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ItemContinuum modeling of electro-chemo-mechanical phenomena in all-solid-state batteries(Georgia Institute of Technology, 2023-06-07) Bistri, DonaldSolid-State-Batteries (SSBs) present a promising technology for next-generation batteries due to their superior properties including increased energy density and safer electrolyte design. Traditional SSB-architecture features a Lithium-metal anode, a solid-state composite cathode, and a stiff ceramic electrolyte. While an attractive alternative, commercialization of SSBs faces a series of chemo-mechanical issues across its constituents, namely growth induced fracture of solid-state electrolyte (SSE) due to metal deposition, interphase formation at the anode/SSE interface and damage of the various phases in composite electrodes. Computational modeling for SSBs is at its infancy and constitutes the focus of this thesis, with an emphasis on mechanical integrity of composite electrodes and deposition-induced fracture of SSE. Both cathode and anode may consist of a composite of active particles surrounded by a ceramic SSE matrix. During cycling, active particles undergo volumetric changes against the stiff SSE, which can lead to fracture. Developing models for these systems requires an understanding of three critical components, namely active particles, SSE, and the combined behavior of the composite. Towards modeling the role of mechanical damage on performance, we propose a novel coupled chemo-mechanical interface element, analogous to cohesive elements used in fracture mechanics. The framework enables for modeling galvanostatic charging of composite electrodes and captures the continuous evolution of mechanical stresses, interfacial damage, and non-uniform current distribution across particles in a microstructure. We specialize on an LCO-LGPS composite cathode and study the evolution of interfacial damage under varying material and microstructural properties. Specifically, we model electrolyte compositions with varying SSE stiffness and active particle volumetric change to assess their effect on interfacial stresses, mechanical damage, and overall electrochemical response. Subsequently, we discuss how variations in microstructural composition alter the state of interfacial damage. Both packing effects and particle size distribution are studied to understand how these factors impact integrity of the interface and performance. Towards modeling the phenomenon of Li-metal filament growth, we formulate a continuum electro-chemo-mechanical gradient theory which couples phase-field damage and electrochemical reactions. The proposed framework is fully-coupled with electrodeposition impacting mechanical deformation, stress generation and subsequent SSE fracture. Conversely, electrodeposition kinetics are affected by mechanical stresses through a thermodynamically-consistent driving force that distinguishes chemical, electrical, and mechanical contributions. Importantly, the theory captures the interplay between crack propagation and electrodeposition by tracking damage and electrodeposition via distinct phase-field variables such that filament growth is preceded by and confined to damaged regions within the SSE. An attractive feature of such approach is its ability to simulate the nucleation, propagation and branching of cracks and Li-filaments in arbitrary orientations. While the framework is general in nature, we specialize it towards modeling the growth of Li-metal filaments in an inorganic LLZO electrolyte. We demonstrate the capacity to capture intergranular and transgranular crack and Li-filament growth, both of which have been experimentally observed. In doing so, we elucidate the manner in which mechanics and fracture of the SSE impact electrodeposition kinetics and Li-filament growth mechanism. From a manufacturing standpoint, we additionally elucidate the role of mechanical boundary conditions (i.e. mechanical confinement) on the rate of crack propagation across the electrolyte versus electrodeposition of Li-metal within cracks. Under specific mechanical boundary conditions, we show the capacity of the framework to capture the experimentally observed phenomenon of crack fronts propagating ahead of Li-metal filaments, as cracks traverse the entire electrolyte in advance of Li-deposits.
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ItemAnalyzing Sparing Policy in the Operations of Space Habitats(Georgia Institute of Technology, 2023-05-08) Maxwell, Andrew JonesThe inclusion of operational sparing policies in early system definition can ensure that spares allocations can optimally meet desired system reliabilities consistent with the planned maintenance of a crewed vehicle. This approach is critical for long-duration crewed missions where mass allocations are constrained and lack of safe abort contingencies limit options in the event of significant system degradation, especially in the environmental and life support systems. The research presents both simulation-based and analytical approaches to identify optimal spares allocations for various sparing policies. The developed simulation method improves a current state-of-the-art tool from two perspectives. First, it develops a new method based on the modified knapsack problem to generate the spares allocations that maximize the probability of sufficiency given a mass capacity. Additionally, it develops a simulation model with a failure queue to enhance the flexibility of the state-of-the-art model to evaluate different sparing policies. With the developed method, comparative studies using two allocation approaches and two different policies are presented. The research also presents an analytical model for analyzing and optimizing sparing policies as part of an overall evaluation of the probability of sufficiency for a system configuration. The repair transition parameters are varied to change the state visitation probabilities which drive a change in the probability of sufficiency observed for a given mass allocation. These parameters are optimized using a particle swarm optimizer to identify the preferred strategy for a desired allocation mass.
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ItemA METHODOLOGY FOR THE MODULARIZATION OF OPERATIONAL SCENARIOS FOR MODELLING AND SIMULATION(Georgia Institute of Technology, 2022-07-29) Muehlberg, MarcAs military operating environments and potential global threats rapidly evolve, military planning processes required to maintain international security and national defense increase in complexity and involve unavoidable uncertainties. The challenges in the field are diverse, including dealing with reemergence of long-term, strategic competition over destabilizing effects of rogue regimes, and the asymmetric non-state actors’ threats such as terrorism and international crime. The military forces are expected to handle increased multi-role, multi-mission demands because of the interconnected character of these threats. The objective of this thesis is to discuss enhancing system-of-systems analysis capabilities by considering diverse operational requirements and operational ways in a parameterized fashion within Capabilities Based Assessments process. These assessments require an open-ended exploratory approach of means and ways, situated in the early stages of planning and acquisition processes. In order to enhance the reflection of increased demands in the process, the integration of multi-scenario capabilities into a process with low-fidelity modelling and simulation is of particular interest. This allows the consideration of a high quantity of feasible alternatives in a timely manner, spanning across a diverse set of dimensions and its parameters. A methodology has been devised as an enhanced Capabilities Based Assessment approach to provide for a formalized process for the consideration and infusion of operational scenarios, and properly constrain the design space prior to computational analysis. In this context, operational scenarios are a representative set of statements and conditions that address a defined problem and include testable metrics to analyze performance and effectiveness. The scenario formalization uses an adjusted elementary definition approach to decompose, define, and recompose operational scenarios to create standardized architectures, allowing their rapid infusion into environments, and to enable the consideration of diverse operational requirements in a conjoint approach overall. Pursuant to this process, discrete event simulations as low-fidelity approach are employed to reflect the elementary structure of the scenarios. In addition, the exploration of the design and options space is formalized, including the collection of alternative approaches within different materiel and non-materiel dimensions and subsequent analysis of their relationship prior to the creation of combinatorial test cases. In the progress of this thesis, the devised methodology as a whole and the two developed augmentations to the Capabilities Based Assessment are tested and validated in a series of experiments. As an overall case study, the decision-making process surrounding the deployment of vertical airlift assets of varying type and quantity for Humanitarian Aid and Disaster Relief operations is utilized. A demonstration experiment is provided exercising the entire methodology to test specifically for its suitability to handle a variety of different scenarios through process, as well as a comprehensive set of materiel and non-materiel parameters. Based on a mission statement and performance targets, the status quo could be evaluated and alternative options for the required performance improvements could be presented. The methodology created in this thesis enables the Capabilities Based Assessment and general defense acquisition considerations to be initially approached in a more open and less constrained manner. This capability is provided through the use of low-fidelity modelling and simulation that enables the evaluation of a large amount of alternatives. In advances to the state of the art, the methodology presented removes subject-matter expert and operator driven constraints, allowing the discovery of solutions that would not be considered in a traditional process. It will support the work of not only defense acquisition analysts and decision-makers, but also provide benefits to policy planners through its ability to instantly revise and analyze cases in a rapid fashion.
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ItemUNMANNED AERIAL VEHICLES: TRAJECTORY PLANNING AND ROUTING IN THE ERA OF ADVANCED AIR MOBILITY(Georgia Institute of Technology, 2022-07-28) Zeng, FanruiqiAdvanced air mobility (AAM) is a revolutionary concept that enables on-demand air mobility, cargo delivery, and emergency services via an integrated and connected multimodal transportation network. In the era of AAM, unmanned aerial vehicles are envisioned as the primary tool for transporting people and cargo from point A to point B. This thesis focuses on the development of a core decision-making engine for strategic vehicle routing and trajectory planning of autonomous vehicles (AVs) with the goal of enhancing the system-wide safety, efficiency, and scalability. Part I of the thesis addresses the routing and coordination of a drone-truck pairing, where the drone travels to multiple locations to perform specified observation tasks and rendezvous periodically with the truck to swap its batteries. Drones, as an alternative mode of transportation, have advantages in terms of lower costs, better service, or the potential to provide new services that were previously not possible. Typically, those services involve routing a fleet of drones to meet specific demands. Despite the potential benefits, the drone has a natural limitation on the flight range due to its battery capacity. As a result, enabling the combination of a drone with a ground vehicle, which can serve as a mobile charging platform for the drone, is an important opportunity for practical impact and research challenges. We first propose a Mixed Integer Quadratically-constrained Programming driven by critical operational constraints. Given the NP-hard nature of the so called Nested-VRP, we analyze the complexity of the MIQCP model and propose both enhanced exact approach and efficient heuristic for solving the Nested-VRP model. We envision that this framework will facilitate the planning and operations of combined drone-truck missions and further improve the scalability and efficiency of the AAM system. Part II of the thesis focuses on the survivability reasoning and trajectory planning of UAVs under uncertainty. Maintaining the survivability of an UAV requires that it precisely perceives and transitions between safe states in the airspace. We first propose a methodology to construct a survivability map for an UAV as a function of the vehicle's maneuverability, remaining lifetime, availability of landing sites, and the volume of air traffic. The issue of trajectory planning under uncertainty has received a lot of attention in the robotics and control communities. Traditional trajectory planning approaches rely primarily on the premise that the uncertainty of dynamic obstacles is either bounded or can be statistically modeled. This is not the case in the urban environment, where the sources of uncertainty are diverse, and their uncertain behavior is typically unpredictable, making precise modeling impossible. Motivated by this, we present a receding horizon control method with innovative trajectory planning policies that enable dynamic updating of planned trajectories in the presence of partially known and unknown uncertainty. The findings of this study have significant implications for achieving safe aviation autonomy within the AAM system.
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ItemDual Solver Computational Modeling of Ship-Helicopter Dynamic Interface Aeromechanics(Georgia Institute of Technology, 2022-05-03) Moushegian, Alex MichaelShipboard landings are a fundamental capability of naval aircraft operations and present a unique challenge to helicopter pilots due to the complex aerodynamic interactions between the ship airwake and the helicopter aerodynamics, known as the dynamic interface (DI). As such, detailed analysis and testing must be done to establish the range of safe conditions at which these maneuvers can be performed, as well as to train pilots to perform them. With the advancement of computational power in the last two to three decades, computational tools have been investigated as a way to supplement flight testing for characterization of the DI. Hybrid CFD techniques have been developed in recent years with the intent of reducing the cost of rotorcraft computational fluid dynamics (CFD) simulations through coupling of an unsteady Reynolds-averaged Navier-Stokes (uRANS) solver with various lower-order computational aerodynamic solvers. Particularly promising for DI applications is the hybrid uRANS/free-vortex wake methodology, which uses uRANS to compute the rotor wake in the near-field and a potential flow model in the far-field. This technique allows wake-body and wake-wake interactions in the DI to be modeled without the need for a highly resolved uRANS domain in the large region between the ship and the helicopter. This research describes the necessary improvements and extensions of a hybrid uRANS/free-wake solver, OVERFLOW-CHARM, required to accurately characterize DI aerodynamics. These improvements are demonstrated and validated on model problems which include fundamental physics of the DI. First, OVERFLOW-CHARM is applied to analysis of an integrated propulsion system where interactional aerodynamics influence the performance of both the propeller and the wing. Second, OVERFLOW-CHARM is applied to rotors in ground effect, where its capabilities are quantified at a range of rotor scales. This verifies that OVERFLOW-CHARM will be able to accurately capture the interaction of the rotor wake with the ship deck during shipboard landing simulations. Finally, OVERFLOW-CHARM simulations replicating a flight test of the UH-60L helicopter operating within the influence of a model LPD-17 hangar face are performed to investigate OVERFLOW-CHARM's capabilities at capturing low-speed object-induced recirculation (LOIDR) effects which impact helicopter performance in the DI.
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ItemINFORMED EXPLORATION ALGORITHMS FOR ROBOT MOTION PLANNING AND LEARNING(Georgia Institute of Technology, 2022-05-03) Joshi, Sagar SuhasSampling-based methods have emerged as a promising technique for solving robot motion-planning problems. These algorithms avoid a priori discretization of the search-space by generating random samples and building a graph online. While the recent advances in this area endow these randomized planners with asymptotic optimality, their slow convergence rate still remains a challenge. One of the reasons for this poor performance can be traced to the widely used uniform sampling strategy that na ̈ıvely explores the entire search-space. Having access to an intelligent exploration strategy that can focus search, would alleviate one of the critical bottlenecks in speeding up these algorithms. This thesis endeavors to tackle this problem by presenting exploration algorithms that leverage different sources of information available during planning time.
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ItemClosed/Semi-Closed Form Solutions for Face/Core Debonds in Sandwich Beams(Georgia Institute of Technology, 2022-05-03) Niranjan Babu, SiddarthSandwich beams are highly susceptible to debonding at the interface between face and core. These debonds can grow and eventually lead to complete failure of the structure. To understand and study such debonds analytically, an Elastic Foundation Analysis (EFA) can be used to incorporate the effects of crack tip deformation in beam theory. In this model, EFA is extended further to better capture the effects of transverse shear. Unlike most models, this approach can be applied for both isotropic and orthotropic face & core materials. The approach uses both normal and rotational springs in the elastic foundation in the bonded region of the beam to capture transverse shear effects. Timoshenko beam theory introduces a rotational degree of freedom to the beam element and the rotational springs are used to capture it. The model is comprehensive and include both the deformation of the debonded part and the substrate. Double Cantilever Beam (DCB) and Single Cantilever Beam (SCB) specimens are chosen to demonstrate the procedure to obtain Mode-I fracture parameters. In the case of Mode-II fracture, the effects of crack face contact can affect the fracture parameters and are usually neglected in analytical approaches. The proposed model extends EFA by introducing a tensionless spring foundation in the cracked region. Tensionless springs are used to capture the compressive stresses across the interface between the debonded face sheet and the substrate. The absence of tensile stresses in the foundation is because when there is tension the debonded face sheet lifts away from the substrate. Apart from compressive stresses, there will also be frictional forces acting between the crack faces. So, the governing equations are modified to capture the friction tractions in the crack faces. An End Notched Flexure (ENF) specimen is chosen to demonstrate Mode-II fracture. Expressions for energy release rates are obtained using J-Integral approach and it is modified to capture the energy lost due to the friction tractions. Solutions for mode partitioning are obtained using the axial and transverse displacements near the crack tip. Results obtained from these expressions are compared with results from finite element models. The model is comprehensive, efficient and would provide accurate results when compared with the other models (from literature).
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ItemKinetic-hydrodynamic instability interactions in near blowoff bluff body flames(Georgia Institute of Technology, 2022-05-02) Manosh Kumar, RaghulThis work examines the dynamics of confined bluff body flames in the process of lean blowoff (LBO) using simultaneous stereo-PIV (particle image velocimetry), OH PLIF (planar laser induced fluorescence) and CH2O PLIF. Flames at high density ratios blow off in at least two distinct stages: stage 1, where intermittent extinction occurs along the flame front, but the flame and flow remain qualitatively similar to stable conditions, and stage 2, where there is permanent downstream flame extinction and large-scale changes in dynamic flow characteristics. This work particularly focuses on stage 2 processes, with the goal of understanding what ultimately leads to irrecoverable flame blowoff. A new test facility was developed with the operational flexibility to achieve two goals: (1) approach LBO by keeping the parameters that influence its hydrodynamic stability approximately constant, particularly flow velocity (u_bulk) and gas expansion ratio (σ), and (2) compare near-LBO dynamics under conditions where, well away from blowoff, the flame is globally stable (high σ case) and globally unstable (low σ case, where the Bénard-Von Karman (BVK) instability of the flow is present). The latter case was of particular interest as most prior detailed diagnostic studies of LBO have been performed at high σ, BVK-suppressed conditions. We find, however, that the transient blowoff process remains largely unchanged in the high and low σ cases, presumably because the BVK instability reappears in either case under conditions very close to LBO. In all cases, blowoff is preceded by permanent downstream extinction that moves progressively closer to the bluff body as LBO is approached. We find that blowoff dynamics are intrinsically 3D, due to both secondary instabilities of the shear layer and confinement effects associated with bluff body-wall interactions. These 3D structures often manifest themselves as burning reactant fingers which are caught in the backflow of the recirculation zone; under very near LBO conditions they impinge on the back of the bluff body and extinguish. At the very edge of blowoff, the recirculation zone is no longer composed of hot products and is unable to autoignite the oncoming reactant flow, leading to global extinction. The characteristic time associated with this feedback between downstream extinction and wake structure alteration causing blowoff is about 2 orders of magnitude larger than the characteristic flow time, D/u_bulk.
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ItemRepresentative Data and Models for Complex Aerospace Systems Analysis(Georgia Institute of Technology, 2022-04-28) Gao, ZhenyuCatalyzed by advances in data quantity and quality, effective and scalable algorithms, and high-performance computation, the data-intensive transformation is rapidly reframing the aerospace industry. The integration of data-driven methods brings many new opportunities, such as (1) streamlining the aerospace design, testing, certification, and manufacturing process, (2) driving fundamental advancements in the traditional aerospace fields, and (3) enhancing the business and operations side of the industry. However, modern aerospace datasets collected from real-world operations, simulations, and scientific observations can be massive, high-dimensional, heterogeneous, and noisy. While sometimes being beyond people's capacity to store, analyze, and archive, these large datasets almost always contain redundant, trivial, and irrelevant information. Because the design and analysis of complex aerospace systems value computational efficiency, robustness, and interpretation, an additional procedure is required to process large datasets and extract/refine a small amount of representative information for in-depth analysis. This dissertation utilizes improved representations of operations data and aircraft models for efficient, accurate, and interpretable air transportation system analysis. Under the overall scope of representative data and models, this dissertation consists of three main parts. Part I, representative operations data, considers the problem of selecting a small subset of the operations data from a large population for more efficient yet accurate probabilistic analyses. This is tackled by a novel distributional data reduction method called Probabilistic REpresentatives Mining (PREM), which is consistent in generating small samples with the same data distribution. Part II, representative aircraft model portfolios, considers the problem of selecting a small proportion of representative aircraft models to sufficiently cover the richness and complexity of a large population when the modeling of every participant in the complex system is infeasible. This is tackled through a clustering framework which optimizes for the minimax criterion and can conduct a trade-off between multiple criteria of the selected portfolio's representativeness. Part III, representative aircraft model features, considers the problem of obtaining improved aircraft model representations for environmental impacts modeling. This is accomplished through using a combination of large-scale computer experiment and multi-level feature representation and selection. The proposed methodologies are demonstrated and tested on four selected experiments through data visualization and quantitative metrics. Overall, this dissertation aims to contribute to both the general methodologies and the solutions to specific aerospace applications.
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ItemA plasma-wall interaction model for the erosion of materials under ion bombardment(Georgia Institute of Technology, 2022-04-20) Logarzo, Hernan JavierUnderstanding the evolution and behavior of materials exposed to plasma is critical for the design of future electric propulsion devices. As ions are ejected from the device generating thrust, they also impact the ceramic walls. This induces wall erosion, ultimately exposing the magnetic circuit leading to malfunction and failure of the device. This problem is only going to be amplified as the field moves towards high power density devices. There are several models that try to predict this effect by accounting for material sputtering. However, they cannot predict the millimeter-scale surface features that develop after prolonged exposure. In this work, we address this issue by introducing a plasma-material interaction model able to capture the evolution of surface features at the macroscopic scale on materials exposed to plasma over a long period of time. The model is based on (i) data from plasma dynamics simulations, (ii) a probability model of erosion, (iii) geometric effects to account for shadowing effects and feature size and (iv) a continuum finite element model for the thermo-mechanical response of the dielectric walls that uses machine learning to account for the complex response of the material. Results show that the model is able to reproduce not only the mean erosion rate but also the macroscopic anomalous ridges that appear after prolonged exposure. Furthermore, it highlights the need to account for complex thermo-mechanical material behavior to be able to explain such features.