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- All Subjects: Mechanical Engineering
Description
In this thesis, the problem of designing model discrimination algorithms for unknown nonlinear systems is considered, where only raw experimental data of the system is available. This kind of model discrimination techniques finds one of its application in the estimation of the system or intent models under consideration, where all incompatible models are invalidated using new data that is available at run time. The proposed steps to reach the end goal of the algorithm for intention estimation involves two steps: First, using available experimental data of system trajectories, optimization-based techniques are used to over-approximate/abstract the dynamics of the system by constructing an upper and lower function which encapsulates/frames the true unknown system dynamics. This over-approximation is a conservative preservation of the dynamics of the system, in a way that ensures that any model which is invalidated against this approximation is guaranteed to be invalidated with the actual model of the system. The next step involves the use of optimization-based techniques to investigate the distinguishability of pairs of abstraction/approximated models using an algorithm for 'T-Distinguishability', which gives a finite horizon time 'T', within which the pair of models are guaranteed to be distinguished, and to eliminate incompatible models at run time using a 'Model Invalidation' algorithm. Furthermore, due the large amount of data under consideration, some computation-aware improvements were proposed for the processing of the raw data and the abstraction and distinguishability algorithms.The effectiveness of the above-mentioned algorithms is demonstrated using two examples. The first uses the data collected from the artificial simulation of a swarm of agents, also known as 'Boids', that move in certain patterns/formations, while the second example uses the 'HighD' dataset of naturalistic trajectories recorded on German Highways for vehicle intention estimation.
ContributorsBhagwat, Mohit Mukul (Author) / Yong, Sze Zheng (Thesis advisor) / Berman, Spring (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2021
Description
This dissertation studies the methods to enhance the performance of foldable robots manufactured by laminated techniques. This class of robots are unique in their manufacturing process, which involves cutting and staking up thin layers of different materials with various stiffness. While inheriting the advantages of soft robots -- low weight, affordable manufacturing cost and a fast prototyping process -- a wider range of actuators is available to these mechanisms, while modeling their behavior requires less computational cost.The fundamental question this dissertation strives to answer is how to decode and leverage the effect of material stiffness in these robots. These robots' stiffness is relatively limited due to their slender design, specifically at larger scales. While compliant robots may have inherent advantages such as being safer to work around, this low rigidity makes modeling more complex. This complexity is mostly contained in material deformation since the conventional actuators such as servo motors can be easily leveraged in these robots. As a result, when introduced to real-world environments, efficient modeling and control of these robots are more achievable than conventional soft robots.
Various approaches have been taken to design, model, and control a variety of laminate robot platforms by investigating the effect of material deformation in prototypes while they interact with their working environments. The results obtained show that data-driven approaches such as experimental identification and machine learning techniques are more reliable in modeling and control of these mechanisms. Also, machine learning techniques for training robots in non-ideal experimental setups that encounter the uncertainties of real-world environments can be leveraged to find effective gaits with high performance. Our studies on the effect of stiffness of thin, curved sheets of materials has evolved into introducing a new class of soft elements which we call Soft, Curved, Reconfigurable, Anisotropic Mechanisms (SCRAMs). Like bio-mechanical systems, SCRAMs are capable of re-configuring the stiffness of curved surfaces to enhance their performance and adaptability. Finally, the findings of this thesis show promising opportunities for foldable robots to become an alternative for conventional soft robots since they still offer similar advantages in a fraction of computational expense.
ContributorsSharifzadeh, Mohammad (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Accurate knowledge and understanding of thermal conductivity is very important in awide variety of applications both at microscopic and macroscopic scales. Estimation,however varies widely with respect to scale and application. At a lattice level, calcu-lation of thermal conductivity of any particular alloy require very heavy computationeven for a relatively small number of atoms. This thesis aims to run conventionalmolecular dynamic simulations for a particular supercell and then employ a machinelearning based approach and compare the two in hopes of developing a method togreatly reduce computational costs as well as increase the scale and time frame ofthese systems. Conventional simulations were run using interatomic potentials basedon density function theory-basedab initiocalculations. Then deep learning neuralnetwork based interatomic potentials were used run similar simulations to comparethe two approaches.
ContributorsDabir, Anirudh (Author) / Zhuang, Houlong (Thesis advisor) / Nian, Qiong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
The tire blowout is potentially one of the most critical accidents that may occur on the road. Following a tire blowout, the mechanical behavior of the tire is extremely affected and the forces generating from the interaction of the tire and the ground are redistributed. This severe change in the mechanism of tire force generation influences the dynamic characteristics of the vehicle significantly. Thus, the vehicle loses its directional stability and has a risk of departing its lane and colliding with other vehicles or the guardrail. This work aims to further broaden our current knowledge of the vehicle dynamic response to a blowout scenario during both rectilinear and curvilinear motions. To that end, a fourteen degrees of freedom full vehicle model combined with the well-grounded Dugoff’s tire models is developed and validated using the high fidelity MSC Adams package. To examine the effect of the tire blowout on the dynamic behavior of the vehicle, a series of tests incorporating a tire blowout is conducted in both rectilinear and curvilinear maneuvers with different tire burst locations. It is observed that the reconstruction of the tire forces resulting from blowout leads to a substantial change in the dynamics of the vehicle as well as a severe directional instability and possibly a rollover accident. Consequently, a corrective safety control system utilizing a braking/traction torque actuation mechanism is designed. The basic idea of the stability controller is to produce a regulated amount of input torque on one or more wheels apart from the blown tire. The proposed novel control-oriented model eliminates the simplifying assumptions used in the design of such controllers. Furthermore, a double integrator was augmented to enhance the steady-state performance of the sliding mode closed-loop system. The chattering problem stemmed by the switching nature of the controller is diminished through tuning the slope of saturation function. Different apparatuses are used in terms of actuation, using an individual front actuator, utilizing multi-actuator, and using two-wheel braking torques successively. It is found that the proposed controllers are perfectly capable of stabilizing the vehicle and robustly track the desired trajectory in straight-line and cornering maneuvers.
ContributorsAl-Quran, Mahdi (Author) / Mayyas, Abdel Ra'Ouf (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Chen, Yan (Committee member) / Ren, Yi (Committee member) / Yong, Sze (Committee member) / Arizona State University (Publisher)
Created2021
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
Mechanical fatigue has been a research topic since quite a long time. It is a complex phenomenon at molecular level. The fact that fatigue failure occurs much below material’s yield point, made it much interesting area for research. So, to understand the physics behind fatigue failure became an important research topic. Fatigue failure is characterized by crack initiation and then crack propagation to finally fracture the material. If this could be modelled mathematically, then it would save lot of resources and would assure the structural integrity of given component. Many such mathematical models were published to calculate fatigue crack growth for Constant Amplitude Loading, but most of the time the applied loads are variable in nature. So, to address this problem a mathematical model which will predict fatigue life in terms of time history is needed. This research study focuses on improving previously developed subcycle fatigue crack growth model also known as small time scale model which works well in Paris regime. In the first part, focus has been given on estimating threshold point using subcycle model by applying load shedding techniques. Later subcycle model has been modified to include fatigue crack growth in threshold region. In the second part of this research study, the concept of Equivalent Initial Flaw Size (EIFS) and fracture mechanics approach has been used to compute fatigue life for Constant as well as Random Amplitude Loading. Further the model has been extended to compute the fatigue life under Mixed Mode Loading (Mode I & Mode II). Standard material properties are used to calibrate the model parameters. The fatigue life results were validated using available open literature data as well as experimental testing data. The subcycle model can be used to calculate fatigue life in case of HCF and LCF, which is suggested as a future work for this research study.
ContributorsShivankar, Sushant (Author) / Liu, Yongming YL (Thesis advisor) / Nian, Qiong QN (Committee member) / Jiao, Yang YJ (Committee member) / Arizona State University (Publisher)
Created2021
Description
How to effectively and accurately describe, character and quantify the microstructure of the heterogeneous material and its 4D evolution process with time suffered from external stimuli or provocations is very difficult and challenging, but it’s significant and crucial for its performance prediction, processing, optimization and design. The goal of this research is to overcome these challenges by developing a series of novel hierarchical statistical microstructure descriptors called “n-point polytope functions” which is as known as Pn functions to quantify heterogeneous material’s microstructure and creating Pn functions related quantification methods which are Omega Metric and Differential Omega Metric to analyze its 4D processing.In this dissertation, a series of powerful programming tools are used to demonstrate that Pn functions can be used up to n=8 for chaotically scattered images which can hardly be distinguished by our naked eyes in chapter 3 to find or compare the potential configuration feature of structure such as symmetry or polygon geometry relation between the different targets when target’s multi-modal imaging is provided. These n-point statistic results calculated from Pn functions for features of interest in the microstructure can efficiently decompose the structural hidden features into a set of “polytope basis” to provide a concise, explainable, expressive, universal and efficient quantifying manner.
In Chapter 4, the Pn functions can also be incorporated into material reconstruction algorithms readily for fast virtualizing 3D microstructure regeneration and also allowing instant material property prediction via analytical structure-property mappings for material design.
In Chapter 5, Omega Metric and Differential Omega Metric are further created and used to provide a time-dependent reduced-dimension metric to analyze the 4D evaluation processing instead of using Pn functions directly because these 2 simplified methods can provide undistorted results to be easily compared. The real case of vapor-deposition alloy films analysis are implemented in this dissertation to demonstrate that One can use these methods to predict or optimize the design for 4D evolution of heterogeneous material.
The advantages of the all quantification methods in this dissertation can let us economically and efficiently quantify, design, predict the microstructure and 4D evolution of the heterogeneous material in various fields.
ContributorsCHEN, PEI-EN (Author) / Jiao, Yang (Thesis advisor) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Zhuang, Houlong (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Engineering materials and structures undergo a wide variety of multiaxial fatigue loading conditions during their service life. Some of the most complex multiaxial loading scenarios include proportional/non-proportional loading, mix-mode loading, overload/underload, etc. Such loadings are often experienced in many critical applications including aircraft, rotorcraft, and wind turbines. Any accidental failure of these structures during their service life can lead to catastrophic damage to life, property, and environment. All fatigue failure begins with the nucleation of a small crack, followed by crack growth, and ultimately the occurrence of final failure; however, the mechanisms governing the crack nucleation and the crack propagation behavior depend on the nature of fatigue loading and microstructure of the material. In general, ductile materials witness multiple nucleation sites leading to its failure; however, high strength material fails from the nucleation of a single dominant crack. Crack propagation, on the other hand, is governed by various competing mechanisms, which can act either ahead of the crack tip or in the wake region of the crack. Depending upon the magnitude of load, overload/underload, mode-mixity, and microstructure, dominant governing mechanisms may include: crack tip blunting; crack deflection, branching and secondary cracking; strain hardening; residual compressive stresses; plasticity-induced closure, etc. Therefore, it is essential to investigate the mechanisms governing fatigue failure of structural components under such complex multiaxial loading conditions in order to provide a reliable estimation of useful life. The research presented in this dissertation provides the foundation for a comprehensive understanding of fatigue damage in AA 7075 subjected to a range of loading conditions. A series of fatigue tests were conducted on specially designed specimens under different forms of multiaxial loading, which was followed by fracture-surface analysis in order to identify the governing micromechanisms and correlate them with macroscopic fatigue damage behavior. An empirical model was also developed to predict the crack growth rate trend under mode II overloads in an otherwise constant amplitude biaxial loading. The model parameters were calculated using the shape and the size of the plastic zone ahead of the crack tip, and the degree of material hardening within the overload plastic zone. The data obtained from the model showed a good correlation with the experimental values for crack growth rate in the transient region.
ContributorsSingh, Abhay Kumar (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Fard, Masoud Y (Committee member) / Arizona State University (Publisher)
Created2021
Description
This research seeks to present the design and testing of exoskeletons capable of assisting with walking gait, squatting, and fall prevention activities. The dissertation introduces wearable
robotics and exoskeletons and then progresses into specific applications and developments in the
targeted field. Following the introduction, chapters present and discuss different wearable
exoskeletons built to address known issues with workers and individuals with increased risk of fall.
The presentation is concluded by an overall analysis of the resulting developments and identifying
future work in the field.
ContributorsOlson, Jason Stewart (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2021
Description
This paper introduces a variable impedance controller which dynamically modulates both its damping and stiffness to improve the trade-off between stability and agility in coupled human-robot systems and reduce the human user’s effort. The controller applies a range of robotic damping from negative to positive values to either inject or dissipate energy based on the user’s intent of motion. The controller also estimates the user’s intent of direction and applies a variable stiffness torque to stabilize the user towards an estimated ideal trajectory. To evaluate the controller’s ability to improve the stability/agility trade-off and reduce human effort, a study was designed for human subjects to perform a 2D target reaching task while coupled with a wearable ankle robot. A constant impedance condition was selected as a control with which to compare the variable impedance condition. The position, speed, and muscle activation responses were used to quantify the user’s stability, agility, and effort, respectively. Stability was quantified spatially and temporally, with both overshoot and stabilization time showing no statistically significant difference between the two experimental conditions. Agility was quantified using mean and maximum speed, with both increasing from the constant impedance to variable impedance condition by 29.8% and 59.9%, respectively. Effort was quantified by the overall and maximum muscle activation data, both of which showed a ~10% reduction in effort. Overall, the study demonstrated the effectiveness of the variable impedance controller.
ContributorsArnold, James (Author) / Lee, Hyunglae (Thesis advisor) / Berman, Spring (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2021