Matching Items (186)
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- All Subjects: Mechanical Engineering
- Genre: Doctoral Dissertation
- Creators: Arizona State University
Description
TolTEC is a three-band millimeter-wave, imaging polarimeter installed on the 50 m diameter Large Millimeter Telescope (LMT) in Mexico. This camera simultaneously images the focal plane at three wavebands centered at 1.1 mm (270 GHz), 1.4 mm (214 GHz), and 2.0 mm (150 GHz). TolTEC combines polarization-sensitive kinetic inductance detectors (KIDs) with the LMT to produce high resolution images of the sky in both total intensity and polarization. I present an overview of the TolTEC camera’s optical system and my contributions to the optomechanical design and characterization of the instrument. As part of my work with TolTEC, I designed the mounting structures for the cold optics within the cryostat accounting for thermal contraction to ensure the silicon lenses do not fracture when cooled. I also designed the large warm optics that re-image the light from the telescope, requiring me to perform static and vibration analyses to ensure the mounts correctly supported the mirrors. I discuss the various methods used to align the optics and the cryostat in the telescope. I discuss the Zemax optical model of TolTEC and compare it with measurements of the instrument to help with characterization. Finally, I present the results of stacking galaxies on data from the Atacama Cosmology Telescope (ACT) to measure the Sunyaev-Zel’dovich (SZ) effect and estimate the thermal energy in the gas around high red-shift, quiescent galaxies as an example of science that could be done with TolTEC data. Since the camera combines high angular resolution with images at three wavelengths near distinct SZ features, TolTEC will provide precise measurements to learn more about these types of galaxies.
ContributorsLunde, Emily Louise (Author) / Mauskopf, Philip (Thesis advisor) / Groppi, Christopher (Committee member) / Scannapieco, Evan (Committee member) / Noble, Allison (Committee member) / Bryan, Sean (Committee member) / Arizona State University (Publisher)
Created2023
Description
Walking and mobility are essential aspects of our daily lives, enabling us to engage in various activities. Gait disorders and impaired mobility are widespread challenges faced by older adults and people with neurological injuries, as these conditions can significantly impact their quality of life, leading to a loss of independence and an increased risk of mortality. In response to these challenges, rehabilitation, and assistive robotics have emerged as promising alternatives to conventional gait therapy, offering potential solutions that are less labor-intensive and costly. Despite numerous advances in wearable lower-limb robotics, their current applicability remains confined to laboratory settings. To expand their utility to broader gait impairments and daily living conditions, there is a pressing need for more intelligent robot controllers. In this dissertation, these challenges are tackled from two perspectives: First, to improve the robot's understanding of human motion and intentions which is crucial for assistive robot control, a robust human locomotion estimation technique is presented, focusing on measuring trunk motion. Employing an invariant extended Kalman filtering method that takes sensor misplacement into account, improved convergence properties over the existing methods for different locomotion modes are shown. Secondly, to enhance safe and effective robot-aided gait training, this dissertation proposes to directly learn from physical therapists' demonstrations of manual gait assistance in post-stroke rehabilitation.
Lower-limb kinematics of patients and assistive force applied by therapists to the patient's leg are measured using a wearable sensing system which includes a custom-made force sensing array. The collected data is then used to characterize a therapist's strategies. Preliminary analysis indicates that knee extension and weight-shifting play pivotal roles in shaping a therapist's assistance strategies, which are then incorporated into a virtual impedance model that effectively captures high-level therapist behaviors throughout a complete training session. Furthermore, to introduce safety constraints in the design of such controllers, a safety-critical learning framework is explored through theoretical analysis and simulations. A safety filter incorporating an online iterative learning component is introduced to bring robust safety guarantees for gait robotic assistance and training, addressing challenges such as stochasticity and the absence of a known prior dynamic model.
ContributorsRezayat Sorkhabadi, Seyed Mostafa (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
Tire blowout often occurs during driving, which can suddenly disturb vehicle motions and seriously threaten road safety. Currently, there is still a lack of effective methods to mitigate tire blowout risks in everyday traffic, even for automated vehicles. To fundamentally study and systematically resolve the tire blowout issue for automated vehicles, a collaborative project between General Motors (GM) and Arizona State University (ASU) has been conducted since 2018. In this dissertation, three main contributions of this project will be presented. First, to explore vehicle dynamics with tire blowout impacts and establish an effective simulation platform for close-loop control performance evaluation, high-fidelity tire blowout models are thoroughly developed by explicitly considering important vehicle parameters and variables. Second, since human cooperation is required to control Level 2/3 partially automated vehicles (PAVs), novel shared steering control schemes are specifically proposed for tire blowout to ensure safe vehicle stabilization via cooperative driving. Third, for Level 4/5 highly automated vehicles (HAVs) without human control, the development of control-oriented vehicle models, controllability study, and automatic control designs are performed based on impulsive differential systems (IDS) theories.
Co-simulations Matlab/Simulink® and CarSim® are conducted to validate performances of all models and control designs proposed in this dissertation. Moreover, a scaled test vehicle at ASU and a full-size test vehicle at GM are well instrumented for data collection and control implementation. Various tire blowout experiments for different scenarios are conducted for more rigorous validations. Consequently, the proposed high-fidelity tire blowout models can correctly and more accurately describe vehicle motions upon tire blowout. The developed shared steering control schemes for PAVs and automatic control designs for HAVs can effectively stabilize a vehicle to maintain path following performance in the driving lane after tire blowout.
In addition to new research findings and developments in this dissertation, a pending patent for tire blowout detection is also generated in the tire blowout project. The obtained research results have attracted interest from automotive manufacturers and could have a significant impact on driving safety enhancement for automated vehicles upon tire blowout.
ContributorsLi, Ao (Author) / Chen, Yan (Thesis advisor) / Berman, Spring (Committee member) / Kannan, Arunachala Mada (Committee member) / Liu, Yongming (Committee member) / Lin, Wen-Chiao (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2023
The Intercoupling of Thermal Transport and Mechanical Properties in Colloidal Nanocrystal Assemblies
Description
Colloidal nanocrystals (NCs) are promising candidates for a wide range of applications (electronics, optoelectronics, photovoltaics, thermoelectrics, etc.). Mechanical and thermal transport property play very important roles in all of these applications. On one hand, mechanical robustness and high thermal conductivity are desired in electronics, optoelectronics, and photovoltaics. This improves thermomechanical stability and minimizes the temperature rise during the device operation. On the other hand, low thermal conductivity is desired for higher thermoelectric figure of merit (ZT). This dissertation demonstrates that ligand structure and nanocrystal ordering are the primary determining factors for thermal transport and mechanical properties in colloidal nanocrystal assemblies. To eliminate the mechanics and thermal transport barrier, I first propose a ligand crosslinking method to improve the thermal transport across the ligand-ligand interface and thus increasing the overall thermal conductivity of NC assemblies. Young’s modulus of nanocrystal solids also increases simultaneously upon ligand crosslinking. My thermal transport measurements show that the thermal conductivity of the iron oxide NC solids increases by a factor of 2-3 upon ligand crosslinking. Further, I demonstrate that, though with same composition, long-range ordered nanocrystal superlattices possess higher mechanical and thermal transport properties than disordered nanocrystal thin films. Experimental measurements along with theoretical modeling indicate that stronger ligand-ligand interaction in NC superlattice accounts for the improved mechanics and thermal transport. This suggests that NC/ligand arranging order also plays important roles in determining mechanics and thermal transport properties of NC assemblies. Lastly, I show that inorganic ligand functionalization could lead to tremendous mechanical enhancement (a factor of ~60) in NC solids. After ligand exchange and drying, the short inorganic Sn2S64- ligands dissociate into a few atomic layers of amorphous SnS2 at room temperature and interconnects the neighboring NCs. I observe a reverse Hall-Petch relation as the size of NC decreases. Both atomistic simulations and analytical phase mixture modeling identify the grain boundaries and their activities as the mechanic bottleneck.
ContributorsWang, Zhongyong (Author) / Wang, Robert RW (Thesis advisor) / Wang, Liping LW (Committee member) / Newman, Nathan NN (Committee member) / Arizona State University (Publisher)
Created2021
Description
A well-insulated dark conventional rooftop can be hotter than any other urban surface, including pavements. Since rooftops cover around 20 – 25% of most urban areas, their role in the urban heat island effect is significant. In general, buildings exchange heat with the surroundings in three ways: heat release from the cooling/heating system, air exchange associated with exfiltration and relief air, and heat transfer between the building envelope and surroundings. Several recent studies show that the building envelope generates more heat release into the environment than any other building component.Current advancements in material science have enabled the development of materials and coatings with very high solar reflectance and thermal emissivity, and that can alter their radiative properties based on surface temperature. This dissertation is an effort to quantify the impact of recent developments in such technologies on urban air. The current study addresses three specific unresolved topics: 1) the relative importance of rooftop solar reflectance and thermal emissivity, 2) the role of rooftop radiative properties in different climates, and 3) the impact of temperature-adaptive exterior materials/coatings on building energy savings and urban cooling. The findings from this study show that the use of rooftop materials with solar reflectance above 0.9 maintain the surface temperature below ambient air temperature most of the time, even when the materials have conventional thermal emissivity (0.9). This research has demonstrated that for hot cities, rooftops with high solar reflectance and thermal emittance maximize building energy savings and always cool the surrounding air. For moderate climate regions, high solar reflectance and low thermal emittance result in the greatest building energy cost savings. This combination of radiative properties cools the air during the daytime and warms it at night. Finally, this research found that temperature-adaptive materials could play a significant role in reducing utility costs for poorly insulated buildings, but that they heat the surrounding air in the winter, irrespective of the rooftop insulation.
Through the detailed analysis of building façade radiative properties, this dissertation offers climate-specific design guidance that can be used to simultaneously optimize energy costs while minimizing adverse warming of the surrounding environment.
ContributorsPrem Anand Jayaprabha, Jyothis Anand (Author) / Sailor, David (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Huang, Huei-Ping (Committee member) / Wang, Liping (Committee member) / Yeom, Dongwoo Jason (Committee member) / Arizona State University (Publisher)
Created2022
Description
When solving analysis, estimation, and control problems for Partial Differential Equations (PDEs) via computational methods, one must resolve three main challenges: (a) the lack of a universal parametric representation of PDEs; (b) handling unbounded differential operators that appear as parameters; and (c), enforcing auxiliary constraints such as Boundary conditions and continuity conditions. To address these challenges, an alternative representation of PDEs called the `Partial Integral Equation' (PIE) representation is proposed in this work. Primarily, the PIE representation alleviates the problem of the lack of a universal parametrization of PDEs since PIEs have, at most, $12$ Partial Integral (PI) operators as parameters. Naturally, this also resolves the challenges in handling unbounded operators because PI operators are bounded linear operators. Furthermore, for admissible PDEs, the PIE representation is unique and has no auxiliary constraints --- resolving the last of the $3$ main challenges. The PIE representation for a PDE is obtained by finding a unique unitary map from the states of the PIE to the states of the PDE. This map shows a PDE and its associated PIE have equivalent system properties, including well-posedness, internal stability, and I/O behavior. Furthermore, this unique map also allows us to construct a well-defined dual representation that can be used to solve optimal control problems for a PDE. Using the equivalent PIE representation of a PDE, mathematical and computational tools are developed to solve standard problems in Control theory for PDEs. In particular, problems such as a test for internal stability, Input-to-Output (I/O) $L_2$-gain, $\hinf$-optimal state observer design, and $\hinf$-optimal full state-feedback controller design are solved using convex-optimization and Lyapunov methods for linear PDEs in one spatial dimension. Once the PIE associated with a PDE is obtained, Lyapunov functions (or storage functions) are parametrized by positive PI operators to obtain a solvable convex formulation of the above-stated control problems. Lastly, the methods proposed here are applied to various PDE systems to demonstrate the application.
ContributorsShivakumar, Sachin (Author) / Peet, Matthew (Thesis advisor) / Nedich, Angelia (Committee member) / Marvi, Hamidreza (Committee member) / Platte, Rodrigo (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2024