all other cases. The novel enabling idea is an inductive formulation of equivalence preservation that supports the addition of new rules to the source language, target language, and compiler.
Pyrosome defines a formal, deeply embedded notion of programming languages with semantics given by dependently sorted equational theories, so all compiler-correctness proofs boil down to type-checking and equational reasoning. We support vertical composition of any compilers expressed in our framework in addition to feature extension. Since our design requires compilers to support open programs, our correctness guarantees support linking with any target code of the appropriate type. As a case study, we present a multipass compiler from System F with simple references, through CPS translation and closure conversion. Specifically, we demonstrate how we can build such a compiler incrementally by starting with a compiler for simply typed lambda-calculus and adding natural numbers, the unit type, recursive functions, and a global heap, then extending judgments with a type environment and adding type abstraction, all while reusing the original theorems. We also present a linear version of the simply typed CPS pass and compile a small imperative language to the simply typed target to show how Pyrosome handles substructural typing and imperative features
Decentralized Declustering of Multiple Underactuated Autonomous Surface Vehicles
No full textMulti-agent systems have seen a significant rise in research interest, enabled by the increasing availability of low-cost autonomous platforms and motivated by a wide range of emerging applications. However, the coordinated deployment of large numbers of autonomous vehicles in marine environments remains a nontrivial and high-risk problem, yet it is often overlooked in the literature. These vehicles are typically deployed from a single location, and their underactuated nature, close proximity, and susceptibility to external disturbances make it difficult to achieve a mission-ready configuration without collisions. In this thesis, we address the problem of transitioning a set of underactuated Autonomous Surface Vehicles (ASVs) from arbitrary and inconvenient initial conditions to a deconflicted set of deployed vehicles. We propose a decentralized and scalable method that calculates and assigns target positions to the vehicles, generates optimal paths that comply with minimum turning radius constraints, and ensures collision avoidance between the vehicles through a shared speed policy. Contributions also include a formal definition and quantification of clustering and declustering in multi-agent systems. The approach is implemented using the MOOS-IvP autonomy framework, and performance is evaluated through simulation with up to vehicles and extensive field trials with eight vehicles. Results demonstrate that our approach reduces the time to decluster for the most challenging initial conditions by 50% compared to the current manual method. By improving efficiency and robustness while eliminating human involvement, this work streamlines ASV fleet deployments, enabling more scalable multi-agent field operations.S.M
A Parametric, second-order cone representable model of fairness for decision-making problems
No full textThe article develops a parametric model of fairness called “ ε -fairness” that can be represented using a single second-order cone constraint and incorporated into existing decision-making problem formulations without impacting the complexity of solution techniques. We develop the model from the fundamental result of finite-dimensional norm equivalence in linear algebra and show that this model has a closed-form relationship to an existing metric for measuring fairness widely used in the literature. Finally, a simple case study on the optimal operation of a damaged power transmission network illustrates its effectiveness
As global ambient temperatures continue to rise, with the highest recorded annual averages since 1850 being within the last ten years, problems emerge for species exhibiting temperature-dependent sex determination. This is the process by which the sex of an animal’s embryo is determined based on the temperature of environment in which it is incubated, which can result in skewed sex ratios within a population like in the case of the critically endangered Hawksbill Sea Turtles (Eretmochelys imbricata). Reportedly, 85-95% of Hawksbills sampled in the wild are currently female [3]. This sex-imbalance can negatively impact the species’ ability to procreate, leading to the potential for extinction. Currently, no viable, long-term solutions exist to effectively and safely cool sea turtle eggs while still keeping them within their natural habitat. This research proposes the creation of sea turtle egg incubators designed to achieve a temperature range that will produce a higher percentage of male hatchlings to help rectify this imbalance in habitats heavily affected by climate change. These incubators are designed to be affordable, easy to build and, most importantly, safe for the sea turtle eggs. Three-month-long temperature trials for the incubator were conducted in Jamaica with conservationist community partners at Oracabessa Bay Sea Turtle Project. Results showed that this incubator is not only easy to manufacture and use, but that it successfully regulates the temperature range in favor of more male hatchlings, while also increasing the emergence rate of the hatchlings from 70% in natural nests to over 80%. During one of the hottest months in Jamaica, the incubator, deployed without water changes, doubled the predicted percentage of males produced by natural nests. When provided with cool water changes the incubator quintupled this value. Throughout the months of August to October, the incubator achieved a temperature range that is predicted to produce 85-99% male hatchlings, thus counteracting the feminization phenomenon occurring in nature.
No full textFoams, widely used in packaging, insulation, protective gear, and medical implants, are versatile materials but mechanically inefficient due to their bending-dominated microstructure, leading to an exponential loss of stiffness and strength at low relative densities. Architected materials address this limitation through engineered microstructures that achieve near-linear scaling of properties with relative density. However, truss- and plate-based designs suffer from stress concentrations, while shell-based architectures, though more mechanically efficient, remain highly sensitive to defects and are challenging to fabricate at scale via additive manufacturing. Spinodal architected materials, derived from scalable spinodal decomposition processes, offer a promising alternative with aperiodic, double-curvature microstructures that enhance mechanical efficiency at low relative densities. Nevertheless, their behavior beyond the elastic regime remains largely unexplored. This thesis investigates the nonlinear mechanics of spinodal architected materials by combining a comprehensive experimental dataset with computational modeling. A total of 107 unique morphologies were fabricated and subjected to uniaxial compression along three principal directions, resulting in a dataset of 321 stress-strain curves. Morphologies were generated via simulated spinodal decomposition, allowing controlled variation of anisotropy. Explicit finite element simulations, validated against experimental data, revealed that plastic energy dissipation dominates the large-strain mechanical response. To quantitatively link local morphology to global mechanical behavior, we introduce the Normal Participation Factor (NPF) — a scalar geometric parameter that captures the alignment between surface normals and the loading direction. We demonstrate that the NPF is a material-agnostic proxy for equivalent plastic strain and is linearly correlated with the total energy dissipated during deformation. Combining insights from both experiments and simulations, we establish the NPF as a first-order predictive tool for mechanical behavior under large strains, enabling structure-property predictions without reliance on costly simulations or extensive experimental testing. Altogether, this work lays the foundation for developing finite-strain structure-property relationships in spinodal architected materials, advancing their potential for real-world applications.S.M
Multipartite Quantum Clock Synchronization viaCollective Symmetric States
No full textThis thesis investigates multipartite quantum clock synchronization (QCS) tasks using a class of quantum states, called collective symmetric (CS) states, which generalize Dicke and N00N states. Employment of CS states in previous QCS procedures is shown to improve synchronization performance in various network scenarios. The focus of the paper is on QCS procedures that, after the distribution of quantum states, rely exclusively on local operations and classical communication (LOCC), ensuring compatibility with highly noisy quantum channels. Two synchronization scenarios are considered: (i) synchronization between the two nodes of an arbitrarily chosen pair of nodes, and (ii) global synchronization where all nodes wish to synchronize their clocks to a common average time. First, a framework in which the previous procedures operate employing the CS states is introduced. Using such framework, possible limitations of the QCS procedures in terms of estimation ambiguity and lack of robustness are pointed out. Second, a procedure referred to as the tactical delay procedure (TDP) is proposed for each of the two synchronization scenarios. The TDP resolves the mentioned limitations and outperforms the state-of-the-art multi-partite QCS procedures in terms of synchronization precision without requiring additional quantum resources.S.M
Riemannian Trust Region Methods for SC 1 Minimization
No full textManifold optimization has recently gained significant attention due to its wide range of applications in various areas. This paper introduces the first Riemannian trust region method for minimizing an SC 1 function, which is a differentiable function that has a semismooth gradient vector field, on manifolds with convergence guarantee. We provide proof of both global and local convergence results, along with demonstrating the local superlinear convergence rate of our proposed method. As an application and to demonstrate our motivation, we utilize our trust region method as a subproblem solver within an augmented Lagrangian method for minimizing nonsmooth nonconvex functions over manifolds. This represents the first approach that fully explores the second-order information of the subproblem in the context of augmented Lagrangian methods on manifolds. Numerical experiments confirm that our method outperforms existing methods
Development of the Deployable HF Vector Sensor for the AERO-VISTA Spacecraft
No full text2024 IEEE Aerospace Conference, Big Sky, MT, USA, 2-9 MarchThe Auroral Emissions Radio Observer (AERO) and Vector Interferometry Space Technology using AERO (VISTA) CubeSat missions will use two identical 6U CubeSats developed to measure HF auroral emissions from Low Earth Orbit for NASA’s Space Mission Directorate (SMD) for Heliophysics. Each CubeSat employs a unique antenna, called a Vector Sensor Antenna (VSA), to measure all six electromagnetic degrees of freedom of incoming HF radiation via a combination of loop, dipole and monopole antennas. The VSA payload stows into a compact volume within the 6U spacecraft, and through a series of deployments, makes a 4 m by 4 m by 2.3 m antenna array. The relatively large antenna element deployment from such a small initial volume is achieved using fiberglass composite tape springs which unroll to form the antenna elements. These tape springs fall into a class of structural elements called High Strain Composites, which are becoming more commonly used in space missions. This paper describes the development, integration and testing of the AERO-VISTA VSA payload prototype
Geothermal Energy Planning Considerations for Military Operational Energy Demands
No full textContingency locations are temporary military bases that are often established in austere or contested environments. These locations rely heavily on diesel fuel for electrical power, which creates logistical vulnerabilities and increases the risk to personnel conducting fuel resupply missions. While the Department of Defense has made progress in adopting renewable energy technologies, many of these systems remain too large, inefficient, or underdeveloped for widespread use in operational environments. Geothermal energy presents a promising but underexplored alternative for generating reliable, on-site electrical power without the need for continuous fuel resupply.
This thesis evaluates the feasibility of geothermal energy systems for military operational energy demands and introduces a modified power planning process that incorporates geothermal considerations. The research focuses on closed-loop geothermal systems, utilizing an example system called the “Mil-Loop”, which is designed to minimize the system surface footprint and support remote installations. The planning process integrates existing geothermal tools, including GEOMAP/TEST for resource estimation and GEOPHIRES for system modeling and performance analysis. The Mil-Loop System Model incorporates each step of the planning process to produce a site-specific power system profile.
A case study using site-specific data from Bagram Airfield was used to assess the performance of a hybrid geothermal-diesel power system. The results suggest that geothermal system integration could reduce diesel fuel consumption by up to 42.9 percent over a 40-year site lifecycle. A sensitivity analysis indicates that geothermal system power output, drilling time, and installation costs are the most critical parameters affecting system viability. Advances in drilling technology and heat extraction have the potential to reduce installation costs and timelines, making geothermal more competitive with diesel generation. This thesis also identifies a gap in military energy planning resources, specifically the lack of frameworks that include geothermal options for operational environments. It recommends that the DoD begin integrating geothermal technologies into its energy planning strategies and develop modular systems that can be deployed in contested or resource-constrained areas.
While this research is limited by simplified power demand modeling and generalized tool assumptions, it offers a practical framework for evaluating geothermal viability in future defense applications. This study demonstrates that geothermal energy systems, particularly closed-loop configurations, can serve as a viable and strategically beneficial power source for military operations. When paired with targeted technology development and thoughtful integration into planning processes, geothermal systems can reduce logistical burdens, improve energy resilience, and enhance mission success in operational environments.S.M
On Monoid Algebras Having Every Nonempty Subset of N ≥ 2 as a Length Set
No full textWe construct monoid algebras that satisfy the ascending chain condition on principal ideals and have the property that every nonempty subset of N ≥ 2 occurs as a length set