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Description
Desorption processes are an important part of all processes which involve utilization of solid adsorbents such as adsorption cooling, sorption thermal energy storage, and drying and dehumidification processes and are inherently energy-intensive. Here, how those energy requirements can be reduced through the application of ultrasound for three widely used adsorbents namely zeolite 13X, activated alumina and silica gel is investigated. To determine and justify the effectiveness of incorporating ultrasound from an energy-savings point of view, an approach of constant overall input power of 20 and 25 W was adopted. To measure the extent of the effectiveness of using ultrasound, the ultrasonic-power-to-total power ratios of 0.2, 0.25, 0.4 and 0.5 were investigated and the results compared with those of no-ultrasound (heat only) at the same total power. Duplicate experiments were performed at three nominal frequencies of 28, 40 and 80 kHz to observe the influence of frequency on regeneration dynamics. Regarding moisture removal, application of ultrasound results in higher desorption rate compared to a non-ultrasound process. A nonlinear inverse proportionality was observed between the effectiveness of ultrasound and the frequency at which it is applied. Based on the variation of desorption dynamics with ultrasonic power and frequency, three mechanisms of reduced adsorbate adsorption potential, increased adsorbate surface energy and enhanced mass diffusion are proposed. Two analytical models that describe the desorption process were developed based on the experimental data from which novel efficiency metrics were proposed, which can be employed to justify incorporating ultrasound in regeneration and drying processes.
ContributorsDaghooghi Mobarakeh, Hooman (Author) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Wang, Robert (Committee member) / Calhoun, Ronald (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2021
Description
Regolith excavation systems are the enabling technology that must be developed in order to implement many of the plans for in-situ resource utilization (ISRU) that have been developed in recent years to aid in creating a lasting human presence on the surface of the Moon, Mars, and other celestial bodies. The majority of proposed ISRU excavation systems are integrated onto a wheeled mobility system, however none yet have proposed the use of a screw-propelled vehicle, which has the potential to augment and enhance the capabilities of the excavation system. As a result, CASPER, a novel screw-propelled excavation rover is developed and analyzed to determine its effectiveness as a ISRU excavation system. The excavation rate, power, velocity, cost of transport, and a new parameter, excavation transport rate, are analyzed for various configurations of the vehicle through mobility and excavation tests performed in silica sand. The optimal configuration yielded a 28.4 kg/hr excavation rate and11.2 m/min traverse rate with an overall system mass of 3.4 kg and power draw of26.3 W. CASPER’s mobility and excavation performance results are compared to four notable proposed ISRU excavation systems of various types. The results indicate that this architecture shows promise as an ISRU excavator because it provides significant excavation capability with low mass and power requirements.
ContributorsGreen, Marko (Author) / Marvi, Hamid (Thesis advisor) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2021
Description
The inherent behavior of many real world applications tends to exhibit complex or chaotic patterns. A novel technique to reduce and analyze such complex systems is introduced in this work, and its applications to multiple perturbed systems are discussed comprehensively. In this work, a unified approach between the Floquet theory for time periodic systems and the Poincare theory of Normal Forms is proposed to analyze time varying systems. The proposed unified approach is initially verified for linear time periodic systems with the aid of an intuitive state augmentation and the method of Time Independent Normal Forms (TINF). This approach also resulted in the closed form expressions for the State Transition Matrix (STM) and Lyapunov-Floquet (L-F) transformation for linear time periodic systems. The application of theory towards stability analysis is further demonstrated with the system of Suction Stabilized Floating (SSF) platform. Additionally, multiple control strategies are discussed and implemented to drive an unstable time periodic system to a desired stable point or orbit efficiently and optimally. The computed L-F transformation is further utilized to analyze nonlinear and externally excited systems with deterministic and stochastic time periodic coefficients. The central theme of this work is to verify the extension of Floquet theory towards time varying systems with periodic coefficients comprising of incommensurate frequencies or quasi-periodic systems. As per Floquet theory, a Lyapunov-Perron (L-P) transformation converts a time-varying quasi-periodic system to a time-invariant form. A class of commutative quasi-periodic systems is introduced to demonstrate the proposed theory and its applications analytically. An extension of the proposed unified approach towards analyzing the linear quasi-periodic system is observed to provide good results, computationally less complex and widely applicable for strongly excited systems. The computed L-P transformation using the unified theory is applied to analyze both commutative and non-commutative linear quasi-periodic systems with nonlinear terms and external excitation terms. For highly nonlinear quasi-periodic systems, the implementation of multiple order reduction techniques and their performance comparisons are illustrated in this work. Finally, the robustness and stability analysis of nonlinearly perturbed and stochastically excited quasi-periodic systems are performed using Lyapunov's direct method and Infante's approach.
ContributorsCherangara Subramanian, Susheelkumar (Author) / Redkar, Sangram (Thesis advisor) / Rogers, Bradley (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2021
Description
The hexagonal honeycomb is a bio-inspired cellular structure with a high stiffness-to-weight ratio. It has contributed to its use in several engineering applications compared to solid bodies with identical volume and material properties. This characteristic behavior is mainly attributed to the effective nature of stress distribution through the honeycomb beams that manifests as bending, axial, and shear deformation mechanisms. Inspired by the presence of this feature in natural honeycomb, this work focuses on the influence of the corner radius on the mechanical properties of a honeycomb structure subjected to in-plane compression loading. First, the local response at the corner node interface is investigated with the help of finite element simulation of a periodic unit cell within the linear elastic domain and validated against the best available analytical models. Next, a parametric design of experiments (DOE) study with the unit cell is defined with design points of varying circularity and cell length ratios towards identifying the optimal combination of all geometric parameters that maximize stiffness per unit mass while minimizing the stresses induced at the corner nodes. The observed trends are then compared with compression tests of 3D printed Nylon 12 honeycomb specimens of varying corner radii and wall thicknesses. The study concluded that the presence of a corner radius has a mitigating effect on peak stresses but that these effects are dependent on thickness while also increasing specific stiffness in all cases. It also points towards an optimum combination of parameters that achieve both objectives simultaneously while shedding some light on the functional benefit of this radius in wasp and bee nests that employ a hexagonal cell.
ContributorsRajeev, Athul (Author) / Bhate, Dhruv (Thesis advisor) / Oswald, Jay (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
Description
Automation has become a staple in high volume manufacturing, where the consistency and quality of a product carries as much importance as the quantity produced. The Aerospace Industry has a vested interest in expanding the application of automation beyond simply manufacturing. In this project, the process of systems engineering has been applied to the Conceptual Design Phase of product development; specifically, the Preliminary Structural Design of a Composite wing for an Unmanned Air Vehicle (UAV). Automated structural analysis can be used to develop a composite wing structure that can be directly rendered in Computer Aided Drafting (CAD) and validated using Finite Element Analysis (FEA). This concept provides the user with the ability to quickly iterate designs and demonstrates how different the “optimal light weight” composite structure must look for UAV systems of varied weight, range, and flight maneuverability.
ContributorsBlair, Martin Caceres (Author) / Takahashi, Timothy (Thesis advisor) / Murthy, Raghavendra (Committee member) / Perez, Ruben (Committee member) / Arizona State University (Publisher)
Created2021
Description
Recent years, there has been many attempts with different approaches to the human-robot interaction (HRI) problems. In this paper, the multi-agent interaction is formulated as a differential game with incomplete information. To tackle this problem, the parameter estimation method is utilized to obtain the approximated solution in a real time basis. Previous studies in the parameter estimation made the assumption that the human parameters are known by the robot; but such may not be the case and there exists uncertainty in the modeling of the human rewards as well as human's modeling of the robot's rewards. The proposed method, empathetic estimation, is tested and compared with the ``non-empathetic'' estimation from the existing works. The case studies are conducted in an uncontrolled intersection with two agents attempting to pass efficiently. Results have shown that in the case of both agents having inconsistent belief of the other agent's parameters, the empathetic agent performs better at estimating the parameters and has higher reward values, which indicates the scenarios when empathy is essential: when agent's initial belief is mismatched from the true parameters/intent of the agents.
ContributorsChen, Yi (Author) / Ren, Yi (Thesis advisor) / Zhang, Wenlong (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2021
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
Additively Manufactured Thin-wall Inconel 718 specimens commonly find application in heat exchangers and Thermal Protection Systems (TPS) for space vehicles. The wall thicknesses in applications for these components typically range between 0.03-2.5mm. Laser Powder Bed Fusion (PBF) Fatigue standards assume thickness over 5mm and consider Hot Isostatic Pressing (HIP) as conventional heat treatment. This study aims at investigating the dependence of High Cycle Fatigue (HCF) behavior on wall thickness and Hot Isostatic Pressing (HIP) for as-built Additively Manufactured Thin Wall Inconel 718 alloys. To address this aim, high cycle fatigue tests were performed on specimens of seven different thicknesses (0.3mm,0.35mm, 0.5mm, 0.75mm, 1mm, 1.5mm, and 2mm) using a Servohydraulic FatigueTesting Machine. Only half of the specimen underwent HIP, creating data for bothHIP and No-HIP specimens. Upon analyzing the collected data, it was noticed that the specimens that underwent HIP had similar fatigue behavior to that of sheet metal specimens. In addition, it was also noticed that the presence of Porosity in No-HIP specimens makes them more sensitive to changes in stress. A clear decrease in fatigue strength with the decrease in thickness was observed for all specimens.
ContributorsSaxena, Anushree (Author) / Bhate, Dhruv (Thesis advisor) / Liu, Yongming (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2021