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Title: Non-Hermitian Phononics
Creator: Mokhtari, Amir Ashkan
Date: 2021
Description: Non-Hermitian and open systems are those that interact with their environment by the ﬂows of energy, particles, and information. These systems...
Show moreNon-Hermitian and open systems are those that interact with their environment by the ﬂows of energy, particles, and information. These systems show rich physical behaviors such as unidirectional wave reflection, enhanced transmission, and enhanced sensitivity to external perturbations comparing to a Hermitian system. To study non-Hermitian and open systems, we first present key concepts and required mathematical tools such as the theory of linear operators, linear algebra, biorthogonality, and exceptional points. We first consider the operator properties of various phononic eigenvalue problems. The aim is to answer some fundamental questions about the eigenvalues and eigenvectors of phononic operators. These include questions about the potential real and complex nature of the eigenvalues, whether the eigenvectors form a complete basis, what are the right orthogonality relationships, and how to create a complete basis when none may exist at the outset. In doing so we present a unified understanding of the properties of the phononic eigenvalues and eigenvectors which would emerge from any numerical method employed to compute such quantities. Next, we apply the mentioned theories on the phononic operators to the problem of scattering of in-plane waves at an interface between a homogeneous medium and a layered composite. This problem is an example of a non self-adjoint operator with biorthogonal eigenvectors and a complex spectrum. Since this problem is non self-adjoint, the degeneracies in the spectrum generally represent a coalescing of both the eigenvalues and eigenvectors (exceptional points). These degeneracies appear in both the complex and real domains of the wavevector. After calculating the eigenvalues and eigenvectors, we then calculate the scattered fields through a novel application of the Betti-Rayleigh reciprocity theorem. Several numerical examples showing rich scattering phenomena are presented afterward. We also prove that energy flux conservation is a restatement of the biorthogonality relationship of the non self-adjoint operators. Finally, we discuss open elastodynamics as a subset of non-Hermitian systems. A basic concept in open systems is effective Hamiltonian. It is a Hamiltonian that acts in the space of reduced set of degrees of freedom in a system and describes only a part of the eigenvalue spectrum of the total Hamiltonian. We present the Feshbach projection operator formalism -- traditionally used for calculating effective Hamiltonians of subsystems in quantum systems -- in the context of mechanical wave propagation problems. The formalism allows for the direct formal representation of effective Hamiltonians of finite systems which are interacting with their environment. This results in a smaller set of equations which isolate the dynamics of the system from the rest of the larger problem that is usually infinite size. We then present the procedure to calculate the Green's function of effective Hamiltonian. Finally we solve the scattering problem in 1D discrete systems using the Green's function method.
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Title: Investigation in the Uncertainty of Chassis Dynamometer Testing for the Energy Characterization of Conventional, Electric and Automated Vehicles
Creator: Di Russo, Miriam
Date: 2023
Description: For conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their...
Show moreFor conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their energy performance exist. However, the regulations do not include requirements on the confidence value to associate with the results. As vehicles become more and more efficient to meet the stricter regulations mandates on emissions, fuel and energy consumption, traditional testing methods may become insufficient to validate these improvements, and may need revision. Without information about the accuracy associated with the results of those procedures however, adjustments and improvements are not possible, since no frame of reference exists. For connected and automated vehicles, there are no standard testing procedures, and researchers are still in the process of determining if current evaluation methods can be extended to test intelligent technologies and which metrics best represent their performance. For these vehicles is even more important to determine the uncertainty associated with these experimental methods and how they propagate to the final results. The work presented in this dissertation focuses on the development of a systematic framework for the evaluation of the uncertainty associated with the energy performance of conventional, electric and automated vehicles. The framework is based on a known statistical method, to determine the uncertainty associated with the different stages and processes involved in the experimental testing, and to evaluate how the accuracy of each parameter involved impacts the final results. The results demonstrate that the framework can be successfully applied to existing testing methods and provides a trustworthy value of accuracy to associate with the energy performance results, and can be easily extended to connected-automated vehicle testing to evaluate how novel experimental methods impact the accuracy and the confidence of the outputs. The framework can be easily be implemented into an existing laboratory environment to incorporate the uncertainty evaluation among the current results analyzed at the end of each test, and provide a reference for researchers to evaluate the actual benefits of new algorithms and optimization methods and understand margins for improvements, and by regulators to assess which parameters to enforce to ensure compliance and ensure projected benefits.
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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.
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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.
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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.
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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.
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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.
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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.
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