Matching Items (15)
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- All Subjects: Mechanical Engineering
- Genre: Doctoral Dissertation
- Creators: Dai, Lenore
Description
The development of advanced, anthropomorphic artificial hands aims to provide upper extremity amputees with improved functionality for activities of daily living. However, many state-of-the-art hands have a large number of degrees of freedom that can be challenging to control in an intuitive manner. Automated grip responses could be built into artificial hands in order to enhance grasp stability and reduce the cognitive burden on the user. To this end, three studies were conducted to understand how human hands respond, passively and actively, to unexpected perturbations of a grasped object along and about different axes relative to the hand. The first study investigated the effect of magnitude, direction, and axis of rotation on precision grip responses to unexpected rotational perturbations of a grasped object. A robust "catch-up response" (a rapid, pulse-like increase in grip force rate previously reported only for translational perturbations) was observed whose strength scaled with the axis of rotation. Using two haptic robots, we then investigated the effects of grip surface friction, axis, and direction of perturbation on precision grip responses for unexpected translational and rotational perturbations for three different hand-centric axes. A robust catch-up response was observed for all axes and directions for both translational and rotational perturbations. Grip surface friction had no effect on the stereotypical catch-up response. Finally, we characterized the passive properties of the precision grip-object system via robot-imposed impulse perturbations. The hand-centric axis associated with the greatest translational stiffness was different than that for rotational stiffness. This work expands our understanding of the passive and active features of precision grip, a hallmark of human dexterous manipulation. Biological insights such as these could be used to enhance the functionality of artificial hands and the quality of life for upper extremity amputees.
ContributorsDe Gregorio, Michael (Author) / Santos, Veronica J. (Thesis advisor) / Artemiadis, Panagiotis K. (Committee member) / Santello, Marco (Committee member) / Sugar, Thomas (Committee member) / Helms Tillery, Stephen I. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focusses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.
ContributorsMoncada, Albert (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2012
Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
Description
Structural health management (SHM) is emerging as a vital methodology to help engineers improve the safety and maintainability of critical structures. SHM systems are designed to reliably monitor and test the health and performance of structures in aerospace, civil, and mechanical engineering applications. SHM combines multidisciplinary technologies including sensing, signal processing, pattern recognition, data mining, high fidelity probabilistic progressive damage models, physics based damage models, and regression analysis. Due to the wide application of carbon fiber reinforced composites and their multiscale failure mechanisms, it is necessary to emphasize the research of SHM on composite structures. This research develops a comprehensive framework for the damage detection, localization, quantification, and prediction of the remaining useful life of complex composite structures. To interrogate a composite structure, guided wave propagation is applied to thin structures such as beams and plates. Piezoelectric transducers are selected because of their versatility, which allows them to be used as sensors and actuators. Feature extraction from guided wave signals is critical to demonstrate the presence of damage and estimate the damage locations. Advanced signal processing techniques are employed to extract robust features and information. To provide a better estimate of the damage for accurate life estimation, probabilistic regression analysis is used to obtain a prediction model for the prognosis of complex structures subject to fatigue loading. Special efforts have been applied to the extension of SHM techniques on aerospace and spacecraft structures, such as UAV composite wings and deployable composite boom structures. Necessary modifications of the developed SHM techniques were conducted to meet the unique requirements of the aerospace structures. The developed SHM algorithms are able to accurately detect and quantify impact damages as well as matrix cracking introduced.
ContributorsLiu, Yingtao (Author) / Chattopadhyay, Aditi (Thesis advisor) / Rajadas, John (Committee member) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012
Description
Damage assessment and residual useful life estimation (RULE) are essential for aerospace, civil and naval structures. Structural Health Monitoring (SHM) attempts to automate the process of damage detection and identification. Multiscale modeling is a key element in SHM. It not only provides important information on the physics of failure, such as damage initiation and growth, the output can be used as "virtual sensing" data for detection and prognosis. The current research is part of an ongoing multidisciplinary effort to develop an integrated SHM framework for metallic aerospace components. In this thesis a multiscale model has been developed by bridging the relevant length scales, micro, meso and macro (or structural scale). Micro structural representations obtained from material characterization studies are used to define the length scales and to capture the size and orientation of the grains at the micro level. Parametric studies are conducted to estimate material parameters used in this constitutive model. Numerical and experimental simulations are performed to investigate the effects of Representative Volume Element (RVE) size, defect area fraction and distribution. A multiscale damage criterion accounting for crystal orientation effect is developed. This criterion is applied for fatigue crack initial stage prediction. A damage evolution rule based on strain energy density is modified to incorporate crystal plasticity at the microscale (local). Optimization approaches are used to calculate global damage index which is used for the RVE failure prediciton. Potential cracking directions are provided from the damage criterion simultaneously. A wave propagation model is incorporated with the damage model to detect changes in sensing signals due to plastic deformation and damage growth.
ContributorsLuo, Chuntao (Author) / Chattopadhyay, Aditi (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2011
Description
Gels are three-dimensional polymer networks with entrapped solvent (water etc.). They bear amazing features such as stimuli-responsive (temperature, PH, electric field etc.), high water content and biocompatibility and thus find a lot of applications. To understand the complex physics behind gel's swelling phenomenon, it is important to build up fundamental mechanical model and extend to complicated cases. In this dissertation, a coupled large deformation and diffusion model regarding gel's swelling behavior is presented. In this model, free-energy of the total gel is constituted by polymer stretching energy and polymer-solvent mixing energy. In-house nonlinear finite element code is implemented with fast computational capability. Complex phenomenon such as buckling and healing of cracked gel by swelling are studied. Due to the wide coverage of polymeric materials and solvents, solvent diffusion in gels not only follows Fickian diffusion law where concentration map is continuous but also follows non-Fickian diffusion law where concentration map shows high gradient. Phenomenological model with viscoelastic polymer constitutive and concentration dependent diffusivity is created. The model well captures this special diffusion phenomenon such as sharp diffusion front and distinctive swollen and unswollen region.
ContributorsZhang, Jiaping (Author) / Jiang, Hanqing (Thesis advisor) / Peralta, Pedro (Committee member) / Dai, Lenore (Committee member) / Rajan, Subramaniam D. (Committee member) / Chawla, Nikhilesh (Committee member) / Arizona State University (Publisher)
Created2012
Description
The rapid progress of solution-phase synthesis has led colloidal nanocrystals one of the most versatile nanoscale materials, provided opportunities to tailor material's properties, and boosted related technological innovations. Colloidal nanocrystal-based materials have been demonstrated success in a variety of applications, such as LEDs, electronics, solar cells and thermoelectrics. In each of these applications, the thermal transport property plays a big role. An undesirable temperature rise due to inefficient heat dissipation could lead to deleterious effects on devices' performance and lifetime. Hence, the first project is focused on investigating the thermal transport in colloidal nanocrystal solids. This study answers the question that how the molecular structure of nanocrystals affect the thermal transport, and provides insights for future device designs. In particular, PbS nanocrystals is used as a monitoring system, and the core diameter, ligand length and ligand binding group are systematically varied to study the corresponding effect on thermal transport.
Next, a fundamental study is presented on the phase stability and solid-liquid transformation of metallic (In, Sn and Bi) colloidal nanocrystals. Although the phase change of nanoparticles has been a long-standing research topic, the melting behavior of colloidal nanocrytstals is largely unexplored. In addition, this study is of practical importance to nanocrystal-based applications that operate at elevated temperatures. Embedding colloidal nanocrystals into thermally-stable polymer matrices allows preserving nanocrystal size throughout melt-freeze cycles, and therefore enabling observation of stable melting features. Size-dependent melting temperature, melting enthalpy and melting entropy have all been measured and discussed.
In the next two chapters, focus has been switched to developing colloidal nanocrystal-based phase change composites for thermal energy storage applications. In Chapter 4, a polymer matrix phase change nanocomposite has been created. In this composite, the melting temperature and energy density could be independently controlled by tuning nanocrystal diameter and volume fractions. In Chapter 5, a solution-phase synthesis on metal matrix-metal nanocrytal composite is presented. This approach enables excellent morphological control over nanocrystals and demonstrated a phase change composite with a thermal conductivity 2 - 3 orders of magnitude greater than typical phase change materials, such as organics and molten salts.
Next, a fundamental study is presented on the phase stability and solid-liquid transformation of metallic (In, Sn and Bi) colloidal nanocrystals. Although the phase change of nanoparticles has been a long-standing research topic, the melting behavior of colloidal nanocrytstals is largely unexplored. In addition, this study is of practical importance to nanocrystal-based applications that operate at elevated temperatures. Embedding colloidal nanocrystals into thermally-stable polymer matrices allows preserving nanocrystal size throughout melt-freeze cycles, and therefore enabling observation of stable melting features. Size-dependent melting temperature, melting enthalpy and melting entropy have all been measured and discussed.
In the next two chapters, focus has been switched to developing colloidal nanocrystal-based phase change composites for thermal energy storage applications. In Chapter 4, a polymer matrix phase change nanocomposite has been created. In this composite, the melting temperature and energy density could be independently controlled by tuning nanocrystal diameter and volume fractions. In Chapter 5, a solution-phase synthesis on metal matrix-metal nanocrytal composite is presented. This approach enables excellent morphological control over nanocrystals and demonstrated a phase change composite with a thermal conductivity 2 - 3 orders of magnitude greater than typical phase change materials, such as organics and molten salts.
ContributorsLiu, Minglu (Author) / Wang, Robert Y (Thesis advisor) / Wang, Liping (Committee member) / Rykaczewski, Konrad (Committee member) / Phelan, Patrick (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2015
Description
The energy crisis in the past decades has greatly boosted the search for alternatives to traditional fossil foils, and solar energy stands out as an important candidate due to its cleanness and abundance. However, the relatively low conversion efficiency and energy density strongly hinder the utilization of solar energy in wider applications. This thesis focuses on employing metamaterials and metafilms to enhance the conversion efficiency of solar thermal, solar thermophotovoltaic (STPV) and photovoltaic systems.
A selective metamaterial solar absorber is designed in this thesis to maximize the absorbed solar energy and minimize heat dissipation through thermal radiation. The theoretically designed metamaterial solar absorber exhibits absorptance higher than 95% in the solar spectrum but shows emittance less than 4% in the IR regime. This metamaterial solar absorber is further experimentally fabricated and optically characterized. Moreover, a metafilm selective absorber with stability up to 600oC is introduced, which exhibits solar absorptance higher than 90% and IR emittance less than 10%.
Solar thermophotovoltaic energy conversion enhanced by metamaterial absorbers and emitters is theoretically investigated in this thesis. The STPV system employing selective metamaterial absorber and emitter is investigated in this work, showing its conversion efficiency between 8% and 10% with concentration factor varying between 20 and 200. This conversion efficiency is remarkably enhanced compared with the conversion efficiency for STPV system employing black surfaces (<2.5%).
Moreover, plasmonic light trapping in ultra-thin solar cells employing concave grating nanostructures is discussed in this thesis. The plasmonic light trapping inside an ultrathin GaAs layer in the film-coupled metamaterial structure is numerically demonstrated. By exciting plasmonic resonances inside this structure, the short-circuit current density for the film-coupled metamaterial solar cell is three times the short-circuit current for a free-standing GaAs layer.
The dissertation is concluded by discussing about the future work on selective solar thermal absorbers, STPV/TPV systems and light trapping structures. Possibilities to design and fabricate solar thermal absorber with better thermal stability will be discussed, the experimental work of TPV system will be conducted, and the light trapping in organic and perovskite solar cells will be looked into.
A selective metamaterial solar absorber is designed in this thesis to maximize the absorbed solar energy and minimize heat dissipation through thermal radiation. The theoretically designed metamaterial solar absorber exhibits absorptance higher than 95% in the solar spectrum but shows emittance less than 4% in the IR regime. This metamaterial solar absorber is further experimentally fabricated and optically characterized. Moreover, a metafilm selective absorber with stability up to 600oC is introduced, which exhibits solar absorptance higher than 90% and IR emittance less than 10%.
Solar thermophotovoltaic energy conversion enhanced by metamaterial absorbers and emitters is theoretically investigated in this thesis. The STPV system employing selective metamaterial absorber and emitter is investigated in this work, showing its conversion efficiency between 8% and 10% with concentration factor varying between 20 and 200. This conversion efficiency is remarkably enhanced compared with the conversion efficiency for STPV system employing black surfaces (<2.5%).
Moreover, plasmonic light trapping in ultra-thin solar cells employing concave grating nanostructures is discussed in this thesis. The plasmonic light trapping inside an ultrathin GaAs layer in the film-coupled metamaterial structure is numerically demonstrated. By exciting plasmonic resonances inside this structure, the short-circuit current density for the film-coupled metamaterial solar cell is three times the short-circuit current for a free-standing GaAs layer.
The dissertation is concluded by discussing about the future work on selective solar thermal absorbers, STPV/TPV systems and light trapping structures. Possibilities to design and fabricate solar thermal absorber with better thermal stability will be discussed, the experimental work of TPV system will be conducted, and the light trapping in organic and perovskite solar cells will be looked into.
ContributorsWang, Hao (Author) / Wang, Liping (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Dai, Lenore (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2016
Description
Origami and Kirigami are two traditional art forms in the world. Origami, from
‘ori’ meaning folding, and ‘kami’ meaning paper is the art of paper folding. Kirigami, from ‘kiri’ meaning cutting, is the art of the combination of paper cutting and paper folding. In this dissertation, Origami and kirigami concepts were successively utilized in making stretchable lithium ion batteries and three-dimensional (3D) silicon structure which both provide excellent mechanical characteristics.
‘ori’ meaning folding, and ‘kami’ meaning paper is the art of paper folding. Kirigami, from ‘kiri’ meaning cutting, is the art of the combination of paper cutting and paper folding. In this dissertation, Origami and kirigami concepts were successively utilized in making stretchable lithium ion batteries and three-dimensional (3D) silicon structure which both provide excellent mechanical characteristics.
ContributorsSong, Zeming (Author) / Jiang, Hanqing (Thesis advisor) / Dai, Lenore (Committee member) / Yu, Hongbin (Committee member) / He, Ximin (Committee member) / Arizona State University (Publisher)
Created2016