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- All Subjects: Mechanical Engineering
- All Subjects: soft robotics
- All Subjects: Biomechanics
- Creators: Rykaczewski, Konrad
Description
Dehumidifiers are ubiquitous and essential household appliances in many parts of the world. They are used extensively in tropical and sub-tropical environments to lower humidity in living spaces, where high ambient humidity can lead to numerous negative health effects from mild physical discomfort to more serious conditions such as mold build up in structures and dangerous illnesses in humans. Most common dehumidifiers are based on conventional mechanical refrigeration cycles, where the effects of condensation heat transfer play a critical role in their effectiveness. In these devices, humid ambient air flows over a cold evaporator, which lowers the temperature of the humid ambient air below its dew point temperature and therefore decreases its water content by causing liquid water condensation on the evaporator surface. The rate at which humidity can be extracted from the ambient air is governed in part by how quickly the evaporator can shed the condensed droplets. Recent advances in soft, stretchable, thermally enhanced (through the addition of liquid metals) silicone tubing offer the potential to use these stretchable tubes in place of conventional copper pipe for applications such as dehumidification. Copper is a common material choice for dehumidifier evaporator tubing owing to its ubiquity and its high thermal conductivity, but it has several thermal downsides. Specifically, copper tubes remain static and typically rely on gravity alone to remove water droplets when they reach a sufficient mass. Additionally, copper’s naturally hydrophilic surface promotes film-wise condensation, which is substantially less effective than dropwise condensation. In contrast to copper, thermally enhanced soft stretchable tubes have naturally hydrophobic surfaces that promote the more effective dropwise condensation mode and a soft surface that offers higher nucleation density. However, soft surfaces also increase droplet pinning, which inhibits their departure. This work experimentally explores the effects of periodic axial stretching and retraction of soft tubing internally cooled with water on droplet condensation dynamics on its exterior surface. Results are discussed in terms of overall system thermal performance and real-time condensation imaging. An overall null result is discovered, and recommendations for future experiments are made.
Contributorsnordstog, thomas (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Devasenathipathy, Shankar (Committee member) / Arizona State University (Publisher)
Created2022
Description
Spray flows are important in a myriad of practical applications including fuel injection, ink-jet printing, agricultural sprays, and industrial processes. Two-phase sprays find particular use for spot cooling applications with high heat fluxes as in casting processes and power electronics. Computability of sprays in a cost-effective manner provides a path to optimize the design of nozzles to tune the spray characteristics for the needs of a particular application. Significant research has so far been devoted to understand and characterize spray flows better, be it from a theoretical, experimental or computational standpoint. The current thesis discusses a methodology for modeling primary atomization using the Quadratic Formula which is derived from an integral formulation of the governing equations. The framework is then applied to different examples of flat-fan hydraulic sprays. For each case, the spray is first resolved as a continuous fluid using the volume of fluid method. Atomization criterion is then applied to the velocity flow-field to determine the sites for primary atomization. At each site, local diameters for particle injection is determined using the quadratic formula. The trajectory of injected particles are then monitored through a particle tracking algorithm. The results from the numerical analysis are compared with experimental data to validate the computational framework.
ContributorsBhardwaj, Angshuman (Author) / Lee, T.-W. (Thesis advisor) / Herrmann, Marcus (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2022
Description
Soft robotics has garnered attention for its substantial prospective in various domains, such as manipulation and interactions with humans, by offering competitive advantages against rigid robotic systems, including inherent compliance and variable stiffness. Despite these benefits, their theoretically infinite degrees of freedom and prominent nonlinearities pose significant challenges in developing dynamic models and guiding the robots along desired paths. Additionally, soft robots may exhibit rigid behaviors and potentially collide with their surroundings during path tracking tasks, particularly when possible contact points are unknown. In this dissertation, reduced-order models are used to describe the behaviors of three different soft robot designs, including both linear parameter varying (LPV) and augmented rigid robot (ARR) models. While the reduced-order model captures the majority of the soft robot's dynamics, modeling uncertainties notably remain. Non-repeated modeling uncertainties are addressed by categorizing them as a lumped disturbance, employing two methodologies, $H_\infty$ method and nonlinear disturbance observer (NDOB) based sliding mode control, for its rejection. For repeated disturbances, an iterative learning control (ILC) with a P-type learning function is implemented to enhance trajectory tracking efficacy. Furthermore,for non-repeated disturbances, the NDOB facilitates the contact estimation, and its results are jointly used with a switching algorithm to modify the robot trajectories. The stability proof of all controllers and corresponding simulation and experimental results are provided. For a path tracking task of a soft robot with multi-segments, a robust control strategy that combines a LPV model with an innovative improved nonlinear disturbance observer-based adaptive sliding mode control (INASMC). The control framework employs a first-order LPV model for dynamic representation, leverages an improved disturbance observer for accurate disturbance forecasting, and utilizes adaptive sliding mode control to effectively counteract uncertainties. The tracking error under the proposed controller is proven to be asymptotically stable, and the controller's effectiveness is is validated with simulation and experimental results. Ultimately, this research mitigates the inherent uncertainty in soft robot modeling, thereby enhancing their functionality in contact-intensive tasks.
ContributorsQIAO, ZHI (Author) / Zhang, Wenlong (Thesis advisor) / Marvi, Hamidreza (Committee member) / Lee, Hyunglae (Committee member) / Berman, Spring (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2023
Description
Sweat evaporation is fundamental to human thermoregulation, yet our knowledge of the microscale sweat droplet evaporation dynamics is very limited. To study sweat droplet evaporation, a reliable way to measure sweat evaporation rate from skin and simultaneously image the droplet dynamics through midwave infrared thermography (MWIR) or optical coherence tomography (OCT) is required. Ventilated capsule is a common device employed for measuring sweat evaporation rates in physiological studies. However, existing designs of ventilated capsules with cylindrical flow chambers create unrealistic flow conditions that include flow separation and swirling. To address this problem, this thesis introduces a ventilated capsule with rectangular sweat evaporation area preceded by a diffuser section with geometry based on wind tunnel design guidelines. To allow for OCT or MWIR imaging, a provision to install an acrylic or a sapphire window directly over the exposed skin surface being measured is incorporated in the design. In addition to the capsule, a simplified artificial sweating surface that can supply water in a filmwise, single or multiple droplet form was developed. The performance of the capsule is demonstrated using the artificial sweating surface along with example MWIR imaging.
ContributorsRamesh, Rajesh (Author) / Rykaczewski, Konrad (Thesis advisor) / Kavouras, Stavros (Committee member) / Phelan, Patrick (Committee member) / Burke, Richard (Committee member) / Arizona State University (Publisher)
Created2023
Description
While wearable soft robots have successfully addressed many inherent design limitations faced by wearable rigid robots, they possess a unique set of challenges due to their soft and compliant nature. Some of these challenges are present in the sensing, modeling, control and evaluation of wearable soft robots. Machine learning algorithms have shown promising results for sensor fusion with wearable robots, however, they require extensive data to train models for different users and experimental conditions. Modeling soft sensors and actuators require characterizing non-linearity and hysteresis, which complicates deriving an analytical model. Experimental characterization can capture the characteristics of non-linearity and hysteresis but requires developing a synthesized model for real-time control. Controllers for wearable soft robots must be robust to compensate for unknown disturbances that arise from the soft robot and its interaction with the user. Since developing dynamic models for soft robots is complex, inaccuracies that arise from the unmodeled dynamics lead to significant disturbances that the controller needs to compensate for. In addition, obtaining a physical model of the human-robot interaction is complex due to unknown human dynamics during walking. Finally, the performance of soft robots for wearable applications requires extensive experimental evaluation to analyze the benefits for the user. To address these challenges, this dissertation focuses on the sensing, modeling, control and evaluation of soft robots for wearable applications. A model-based sensor fusion algorithm is proposed to improve the estimation of human joint kinematics, with a soft flexible robot that requires compact and lightweight sensors. To overcome limitations with rigid sensors, an inflatable soft haptic sensor is developed to enable gait sensing and haptic feedback. Through experimental characterization, a mathematical model is derived to quantify the user's ground reaction forces and the delivered haptic force. Lastly, the performance of a wearable soft exosuit in assisting human users during lifting tasks is evaluated, and the benefits obtained from the soft robot assistance are analyzed.
ContributorsQuiñones Yumbla, Emiliano (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
Thermal management of electronics is critical to meet the increasing demand for high power and performance. Thermal interface materials (TIMs) play a key role in dissipating heat away from the microelectronic chip and hence are a crucial component in electronics cooling. Challenges persist with overcoming the interfacial boundary resistance and filler particle connectivity in TIMs to achieve thermal percolation while maintaining mechanical compliance. Gallium-based liquid metal (LM) capsules offer a unique set of thermal-mechanical characteristics that make them suitable candidates for high-performance TIM fillers. This dissertation research focuses on resolving the fundamental challenges posed by integration of LM fillers in polymer matrix. First, the rupture mechanics of LM capsules under pressure is identified as a key factor that dictates the thermal connectivity between LM-based fillers. This mechanism of oxide “popping” in LM particle beds independent of the matrix material provides insights in overcoming the particle-particle connectivity challenges. Second, the physical barrier introduced due to the polymer matrix needs to be overcome to achieve thermal percolation. Matrix fluid viscosity impacts thermal transport, with high viscosity uncured matrix inhibiting the thermal bridging of fillers. In addition, incorporation of solid metal co-fillers that react with LM fillers is adopted to facilitate popping of LM oxide in uncured polymer to overcome this matrix barrier. Solid silver metal additives are used to rupture the LM oxide, form inter-metallic alloy (IMC), and act as thermal anchors within the matrix. This results in the formation of numerous thermal percolation paths and hence enhances heat transport within the composite. Further, preserving this microstructure of interconnected multiphase filler system with thermally conductive percolation pathways in a cured polymer matrix is critical to designing high-performing TIM pads. Viscosity of the precursor polymer solution prior to curing plays a major role in the resulting thermal conductivity. A multipronged strategy is developed that synergistically combines reactive solid and liquid fillers, a polymer matrix with low pre-cure viscosity, and mechanical compression during thermal curing. The results of this dissertation aim to provide fundamental insights into the integration of LMs in polymer composites and give design knobs to develop high thermally conducting soft composites.
ContributorsUppal, Aastha (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Thesis advisor) / Kwon, Beomjin (Committee member) / Choksi, Gaurang (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2022
Description
Soft robots currently rely on additional hardware such as pumps, high voltage supplies,light generation sources, and magnetic field generators for their operation. These components
resist miniaturization; thus, embedding them into small-scale soft robots is challenging.
This issue limits their applications, especially in hyper-redundant mobile robots. This
dissertation aims at addressing some of the challenges associated with creating miniature,
untethered soft robots that can function without any attachment to external power supplies
or receiving any control signals from outside sources. This goal is accomplished by introducing
a soft active material and a manufacturing method that together, facilitate the
miniaturization of soft robots and effectively supports their autonomous, mobile operation
without any connection to outside equipment or human intervention.
The soft active material presented here is a hydrogel based on a polymer called poly(Nisopropylacrylamide)
(PNIPAAm). This hydrogel responds to changes in the temperature
and responds by expanding or contracting. A major challenge regarding PNIPAAm-based
hydrogels is their slow response. This challenge is addressed by introducing a mixedsolvent
photo-polymerization technique that alters the pore structure of the hydrogel and
facilitates the water transport and thus the rate of volume change. Using this technique,
the re-swelling response time of hydrogels is reduced to 2:4min – over 25 times faster
than hydrogels demonstrated previously. The material properties of hydrogels including
their response rate and Young’s modulus are tuned simultaneously. The one-step photopolymerization
using UV light is performed in under 15 sec, which is a significant improvement
over thermo-polymerization, which takes anywhere between a few minutes to
several hours. Photopolymerization is key towards simplifying recipes, improving access
to these techniques, and making them tractable for iterative design processes.
To address the manufacturing challenges, soft voxel actuators (SVAs) are presented.
SVAs are actuated by electrical currents through Joule heating. SVAs weighing only 100 mg require small footprint microcontrollers for their operation which can be embedded
in the robotic system. The advantages of hydrogel-based SVAs are demonstrated through
different robotic platforms namely a hyper-redundant manipulator with 16 SVAs, an untethered
miniature robot for mobile underwater applications using 8 SVAs, and a gripper
using 32 SVAs.
ContributorsKhodambashi, Roozbeh (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2021
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
Human exposure to extreme heat is becoming more prevalent due to increasing urbanization and changing climate. In many extreme heat conditions, thermal radiation (from solar to emitted by the surrounding) is a significant contributor to heating the body, among other modes of heat transfer. Therefore, accurately measuring radiative heat flux on a human body is becoming increasingly important for calculating human thermal comfort and heat safety in extreme conditions. Most often, radiant heat exchange between the human body and surroundings is quantified using mean radiant temperature, T_mrt. This value is commonly measured using globe or cylindrical radiometers. It is based on radiation absorbed by the surface of the radiometer, which can be calculated using a surface energy balance involving both convection and emitted radiation at steady state. This convection must be accounted for and is accomplished using a traditional heat transfer coefficient correlation with measured wind speed. However, the utilized correlations are based on wind tunnel measurements and do not account for any turbulence present in the air. The latter can even double the heat transfer coefficient, so not accounting for it can introduce major errors in T_mrt. This Thesis focuses on the development, and testing of a cost-effective heated cylinder to directly measure the convection heat transfer coefficient in field conditions, which can be used for accounting convection in measuring T_mrt using a cylindrical radiometer. An Aluminum cylinder of similar dimensions as that of a cylindrical radiometer was heated using strip heaters, and the surface temperature readings were recorded to estimate the convection heat transfer coefficient, h. Various tests were conducted to test this concept. It was observed that heated cylinders take significantly less time to reach a steady state and respond to velocity change quicker than existing regular-sized globe thermometers. It was also shown that, for accurate estimation of h, it is required to measure the outer surface temperature than the center temperature. Furthermore, the value calculated matches well in range with classic correlations that include velocity, showing proof of concept.
ContributorsGuddanti, Sai Susmitha (Author) / Rykaczewski, Konrad (Thesis advisor) / Vanos, Jennifer (Committee member) / Wang, Robert (Committee member) / Burke, Richard (Committee member) / Arizona State University (Publisher)
Created2023
Description
The microelectronics industry is actively focusing on advanced packaging technologies, notably on three-dimensional stacking of heterogeneous integrated (3D-HI) circuits for enhanced performance. Despite its computational performance benefits, this approach faces challenges in thermal management due to increased power density and heat generation. Conventional cooling methods struggle to address this issue effectively. This study investigates microfluidic intralayer cooling techniques using analytical correlation and computational fluid dynamics (CFD) principles to propose a method capable of managing thermal performance across varying load conditions. The proposed configuration achieved a dissipation of 40 W/cm2 with a volumetric flow rate of 200 mL/min, maintaining chip temperature at 315K. Additionally, extreme hotspot conditions generating 1kW/cm2, along with the presence of thermal resistance from redistribution layers (RDLs), are analyzed. This research aims to establish a model for understanding geometric property variations under different heat flux conditions in 3D heterogeneous integration of semiconductor packaging.
ContributorsGandhi, Rohit Mahavir (Author) / Wang, Robert Y (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2024