Search results
(381 - 400 of 411)
Pages
- Title
- Improving Localization Safety for Landmark-Based LiDAR Localization System
- Creator
- Chen, Yihe
- Date
- 2024
- Description
-
Autonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem...
Show moreAutonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem reliability, control algorithm stability, path planning, and localization. This thesis specifically delves into the localizer, a critical component responsible for determining the vehicle’s state (e.g., position and orientation), assessing compliance with localization safety requirements, and proposing methods for enhancing localization safety.Within the robotics domain, diverse localizers are utilized, such as scan-matching techniques like normal distribution transformations (NDT), the iterative closest point (ICP) algorithm,probabilistic maps method, and semantic map-based localization.Notably, NDT stands out as a widely adopted standalone laser localization method, prevalent in autonomous driving software such as Autoware and Apollo platforms.In addition to the mentioned localizers, common state estimators include variants of Kalman Filter, particle filter-based, and factor graph-based estimators. The evaluation of localization performance typically involves quantifying the estimated state variance for these state estimators.While various localizer options exist, this study focuses on those utilizing extended Kalman filters and factor graph methods. Unlike methods like NDT and ICP algorithms, extended Kalman filters and factor graph based approaches guarantee bounding of estimated state uncertainty and have been extensively researched for integrity monitoring.Common variance analysis, employed for sensor readings and state estimators, has limitations, primarily focusing on non-faulted scenarios under nominal conditions. This approach proves impractical for real-world scenarios and falls short for safety-critical applications like autonomous vehicles (AVs).To overcome these limitations, this thesis utilizes a dedicated safety metric: integrity risk. Integrity risk assesses the reliability of a robot’s sensory readings and localization algorithm performance under both faulted and non-faulted conditions. With a proven track record in aviation, integrity risk has recently been applied to robotics applications, particularly for evaluating the safety of lidar localization.Despite the significance of improving localization integrity risk through laser landmark manipulation, this remains an under explored territory. Existing research on robot integrity risk primarily focuses on the vehicles themselves. To comprehensively understand the integrity risk of a lidar-based localization system, as addressed in this thesis, an exploration of lidar measurement faults’ modes is essential, a topic covered in this thesis.The primary contributions of this thesis include: A realistic error estimation method for state estimators in autonomous vehicles navigating using pole-shape lidar landmark maps, along with a compensatory method; A method for quantifying the risk associated with unmapped associations in urban environments, enhancing the realism of values provided by the integrity risk estimator; a novel approach to improve the localization integrity of autonomous vehicles equipped with lidar feature extractors in urban environments through minimal environmental modifications, mitigating the impact of unmapped association faults. Simulation results and experimental results are presented and discussed to illustrate the impact of each method, providing further insights into their contributions to localization safety.
Show less
- Title
- Predictive energy efficient control framework for connected and automated vehicles in heterogeneous traffic environments
- Creator
- Vellamattathil Baby, Tinu
- Date
- 2023
- Description
-
Within the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this...
Show moreWithin the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this context, connected and automated vehicles (CAVs) represent a significant advancement, as they can optimize their acceleration pattern to improve their fuel efficiency. However, when CAVs coexist with human-driven vehicles (HDVs) on the road, suboptimal conditions arise, which adversely affect the performance of CAVs. This research analyzes the automation capabilities of production vehicles to identify scenarios where their performance is suboptimal, and proposes a merge-aware modification of adaptive cruise control (ACC) method for highway merging situations. The proposed algorithm addresses the issue of sudden gap and velocity changes in relation to the preceding vehicle, thereby reducing substantial braking during merging events, resulting in improved energy efficiency. This research also presents a data-driven model for predicting the velocity and position of the preceding vehicle, as well as a robust model predictive control (MPC) strategy that optimizes fuel consumption while considering prediction inaccuracies. Another focus of this research is a novel suggestion-based control framework in interactive mixed traffic environments leveraging the emerging connectivity between vehicles and with infrastructure. It is based on MPC to optimize the fuel efficiency of CAVs in heterogeneous or mixed traffic environments (i.e., including both CAVs and HDVs). In this suggestion-based control framework, the CAVs are considered to provide non-binding velocity and lane change suggestions to the HDVs to follow to improve the fuel efficiency of both the CAVs and the HDVs. To achieve this, the host CAV must devise its own fuel-efficient control solution and determine the recommendations to convey to its preceding HDV. It is assumed that the CAVs can communicate with the HDVs via Vehicle to Vehicle (V2V) communication, while the Signal Phase and Timing (SPaT) information is accessed via Vehicle-to- Infrastructure (V2I) communication. These velocity suggestions remain constant for a predefined period, allowing the driver to adjust their speed accordingly. It is also considered that the suggestions are non binding, i.e., a driver can choose not to follow the suggested velocity. For this control framework to function, we present a velocity prediction model based on experimental data that captures the response of a HDV to different suggested velocities, and a robust approach to ensure collision avoidance. The velocity prediction’s accuracy is also validated with the experimental data (on a table-top drive simulator), and the results are presented. In cases of low CAV penetration, a CAV needs to provide suggestions to multiple surrounding HDVs and incorporating the suggestions to all the HDVs as decision variables to the optimal control problem can be computationally expensive. Hence, a suggestion-based hierarchical energy efficient control framework is also proposed in which a CAV takes into account the interactive nature of the environment by jointly planning its own trajectory and evaluating the suggestions to the surrounding HDVs. Joint planning requires solving the problem in joint state- and action-space, and this research develops a Monte Carlo Tree Search (MCTS)-based trajectory planning approach for the CAV. Since the joint action- and state-space grows exponentially with the number of agents and can be computationally expensive, an adaptive action-space is proposed through pruning the action-space of each agent so that the actions resulting in unsafe trajectories are eliminated. The trajectory planning approach is followed by a low-level model predictive control (MPC)-based motion controller, which aims at tracking the reference trajectory in an optimal fashion. Simulation studies demonstrate the proposed control strategy’s efficacy compared to existing baseline methods.
Show less
- Title
- Optimization methods and machine learning model for improved projection of energy market dynamics
- Creator
- Saafi, Mohamed Ali
- Date
- 2023
- Description
-
Since signing the legally binding Paris agreement, governments have been striving to fulfill the decarbonization mission. To reduce carbon...
Show moreSince signing the legally binding Paris agreement, governments have been striving to fulfill the decarbonization mission. To reduce carbon emissions from the transportation sector, countries around the world have created a well-defined new energy vehicle development strategy that is further expanding into hydrogen vehicle technologies. In this study, we develop the Transportation Energy Analysis Model (TEAM) to investigate the impact of the CO2 emissions policies on the future of the automotive industries. On the demand side, TEAM models the consumer choice considering the impacts of technology cost, energy cost, refueling/charging availability, consumer travel pattern. On the supply side, the module simulates the technology supply by the auto-industry with the objective of maximizing industry profit under the constraints of government policies. Therefore, we apply different optimization methods to guarantee reaching the optimal automotive industry response each year up to 2050. From developing an upgraded differential evolution algorithm, to applying response surface methodology to simply the objective function, the goal is to enhance the optimization performance and efficiency compared to adopting the standard genetic algorithm. Moreover, we investigate TEAM’s robustness by applying a sensitivity analysis to find the key parameters of the model. Finally based on the key sensitive parameters that drive the automotive industry, we develop a neural network to learn the market penetration model and predict the market shares in a competitive time by bypassing the total cost of ownership analysis and profit optimization. The central motivating hypothesis of this thesis is that modern optimization and modeling methods can be applied to obtain a computationally-efficient, industry-relevant model to predict optimal market sales shares for light-duty vehicle technologies. In fact, developing a robust market penetration model that is optimized using sophisticated methods is a crucial tool to automotive companies, as it quantifies consumer’s behavior and delivers the optimal way to maximize their profits by highlighting the vehicles technologies that they could invest in. In this work, we prove that TEAM reaches the global solution to optimize not only the industry profits but also the alternative fuels optimized blends such as synthetic fuels. The time complexity of the model has been substantially improved to decrease from hours using the genetic algorithm, to minutes using differential evolution, to milliseconds using neural network.
Show less
- Title
- Analysis of High-Fidelity Experiments and Simulations of the Flow in Simplified Urban Environments
- Creator
- Stuck, Maxime
- Date
- 2020
- Description
-
The mean flow and turbulence statistics of the flow through a simplified urban environment, which is an active research area in order to improve...
Show moreThe mean flow and turbulence statistics of the flow through a simplified urban environment, which is an active research area in order to improve the knowledge of turbulent flow in cities, is investigated. This is useful for civil engineering, pedestrian comfort and for health concerns caused by pollutant spreading. In this work, we provide analysis of the turbulence statistics obtained both from highly-quality stereoscopic particle image-velocimetry (SPIV) measurements (from Monnier et al.) and well-resolved large eddy simulations (LES) by Torres et al. A detailed comparison of both databases reveals the impact of the geometry of the urban array on the flow characteristics and provides for a good description of the turbulent features of the flow around a simplified urban environment. The most prominent features of this complex flow include coherent vortical structures such as the so-called arch vortex, the horseshoe vortex, or the roof vortex. These structures of the flow have been identified by an analysis of the turbulence statistics. The influence of the geometry of the urban environment (and particularly the street width and the building height) on the overall flow behavior has also been studied.
Show less
- Title
- Predictive energy efficient control framework for connected and automated vehicles in heterogeneous traffic environments
- Creator
- Vellamattathil Baby, Tinu
- Date
- 2023
- Description
-
Within the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this...
Show moreWithin the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this context, connected and automated vehicles (CAVs) represent a significant advancement, as they can optimize their acceleration pattern to improve their fuel efficiency. However, when CAVs coexist with human-driven vehicles (HDVs) on the road, suboptimal conditions arise, which adversely affect the performance of CAVs. This research analyzes the automation capabilities of production vehicles to identify scenarios where their performance is suboptimal, and proposes a merge-aware modification of adaptive cruise control (ACC) method for highway merging situations. The proposed algorithm addresses the issue of sudden gap and velocity changes in relation to the preceding vehicle, thereby reducing substantial braking during merging events, resulting in improved energy efficiency. This research also presents a data-driven model for predicting the velocity and position of the preceding vehicle, as well as a robust model predictive control (MPC) strategy that optimizes fuel consumption while considering prediction inaccuracies. Another focus of this research is a novel suggestion-based control framework in interactive mixed traffic environments leveraging the emerging connectivity between vehicles and with infrastructure. It is based on MPC to optimize the fuel efficiency of CAVs in heterogeneous or mixed traffic environments (i.e., including both CAVs and HDVs). In this suggestion-based control framework, the CAVs are considered to provide non-binding velocity and lane change suggestions to the HDVs to follow to improve the fuel efficiency of both the CAVs and the HDVs. To achieve this, the host CAV must devise its own fuel-efficient control solution and determine the recommendations to convey to its preceding HDV. It is assumed that the CAVs can communicate with the HDVs via Vehicle to Vehicle (V2V) communication, while the Signal Phase and Timing (SPaT) information is accessed via Vehicle-to- Infrastructure (V2I) communication. These velocity suggestions remain constant for a predefined period, allowing the driver to adjust their speed accordingly. It is also considered that the suggestions are non binding, i.e., a driver can choose not to follow the suggested velocity. For this control framework to function, we present a velocity prediction model based on experimental data that captures the response of a HDV to different suggested velocities, and a robust approach to ensure collision avoidance. The velocity prediction’s accuracy is also validated with the experimental data (on a table-top drive simulator), and the results are presented. In cases of low CAV penetration, a CAV needs to provide suggestions to multiple surrounding HDVs and incorporating the suggestions to all the HDVs as decision variables to the optimal control problem can be computationally expensive. Hence, a suggestion-based hierarchical energy efficient control framework is also proposed in which a CAV takes into account the interactive nature of the environment by jointly planning its own trajectory and evaluating the suggestions to the surrounding HDVs. Joint planning requires solving the problem in joint state- and action-space, and this research develops a Monte Carlo Tree Search (MCTS)-based trajectory planning approach for the CAV. Since the joint action- and state-space grows exponentially with the number of agents and can be computationally expensive, an adaptive action-space is proposed through pruning the action-space of each agent so that the actions resulting in unsafe trajectories are eliminated. The trajectory planning approach is followed by a low-level model predictive control (MPC)-based motion controller, which aims at tracking the reference trajectory in an optimal fashion. Simulation studies demonstrate the proposed control strategy’s efficacy compared to existing baseline methods.
Show less
- Title
- Laser Powder Bed Fusion Of Cost-Effective Non-Spherical Ti-6Al-4V Powder
- Creator
- Asherloo, Mohammadreza
- Date
- 2023
- Description
-
This comprehensive research delves into the intricate dynamics of Laser Powder Bed Fusion (L-PBF) of Ti-6Al-4V powders, emphasizing the...
Show moreThis comprehensive research delves into the intricate dynamics of Laser Powder Bed Fusion (L-PBF) of Ti-6Al-4V powders, emphasizing the potential of non-spherical, hydride-dehydride (HDH) powders as a cost-efficient alternative to traditional spherical powders. The study systematically explores the interplay between powder morphology, granulometry, and various post-processing treatments in shaping the resultant microstructure, porosity, and mechanical properties of L-PBF fabricated Ti-6Al-4V components.Initial investigations focused on the flowability, packing density, and resultant density of L-PBF parts using HDH powders with varying size distributions. Through meticulous optimization of laser parameters, parts with a relative density exceeding 99.5% were achieved, even at production rates 1.5–2 times higher than conventional LPBF processes. Dynamic synchrotron X-ray imaging provided insights into laser-powder interactions, revealing key mechanisms of porosity formation associated with HDH powders. Further microstructural examinations highlighted the formation of columnar β grains with acicular α/α′ phases in the as-built condition. Mechanical tests, including fatigue assessments under fully-reversed tension-compression conditions, revealed the critical role of surface roughness in fatigue performance. Notably, mechanical grinding significantly improved fatigue strength, especially in the high cycle fatigue region, by eliminating surface micro-notches. X-ray diffraction analyses further elucidated the stress and micro-strain profiles, offering insights into the material's deformation mechanisms. A pivotal discovery was the presence of α/α′ on prior β/β grain boundaries, challenging the prevailing notion that high cooling rates in L-PBF preclude β/β grain boundary variant selection. Electron backscatter diffraction and synchrotron X-ray imaging illuminated the role of powder characteristics in locally modulating cooling rates, leading to β/β grain boundary α′ lath growth. Lastly, the research underscored the multifaceted interdependencies among contouring, powder granulometry, Hot Isostatic Pressing (HIP), and mechanical surface treatments. A pronounced increase in sub-surface porosities was identified when contouring was combined with fine powder granulometry. However, post-HIP treatments induced a phase transformation from martensitic α′ to a basket-weave α+β microstructure, enhancing the material's fatigue resistance to levels comparable to wrought Ti-6Al-4V. In summation, this doctoral research offers a holistic understanding of the L-PBF process for Ti-6Al-4V, emphasizing the viability of non-spherical HDH powders and providing a roadmap for parameter optimization, defect minimization, and mechanical property enhancement in L-PBF-fabricated Ti-6Al-4V structures.
Show less
- Title
- Investigation of Electrochemical Properties and Fabrication of Lithium- and Sodium-ion Batteries
- Creator
- Chen, Changlong
- Date
- 2023
- Description
-
Since the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy...
Show moreSince the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy supply and less environmental concerns has been significantly increased. This triggered tremendous efforts from both academy and industry in building better Li-ion batteries. Along the research and development over past 30 years, the performance of current Li-ion batteries has met some basic needs in our daily life, such as powering electronic devices and electric vehicles for a short time, while superior capabilities, like extended operating life, stable function under extreme circumstances, is always pursued. Under the pressure from these ever-growing demands, the corresponding Li-ion battery production is faced with a lot of new challenges. Regarding the battery production, the present Li-ion battery manufacturing heavily relies on the use of certain repo-toxic solvent, N-methyl-2-pyrrolidone (NMP), which arouses safety concerns to human health. In the pursuit of a higher energy density, silicon anode, bearing ten times the gravimetric capacity of commercially-dominating graphite anode, is intensively studied as the anode material for next-generation Li-ion batteries. However, its degradation mechanism is not completely revealed yet, which makes the methods of effective optimizations hard to be developed. In terms of the cost control, Na-ion batteries have been revisited and have received extra attention in the past decade owing to the abundance in raw materials and the high compatibility with state-of-art Li-ion industry while blank space in understanding primary electrochemical properties, such as impedance signals, has not been totally filled. This will also cause the misunderstandings in such interpretation and, thereby, postpone the pace of relevant advancement. Targeting these proposed issues, this thesis provides a series of feasible solutions via careful investigation and rational analysis with the aid of various advanced (non)electrochemical techniques, which offers a few unique perspectives in studying Li- and Na-ion batteries, and further facilitates the following research and development in the corresponding communities.
Show less
- Title
- Resolvent analysis of turbulent flows: Extensions, improvements and applications
- Creator
- Lopez-Doriga Costales, Barbara
- Date
- 2024
- Description
-
This thesis presents several advances in both physics-based and data-driven modeling of turbulent fluid flows. In particular, the present...
Show moreThis thesis presents several advances in both physics-based and data-driven modeling of turbulent fluid flows. In particular, the present thesis focuses on resolvent analysis, a physics-based framework that identifies the coherent structures that are most amplified by the Navier-Stokes equations when they are linearized about a known turbulent mean flow via a singular value decomposition (SVD) of a discretized operator. This method has proven to effectively capture energetically-relevant features observed in various flows. However, it has some shortcomings that the present work intends to alleviate. First, the original formulation of resolvent analysis is restricted to statistically-stationary or time-periodic mean flows. To expand the applicability of this framework, this thesis presents a spatiotemporal variant of resolvent analysis that is able to account for time-varying systems. Moreover, sparsity (which manifests in localization) is also incorporated to the analysis through the addition of an l1-norm penalization term to the optimization associated with the SVD. This allows for the identification of energetically-relevant coherent structures that correspond to spatio-temporally localized amplification mechanisms, for flows with either a time-varying or stationary mean. The high computational cost associated with the discretization and analysis of a large discretized of the mean-linearized Navier-Stokes operator represents the second drawback of resolvent analysis. As a second contribution, this thesis provides an analytic form of resolvent analysis for planar flows based on wavepacket pseudomode theory, avoiding the numerical computations required in the original framework. The third contribution focuses on the characterization of the energetically-dominant coherent structures that arise in turbulent flow traveling through straight ducts with square and rectangular cross-sections. First, resolvent analysis is applied to predict the coherent structures that arise in this flow, and to study the sensitivity of this methodology to the secondary mean flow components that display a distinct pattern near the duct corners. Next, a data-driven causality analysis is performed to understand the physical mechanisms involved in the evolution of coherent structures near the duct corners. To do this, a nonlinear Granger causality analysis method is developed and applied to proper orthogonal decomposition coefficients of direct numerical simulation data, revealing that the structures associated with the secondary velocity components are behind the formation and translation of the near-wall and near-corner streamwise structures. A general discussion and future prospects are discussed at the end of this thesis.
Show less
- Title
- Resolvent Analysis of Turbulent Flow over Compliant Surfaces: Optimization Methods and Stability Considerations.
- Creator
- Lapanderie, Kilian Pierre Lucien
- Date
- 2024
- Description
-
This thesis delves into the manipulation of turbulence properties through innovative compliant surface designs. Turbulence, known for its...
Show moreThis thesis delves into the manipulation of turbulence properties through innovative compliant surface designs. Turbulence, known for its unpredictable fluid movements, presents substantial challenges across engineering disciplines, particularly in optimizing system efficiency and minimizing energy losses. This research explores the potential of compliant surfaces to control and mitigate the adverse effects of turbulent flow, thereby enhancing the performance and reliability of engineering systems.Employing the resolvent analysis method, this work investigates the interaction between turbulent flows and surfaces capable of dynamic adaptation. The study evaluates the impact of these surfaces on turbulence suppression through the application of both space-dependent and independent compliance models, where the compliance model is characterised by an admittance, which represents the relationship between the instantaneous surface pressure and surface velocity. This approach allows for a nuanced understanding of how different surface properties can influence the behavior of turbulent flows.A significant contribution of this thesis is the comprehensive stability analysis conducted to assess the implications of compliant surfaces on the linear stability of the dynamical system. By examining the eigenvalues of the mean-linearized system, the research identifies the conditions under which compliant surfaces may induce or mitigate instabilities within turbulent flows. This analysis is pivotal in developing compliant surface designs that not only reduce turbulence-induced energy losses but also ensure the stability of the flow, a critical consideration for practical engineering applications.The findings of this thesis offer valuable insights into the role of surface compliance in turbulence control, paving the way for further research and the development of advanced engineering solutions. Through a detailed investigation of the interactions between compliant surfaces and turbulent flows, this work contributes to the broader field of fluid dynamics and underscores the potential of innovative surface designs in achieving more efficient and sustainable engineering systems.
Show less
- Title
- Ultrasound Image Guided Robot Arm for Targeted Delivery of Therapeutic Drugs and MicroRNA for Cancer Therapy
- Creator
- Nagarajan Parimala, Abishek
- Date
- 2024
- Description
-
Molecular imaging has revolutionized medical diagnostics by providing detailed insights into biological processes at the molecular level...
Show moreMolecular imaging has revolutionized medical diagnostics by providing detailed insights into biological processes at the molecular level within the living subject. Ultrasound Molecular Imaging (USMI) has emerged as a promising diagnostic imaging modality by utilizing targeted contrast agents to unveil crucial molecular information, including vascular biomarkers associated with cancer and other diseases. Despite its potential, the transition of Ultrasound Contrast Agents (UCA) from preclinical evaluation to FDA-approved clinical use faces challenges due to the short in vivo half-life of Micro-Bubbles (MBs), necessitating repeated administrations for comprehensive assessments. Moreover, conventional ultrasound imaging methods suffer from limited scanning areas and single-target focus, leading to low throughput in preclinical evaluations.This thesis addresses these challenges by proposing a robot-assisted whole-body scanning pipeline for preclinical evaluations in Ultrasound Molecular Imaging. By integrating a robotic arm into the imaging setup, this approach enhances scanning flexibility and precision, enabling scans across the entire body of a mouse. This extension of the imaging time window allows for comprehensive assessments without the need for repeated contrast agent administrations. Additionally, the ability to simultaneously scan multiple targets within the same session significantly increases the throughput of preclinical assessments, thereby improving the efficiency and reliability of Ultrasound Molecular Imaging in clinical translation.
Show less
- Title
- Development of Granular Jamming Soft Robots from Boundary Constrained to Interconnected Systems
- Creator
- Tanaka, Koki
- Date
- 2023
- Description
-
This dissertation provides a detailed study on the conceptualization, creation, and optimization of a unique, interconnected soft robot system...
Show moreThis dissertation provides a detailed study on the conceptualization, creation, and optimization of a unique, interconnected soft robot system. It introduces a flexible assembly of locomotive robotic modules interconnected by an envelope, capable of granular jamming. In doing so, it highlights the practical capabilities of these interconnected modules to adapt and function cohesively as a single robot system.As a precursor to the primary investigation, the study initially presents the development and experimental validation of a boundary constrained mobile soft robot. This design leverages granular jamming for locomotion and object grasping, thereby laying a robust foundation for the subsequent exploration of complex soft robotic systems.The cornerstone of this study is the development of an interconnected soft robot system, where locomotive robotic modules, primarily composed of an elastic material, are bound together by a flexible envelope designed for granular jamming. The robotic modules, fundamentally constructed from an elastic material, incorporate origami-inspired artificial muscle actuators. These actuators, with their semi-soft characteristics, complement the inherent flexibility of the modules and play a significant role in facilitating module propulsion. Although the design incorporates a traditional rigid power source, as opposed to a fully soft robot system, the integration of a pneumatic power method into the system successfully reduces the mechanical intricacy and unwieldiness typically associated with rigid mechanisms.This research further probes into the diverse applications of this interconnected soft robot system. Its ability to shape-shift and maintain these forms during locomotion exemplifies a robust control strategy for the system that may undergo substantial deformation, proving instrumental in dynamic environments. The study demonstrates a methodology for object manipulation and obstacle avoidance that does not rely heavily on precise control and sensing. Instead, it utilizes the inherent compliance of the soft robot system. In a notable departure from previous studies, the system also exhibits a unique capability for ascending and traversing inclined surfaces.Additionally, the study dives into the optimization of the interconnected robot system via a physics-based simulation and genetic algorithm. This approach results in an assortment of optimized configurations that excel in object grasping tasks of various shapes, thereby laying a robust groundwork for the progression of soft robotics in the future.In conclusion, this investigation reveals groundbreaking insights into the field of soft robotics through the successful design and optimization of an interconnected soft robot system. Its standout performances in deformation, manipulation, and navigation tasks set it apart. This work serves to significantly enhance the adaptability and functionality of future robotic systems, pushing the edge of what is possible across a diverse range of sectors. By portraying a significant step towards a future where robots can dynamically adapt to their environments and efficiently accomplish complex tasks, this dissertation exemplifies a transformative stride in the field.
Show less
- Title
- First-principles study on the stability, electrochemical property, and degradation mechanism of ceramic electrode materials
- Creator
- Wei, Jialiang
- Date
- 2023
- Description
-
First-principles studies demonstrate the capability to rapidly and accurately calculate desired properties in battery materials. This thesis...
Show moreFirst-principles studies demonstrate the capability to rapidly and accurately calculate desired properties in battery materials. This thesis focuses on the examination of layered NaCrO2 as a case study to assess the impact of various calculation methods. Additionally, a microscopic analysis is conducted to investigate the failure mode of NaCrO2. Lastly, a successful first-principles based high-throughput screening of electrode materials is performed to identify stable compounds that enable easy Li migration.The layered O3 NaCrO2 compound exhibits promising characteristics as a Na-ion cathode material, including good thermal stability and specific capacity. However, it suffers from poor rate capability. To address this limitation and develop high-rate Na-ion cathodes, we conducted a first-principles study that focused on the stability and Na diffusion in pure and doped NaCrO2. The study utilized various functionals, including those explicitly incorporating van der Waals (vdW) interactions. By including vdW interactions, we observed a significant reduction in interlayer distances within partially desodiated NaCrO2, which directly impacted the prediction of Na diffusion barriers. We established a linear relationship between interlayer distance and diffusion barrier using different functionals. Notably, the increased diffusion barriers were mainly due to the reduced interlayer distances predicted by the vdW-inclusive functionals, rather than the inclusion of vdW interactions in the transition state calculations. Other factors, such as the charge density change introduced by different dopants, also influenced the Na diffusion barriers. Metal doping (Al, Zn, Mn, and Co) at low concentrations in NaCrO2 had minor effects on its thermodynamic stability but significantly promoted Na diffusivity. Among the doped NaCrO2 compounds, Co-doped NaCrO2 exhibited the lowest Na diffusion barriers and emerged as a potential candidate for high-rate Na-ion cathode materials. This study highlights the significance of vdW interactions in layered transition metal oxides and provides strategies to enhance first-principles predictions for such structures.Then, TM migration usually occurs at highly charged states in layered Na transition metal oxide, leading to a deterioration in capacity and reversibility. Furthermore, the formation of hybrid phases, characterized by the intergrowth of octahedral and prismatic Na layers, is known to take place at highly charged states. These hybrid phases often exhibit greater stability compared to simple O3 or P3 stacking configurations. However, there is limited understanding regarding the mechanism and impact of TM migration in these hybrid phases. To address this gap, we conducted a comparative first-principles study to elucidate the connection between structural changes and Cr migration in layered O3 and hybrid-phased NaCrO2. We observed that the hybrid-phased NaCrO2 experienced more significant layer shrinkage than the O3 phase after Cr migration. Three factors were found to affect the Cr migration energy: the Na concentration, local 3D configuration, and 2D in-plane geometry. Low Na concentration and specific 3D configurations facilitated Cr migration. Furthermore, the Cr migration barriers in both O3 and hybrid-phased NaCrO2 were found to be positively correlated with Cr migration energy. Lastly, we surveyed the Cr migration of 17 doped O3 and hybrid-phased NaCrO2 compounds. A uniform distribution of Cr-O bond length usually indicated suppressed Cr migration. We identified optimal dopants for Cr migration suppression by considering both Cr and dopant migration energy. This comparative study on Cr migration in O3 and hybrid-phased NaCrO2 highlights the significant role of hybrid phases in the application of layered cathode materials.Moving from the calculations of single material system, we last conduct a first-principles high-throughput screening of multicomponent transition metal sulfides (TMS) as fast Li-ion intercalation compounds. We compared two representative TMS frameworks, pyrite and spinel, with regard to their selectivity in forming stable disordered TMS. To quantify the ability to form entropy stabilized disordered TMS, we examined the effects of cation permutation on the formation enthalpy range. Although low energy-above-hull (Ehull) is a preliminary requirement for the formation of stable TMS, a narrow formation enthalpy range can also lead to entropy stabilized TMS, as only a small amount of excess energy is required to stabilize the metastable configurations. Among the 70 pyrite and spinel frameworks studied, we selected 13 spinel compounds based on their low Ehull and narrow Ef range. Additionally, these spinel compounds exhibited greater stability compared to their pyrite counterparts. We found that early transition metal elements such as Ti and V were less favorable for the formation of pyrite TMS, while late TM elements, especially Cu, strongly destabilized spinel TMS. The spinel (CrMnCoNi)S2 TMS demonstrated the most promising characteristics with a narrow Ef range. Finally, we calculated and ranked the Li migration barriers in the 13 stable spinel TMS using a bond valence-based method, which allowed for quick screening of ion migration. High oxidation state TM elements, such as Mn4+ and Cr3+, located nearest to the Li migration path, increased the Li migration barrier. (CrMnCoNi)S2 exhibited the lowest Li migration barrier, positioning it as a promising entropy-stabilized spinel intercalation compound.
Show less
- Title
- Effect of Phosphorus Additions on Polycrystalline Ni-base Superalloys
- Creator
- Li, Linhan
- Date
- 2020
- Description
-
In recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level...
Show moreIn recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level of refractory elements as solid-solution strengtheners in an effort to extend the temperature capability. Moreover, the properties of the grain boundaries become more important and this necessitates the need to study of effects of minor additions of interstitial P for grain structure optimization. Due to the increased level of refractory elements employed, powder-processed Ni-base superalloys tend to have a high propensity to form Topologically Close-Packed (TCP) phases, which was found to be further promoted by the addition of P. A systematic study of the phase stability of high refractory content powder-processed Ni-base superalloys with three levels of P additions revealed an increased tendency to form Laves phase as a function of P additions. Additions of P were discovered to not only depress the incipient melting temperature to stabilize the eutectic Laves phase, but also promote Laves phase formation during the aging heat treatment and the following isothermal exposure. During the thermal exposure, excessive formation of Laves phase promoted the formation of a basket-weave structure comprised of an intertwined mixture of Laves and Sigma phase. The stabilization of the Laves phase structure due to P additions was found to be consistent with Density Functional Theory (DFT) calculations and could be rationalized through structure maps that relate the valence electron concentration and relative size differences. Additionally, a variation of grain structure obtained via either a sub-solvus or super-solvus solution heat treatment was noted to some extent vary the P segregation level at high-angle grain boundaries, thereby affecting the phase stability. For a sub-solvus solutioned grain structure that possessed a high length density of high-angle grain boundaries, the Laves phase formation was depressed for alloys with a low level of P addition. However, the phase stability variation associated with Laves phase formation was moderate when high concentrations of P were present. The effect of P addition on the γ′ microstructure variation is limited, which was confirmed by microstructure observations as well as through the short-term 0.6%-strain stress relaxation tests at high temperature. Heat treatment variations to modify the secondary and tertiary γ′ microstructures were discovered to exert a much more significant influence on the 0.6%-strain stress relaxation behavior. When a higher initial strain of 2% was applied, the stress relaxation behavior of the powder-processed Ni-base superalloys was found to be microstructure independent. The creep ductility of Waspaloy was determined to be notably reduced by the P additions due to the enhanced precipitation of M23C6 carbide at the grain boundaries. Excessive precipitation of M23C6 carbide increased the likelihood of brittle fracture when tested under low temperature/high stress creep conditions. However, the P addition as well as the excessive precipitation of M23C6 carbide did not impact the creep behavior as the dominant deformation was transgranular in nature when tested under high temperature/low stress conditions.
Show less
- Title
- Prediction and Control of In-Cylinder Processes in Heavy-Duty Engines Using Alternative Fuels
- Creator
- Pulpeiro Gonzalez, Jorge
- Date
- 2024
- Description
-
This Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal...
Show moreThis Ph.D. thesis focuses on advancing diagnostic techniques and control-oriented models to enhance the efficiency and performance of internal combustion (IC) engines, particularly heavy-duty engines utilizing alternative fuels. The research endeavors to contribute to the field of model-based control of engines through the development and implementation of innovative methodologies. The primary emphasis is on the development of diagnostic methods, control-oriented models and advanced control strategies for compression ignition engines using alternative fuels. The first key topic explores the determination of the Most Representative Cycle for Combustion Phasing Estimation based on cylinder pressure measurements. The method developed extracts crucial information from experimental data obtained from four distinct engines: the heavy-duty single-cylinder GCI engine, the light-duty multi-cylinder diesel engine, a CFR engine, and a single-cylinder light-duty Spark Ignition (SI) engine. This work lays the foundation for precise combustion phasing estimation, a critical parameter for engine control. The second major contribution involves the development of control-oriented models for Variable Geometry Turbochargers (VGT) and inter-coolers. Two models are established: a data-driven turbocharger model and an empirical inter-cooler model. These models are meticulously calibrated and validated using experimental data from a multi-cylinder light-duty diesel engine, providing valuable insights into the behavior of these components under varying conditions. The outcomes contribute to facilitate predictive control of engine air systems. The third core aspect of the thesis revolves around Model Predictive Control of Combustion Phasing in heavy-duty compression-ignition engines utilizing alternative fuels. A combustion phasing and engine load model is derived from experimental data and incorporated into an MPC framework. The MPC strategy is subsequently tested in the heavy-duty GCI test cell and compared against a conventional Proportional-Integral-Derivative (PID) control strategy. The results showcase the effectiveness of the MPC approach in achieving precise control of combustion phasing, demonstrating its potential for optimizing engine performance. In summary, this Ph.D. thesis contributes significantly to the field of engine controls by advancing diagnostic techniques, control-oriented models, and implementing a cutting-edge MPC-based control strategy for compression ignition engines using alternative fuels. The research findings not only enhance the understanding of in-cylinder processes but also pave the way for more efficient and sustainable heavy-duty engines using alternative fuels.
Show less
- Title
- Effect of Stress Triaxiality and Lode Angle on Ductile Fracture
- Creator
- Nia, Mahan
- Date
- 2023
- Description
-
Although many ductile damage accumulation studies have been done in recent years, there is still insufficient research towards the development...
Show moreAlthough many ductile damage accumulation studies have been done in recent years, there is still insufficient research towards the development of ductile fracture models, mainly due to the difficulty of performing experiments under different states of multiaxial stress. The goals of this Ph.D. research are to (i) produce much-needed experimental data, (ii) investigate the performance of existing models against these data, and (iii) develop a new predictive ductile fracture model validated by experiments. The new model seeks to predict the fracture strain as a function of the stress triaxiality and normalized Lode angle. One of the prominent works in this area was done by Bai and Wierzbicki in 2008 by testing 2024-T351 aluminum alloy. They proposed an asymmetric 3D empirical fracture model with six model parameters. Thus, the Bai method was investigated alongside a new model for predicting ductile fracture. For that purpose, 2139-T8 aluminum alloy was chosen for our experimental program to evaluate these models better, and the data extracted from Bai's work was also used as an additional data set. An extensive experimental program was considered to create different stress states in the material, including tensile tests (with round smooth and four round notched and plate specimens), torsion, compression (with four smooth and two notched specimens), and shear-compression experiments (two different sizes). The specimens were longitudinally machined from a block of 2139-T8 aluminum alloy. The combined effects of two variables, stress triaxiality and normalized Lode angle, define a 3D fracture envelope for fracture strain. A parallel FE simulation (fine-tuned by the experimental results) has been performed for each experiment to evaluate the evolution of stress triaxiality and Lode angle in the gauge section of the specimens with complicated geometries. Finally, these results were used in developing two predictive fracture models. The first model is based on the Bai-Wierzbicki form of fracture. The second one is a new model that has been presented in this research. This new model is a modification of the Johnson-Cook fracture model and considers the simultaneous effects of Lode angle and stress triaxiality in fracture. The original Johnson-Cook fracture model (1984) does not consider the Lode angle effect. In the end, errors in the proposed approach to modeling ductile fracture have been compared to errors from Bai's work, resulting in the conclusions and recommendations for future studies.
Show less
- Title
- Ground Monitors to Support Navigation Operations of ARAIM and GBAS
- Creator
- Patel, Jaymin Harshadkumar
- Date
- 2023
- Description
-
Receiver Autonomous Integrity Monitoring (RAIM) currently provides safehorizontal navigation guidance to en route civil aircraft using the GPS...
Show moreReceiver Autonomous Integrity Monitoring (RAIM) currently provides safehorizontal navigation guidance to en route civil aircraft using the GPS L1 frequency. As an evolution of RAIM, Advanced RAIM (ARAIM) is being developed to provide vertical guidance in addition to horizontal using multiple constellations and dual frequency thus facilitating precision approach without ground support for civil aircraft. However, navigation guidance during zero-visibility (Category III) precision landing requires an additional support in real time from a Ground Based Augmentation System (GBAS). To improve the aircraft navigation solution, GBAS broadcasts a differential correction and monitors any failure on transmitted satellite signals. This dissertation contributes to ARAIM and GBAS to improve existing navigation operations in order to enable precision approach and landing.The achievable performance of ARAIM is highly dependent on the assumptionson a constellation’s nominal Signal-In-Space (SIS) error models and a priori fault probability. In the framework of ARAIM, an Integrity Support Message (ISM) is envisioned to carry the required SIS error-model parameters and fault statistics for users. The ISM is generated and validated through offline monitoring, and disseminated along the navigation message. The first dissertation contribution is to provide necessary satellite positions and clock biases as a truth product to evaluate nominal SIS range errors (SISREs). An estimator is developed to generate accurate ephemeris parameters to provide these truth products. The estimator’s performance is demonstrated for the Global Positioning System (GPS) constellation by utilizing the International GNSS Service (IGS) ground network to collect dual-frequency raw GPS code and carrier phase measurements. The resulting SISREs from the estimator are predicted to have a standard deviation of 0.5 m. When estimated ephemeris parameters and clock biases are compared with precise IGS orbit and clock products, the resulting SISREs are within ±2! at all times. In the second contribution, a new approach is proposed to generate the ISM by modeling the ephemeris parameter errors directly. In preliminary analysis, an ephemeris parameter error model is developed for the broadcast GPS legacy navigation message (LNAV) under nominal conditions. Then, the proposed approach is demonstrated to provide the nominal bias and standard deviation on GPS SISREs.As a part of fault monitoring in the GBAS, a ground monitor is developedto detect ephemeris failures, incorrect broadcast satellite positions, and hazardous ionosphere storms using either single- or dual frequency. The monitor also addresses the challenge of fault-free differential correction when satellites are rising, newly acquired, and re-acquired. The monitor utilizes differential code and carrier phase measurements across multiple reference receiver antennas as the basis for detection. Finally, the analytical performance of the monitor is demonstrated to meet Category III precision approach and landing requirements.
Show less
- Title
- High-Entropy Stabilization as a Designing Tool for Li-Ion Electrodes
- Creator
- Bandeira Jovino Marques, Otavio Jose
- Date
- 2023
- Description
-
High-Entropy oxides (HEOs) form a new class of materials where the configurational entropy plays the stabilizing role of multicomponent...
Show moreHigh-Entropy oxides (HEOs) form a new class of materials where the configurational entropy plays the stabilizing role of multicomponent systems at high temperatures. Recently, it raised much attention for energy storage applications, especially on Li-ion batteries, where the combination of several different elements in a single solid solution can synergistically act to overcome some of its main drawbacks, improving the battery’s performance. The entropy stabilization opens new boundaries on electrode’s design by increasing the compositional space available for different structures and compounds. Not long ago, the high-entropy oxide (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)O demonstrated a big potential as anode material in Li-ion batteries. Its high capacity and long cycling stability raised a lot of questions about the role of the transition metals in the conversion reaction, and the configurational entropy contribution to the electrochemical reaction, further supporting the electrode’s stability. In order to investigate the structural evolution, the role of the multicomponent oxides and structures on the battery’s performance, and the entropic contribution to the electrode’s stability, this research proposes a systematic and robust methodology around the (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)O high-entropy oxide (HEO). The project heavily relies on the EXAFS ability to determine the short-range structure and the chemical sensitivity to isolate the elemental contribution of the compound at different cycling and charging states. First, the role of different metallic cations on the electrochemical reaction mechanism of the HEO was analyzed by the change in local structure during different charging steps of a Li-ion battery (Chapter 3). Secondly, the entropy contribution and tunability effects on electrochemical performance were tested in a series of medium and high-entropy oxides derived from the seminal HEO. Mg, Co, Ni, Cu, and Zn were individually removed from the HEO’s composition at a time and tested as Li-ion electrode. Fe was also added to the HEO’s composition (HEO+Fe) in order to prove the tunability effects and entropy contribution (Chapter 4). Operando x-ray absorption spectroscopy (XAS) was used to capture the short lived phases and the transient nature of the conversion reaction, to explain the origins of the extra storage capacity encountered on entropy stabilized systems (Chapter 5). Finally, the role of the high-entropy oxide initial structure was investigated and compared, to check versatility of the elements that can be used on a high-entropy system (Chapter 6).
Show less
- Title
- Development of data assimilation for analysis of ion drifts during geomagnetic storms
- Creator
- Hu, Jiahui
- Date
- 2024
- Description
-
The primary objective of this dissertation is to gain insight into geomagnetic storm effects at mid-latitudes induced by solar activity....
Show moreThe primary objective of this dissertation is to gain insight into geomagnetic storm effects at mid-latitudes induced by solar activity. Geomagnetic storms affect our everyday lives because they give rise to transient signal loss, data transmission errors, negatively impacting users of satellite navigation systems. The Nighttime Localized Ionospheric Enhancement (NILE) is a localized plasma enhancement that because it is not well understood, drives the design of satellite-based augmentationsystems. To better secure operation of technological infrastructure, it is essential to build a comprehensive understanding of the atmospheric drivers, especially during solar active periods. Instrument measurements and climate models serve as valuable tools in obtaining information regarding the occurrence of space weather events; nonetheless, both sources exhibit quantitative and qualitative limitations. Data assimilation, an evolving technique, integrates measurements and model information to optimize the state estimations. This dissertation presents developments in a data assimilation algorithm known as Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE), and its applications in investigating the atmospheric behaviors under varying solar conditions. EMPIRE is a data assimilation algorithm specifically designed for upper atmospheric driver estimation of neutral wind and ion drifts at user-defined spatial and temporal scales. The EMPIRE application in this work aims to contribute to a more comprehensive understanding of the effects of the NILE. EMPIRE utilizes the Kalman filter to optimize state calculations primarily based on electron density rates, provided by other data assimilation algorithms. Earlier runs of the algorithm used pre-defined values for the background state covariance cross time. To address model limitations under changing geomagnetic conditions, the algorithm is enhanced by concurrently updating the background state covariance during assimilation processes. Additionally, representation error is incor- porated as a component of the observation error, and error analysis is performed through a synthetic-data study. Previously, EMPIRE fused Fabry-Perot Interferometer (FPI) neutral wind measurements, demonstrating increased agreement with validation neutral wind data. In this work, this approach is extended to augment Coherent Scatter Radar (CSR) ion drift measurements from Super Dual Auroral Radar Network (SuperDARN), providing additional insights into EMPIRE’s estimated field-perpendicular ion motion. For an in-depth exploration of storm-related NILE, both EMPIRE and another data assimilation method, the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension coupled with Data Assimilation Research Testbed (WACCM-X + DART), is implemented for a storm event to test the proposed NILE driving mechanism. Furthermore, this dissertation introduces a Kalman smoother technique into the EMPIRE to enhance its ability to assess past storm events, and to explore the potential for algorithm improvements.
Show less
- Title
- Modeling and Optimization of Embedded Active Flow Control Systems
- Creator
- Henry, James M.
- Date
- 2024
- Description
-
This thesis presents research focused on the aerodynamic performance of circulation control on two-dimensional and quasi-two-dimensional wings...
Show moreThis thesis presents research focused on the aerodynamic performance of circulation control on two-dimensional and quasi-two-dimensional wings. Aerodynamic loads, namely lift, drag, and moment coefficients, are measured through Reynolds Averaged Navier Stokes (RANS) modeling and wind tunnel experiment. A simplified and parameterized RANS model is presented as a rapidly iterable approach to estimating the performance of trailing-edge circulation control on two dimensional airfoils, with the hypothesis that an optimized airfoil shape can be found which maximizes the lift coefficient increment generated by circulation control, through modification of the wing profile. The simplified modeling setup is compared with more conventional approaches to numerical simulation of circulation control. The performance of the simplified modeling scheme is then compared with wind tunnel studies, for both steady-state and dynamic performance, as functions of both momentum coefficient dCμ and chord-based Reynolds number Re_c. The dynamic performance for the model is studied to find an analog to the theoretical unsteady models of Wagner and Theodorsen. An adjoint optimization framework is used to find an optimal airfoil profile for circulation control. The optimized profile is then compared in both a simulation and a wind tunnel test study against a NACA0015 airfoil. In simulation, improvement between 12% and 15% is seen for the lift control authority for all values of dCμ and Re_c tested. In experiment, the optimized profile demonstrated improvements of up to 28% in lift control authority, dCL/dCμfor values of Cμ, and decreased performance for higher values of Cμ.
Show less
- Title
- Estimation of Platinum Oxide Degradation in Proton Exchange Membrane Fuel Cells
- Creator
- Ahmed, Niyaz Afnan
- Date
- 2024
- Description
-
The performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the...
Show moreThe performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the platinum catalyst. The production of platinum oxide is a major cause of the degradation of the fuel cell system, negatively affecting its performance and durability. In order to predict and prevent this degradation, this research examines a novel method to estimate degradation due to platinum oxide formation and predict the level of platinum oxide coverage over time. Mechanisms of platinum oxide formation are outlined and two methods are compared for platinum oxide estimation. Linear regression and two Artificial Neural Network (ANN) models, including a Recurrent Neural Network (RNN) and Feed-forward Back Propagation Neural Network (FFBPNN), are compared for estimation. The estimation model takes into account the influence of cell temperature and relative humidity.Evaluation of relative errors (RE) and root mean square error (RMSE) illustrates the superior performance of RNN in contrast to GT-Suite and FFBPNN. However, both RNN and GT-Suite showcase an average error rate below 5% while the FFBPNN had a higher error rate of approximately 7%. The RMSE of RNN shows mostly less compared to FFBPNN and GT-Suite, however, at 50% training data, GT-Suite shows lowest RMSE. These findings indicate that GT-Suite can be a valuable tool for estimating platinum oxide in fuel cells with a relatively low RE, but the RNN model may be more suitable for real-time estimation of platinum oxide degradation in PEM fuel cells, due to its accurate predictions and shorter computational time. This comprehensive approach provides crucial insights for optimizing fuel cell efficiency and implementing effective maintenance strategies.
Show less