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Description
Information exists in various forms and a better utilization of the available information can benefit the system awareness and response predictions. The focus of this dissertation is on the fusion of different types of information using Bayesian-Entropy method. The Maximum Entropy method in information theory introduces a unique way of handling information in the form of constraints. The Bayesian-Entropy (BE) principle is proposed to integrate the Bayes’ theorem and Maximum Entropy method to encode extra information. The posterior distribution in Bayesian-Entropy method has a Bayesian part to handle point observation data, and an Entropy part that encodes constraints, such as statistical moment information, range information and general function between variables. The proposed method is then extended to its network format as Bayesian Entropy Network (BEN), which serves as a generalized information fusion tool for diagnostics, prognostics, and surrogate modeling.
The proposed BEN is demonstrated and validated with extensive engineering applications. The BEN method is first demonstrated for diagnostics of gas pipelines and metal/composite plates for damage diagnostics. Both empirical knowledge and physics model are integrated with direct observations to improve the accuracy for diagnostics and to reduce the training samples. Next, the BEN is demonstrated in prognostics and safety assessment in air traffic management system. Various information types, such as human concepts, variable correlation functions, physical constraints, and tendency data, are fused in BEN to enhance the safety assessment and risk prediction in the National Airspace System (NAS). Following this, the BE principle is applied in surrogate modeling. Multiple algorithms are proposed based on different type of information encoding, such as Bayesian-Entropy Linear Regression (BELR), Bayesian-Entropy Semiparametric Gaussian Process (BESGP), and Bayesian-Entropy Gaussian Process (BEGP) are demonstrated with numerical toy problems and practical engineering analysis. The results show that the major benefits are the superior prediction/extrapolation performance and significant reduction of training samples by using additional physics/knowledge as constraints. The proposed BEN offers a systematic and rigorous way to incorporate various information sources. Several major conclusions are drawn based on the proposed study.
The proposed BEN is demonstrated and validated with extensive engineering applications. The BEN method is first demonstrated for diagnostics of gas pipelines and metal/composite plates for damage diagnostics. Both empirical knowledge and physics model are integrated with direct observations to improve the accuracy for diagnostics and to reduce the training samples. Next, the BEN is demonstrated in prognostics and safety assessment in air traffic management system. Various information types, such as human concepts, variable correlation functions, physical constraints, and tendency data, are fused in BEN to enhance the safety assessment and risk prediction in the National Airspace System (NAS). Following this, the BE principle is applied in surrogate modeling. Multiple algorithms are proposed based on different type of information encoding, such as Bayesian-Entropy Linear Regression (BELR), Bayesian-Entropy Semiparametric Gaussian Process (BESGP), and Bayesian-Entropy Gaussian Process (BEGP) are demonstrated with numerical toy problems and practical engineering analysis. The results show that the major benefits are the superior prediction/extrapolation performance and significant reduction of training samples by using additional physics/knowledge as constraints. The proposed BEN offers a systematic and rigorous way to incorporate various information sources. Several major conclusions are drawn based on the proposed study.
ContributorsWang, Yuhao (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Yan, Hao (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2020
Description
Almost all mechanical and electro-mechanical products are assemblies of multiple parts, either because of requirements for relative motion, or use of different materials, shape/size differences. Thus, assembly design is the very crux of engineering design. In addition to nominal design of an assembly, there is also tolerance design to determine allowable manufacturing variations to ensure proper functioning and assemblability. Most of the flexible assemblies are made by stamping sheet metal. Sheet metal stamping process involves plastically deforming sheet metals using dies. Sub-assemblies of two or more components are made with either spot-welding or riveting operations. Various sub-assemblies are finally joined, using spot-welds or rivets, to create the desired assembly. When two components are brought together for assembly, they do not align exactly; this causes gaps and irregularities in assemblies. As multiple parts are stacked, errors accumulate further. Stamping leads to variable deformations due to residual stresses and elastic recovery from plastic strain of metals; this is called as the ‘spring-back’ effect. When multiple components are stacked or assembled using spot welds, input parameters variations, such as sheet metal thickness, number and order of spot welds, cause variations in the exact shape of the final assembly in its free state. It is essential to understand the influence of these input parameters on the geometric variations of both the individual components and the assembly created using these components. Design of Experiment is used to generate principal effect study which evaluates the influence of input parameters on output parameters. The scope of this study is to quantify the geometric variations for a flexible assembly and evaluate their dependence on specific input variables. The 3 input variables considered are the thickness of the sheet material, the number of spot welds used and the spot-welding order to create the assembly. To quantify the geometric variations, sprung-back nodal points along lines, circular arcs, a combination of these, and a specific profile are reduced to metrologically simulated features.
ContributorsJoshi, Abhishek (Author) / Ren, Yi (Thesis advisor) / Davidson, Joseph (Committee member) / Shah, Jami (Committee member) / Arizona State University (Publisher)
Created2020
Description
Thermal Energy Storage (TES) is of great significance for many engineering applications as it allows surplus thermal energy to be stored and reused later, bridging the gap between requirement and energy use. Phase change materials (PCMs) are latent heat-based TES which have the ability to store and release heat through phase transition processes over a relatively narrow temperature range. PCMs have a wide range of operating temperatures and therefore can be used in various applications such as stand-alone heat storage in a renewable energy system, thermal storage in buildings, water heating systems, etc. In this dissertation, various PCMs are incorporated and investigated numerically and experimentally with different applications namely a thermochemical metal hydride (MH) storage system and thermal storage in buildings. In the second chapter, a new design consisting of an MH reactor encircled by a cylindrical sandwich bed packed with PCM is proposed. The role of the PCM is to store the heat released by the MH reactor during the hydrogenation process and reuse it later in the subsequent dehydrogenation process. In such a system, the exothermic and endothermic processes of the MH reactor can be utilized effectively by enhancing the thermal exchange between the MH reactor and the PCM bed. Similarly, in the third chapter, a novel design that integrates the MH reactor with cascaded PCM beds is proposed. In this design, two different types of PCMs with different melting temperatures and enthalpies are arranged in series to improve the heat transfer rate and consequently shorten the time duration of the hydrogenation and dehydrogenation processes. The performance of the new designs (in chapters 2 and 3) is investigated numerically and compared with the conventional designs in the literature. The results indicate that the new designs can significantly enhance the time duration of MH reaction (up to 87%). In the fourth chapter, organic coconut oil PCM (co-oil PCM) is explored experimentally and numerically for the first time as a thermal management tool in building applications. The results show that co-oil PCM can be a promising solution to improve the indoor thermal environment in semi-arid regions.
ContributorsAlqahtani, Talal (Author) / Phelan, Patrick E (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Mellouli, Sofiene (Committee member) / Wang, Robert (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2020
Description
Water desalination has become one of the viable solutions to provide drinking water in regions with limited natural resources. This is particularly true in small communities in arid regions, which suffer from low rainfall, declining surface water and increasing salinity of groundwater. Yet, current desalination methods are difficult to be implemented in these areas due to their centralized large-scale design. In addition, these methods require intensive maintenance, and sometimes do not operate in high salinity feedwater. Membrane distillation (MD) is one technology that can potentially overcome these challenges and has received increasing attention in the last 15 years. The driving force of MD is the difference in vapor pressure across a microporous hydrophobic membrane. Compared to conventional membrane-based technologies, MD can treat high concentration feedwater, does not need intensive pretreatment, and has better fouling resistance. More importantly, MD operates at low feed temperatures and so it can utilize low–grade heat sources such as solar energy for its operation. While the integration of solar energy and MD was conventionally indirect (i.e. by having two separate systems: a solar collector and an MD module), recent efforts were focused on direct integration where the membrane itself is integrated within a solar collector aiming to have a more compact, standalone design suitable for small-scale applications. In this dissertation, a comprehensive review of these efforts is discussed in Chapter 2. Two novel direct solar-powered MD systems were proposed and investigated experimentally: firstly, a direct contact MD (DCMD) system was designed by placing capillary membranes within an evacuated tube solar collector (ETC) (Chapter 3), and secondly, a submerged vacuum MD (S-VMD) system that uses circulation and aeration as agitation techniques was investigated (Chapter 4). A maximum water production per absorbing area of 0.96 kg·m–2·h–1 and a thermal efficiency of 0.51 were achieved. A final study was conducted to investigate the effect of ultrasound in an S-VMD unit (Chapter 5), which significantly enhanced the permeate flux (up to 24%) and reduced the specific energy consumption (up to 14%). The results add substantially to the understanding of integrating ultrasound with different MD processes.
ContributorsBamasag, Ahmad (Author) / Phelan, Patrick E (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Wang, Liping (Committee member) / Bocanegra, Luis (Committee member) / Roedel, Ronald (Committee member) / Arizona State University (Publisher)
Created2020
Description
Deformable heat exchangers could provide a multitude of previously untapped advantages ranging from adaptable performance via macroscale, dynamic shape change (akin to dilation/constriction seen in blood vessels) to enhanced heat transfer at thermal interfaces through microscale, surface deformations. So far, making deformable, ‘soft heat exchangers’ (SHXs) has been limited by the low thermal conductivity of materials with suitable mechanical properties. The recent introduction of liquid-metal embedded elastomers by Bartlett et al1 has addressed this need. Specifically, by remaining soft and stretchable despite the addition of filler, these thermally conductive composites provide an ideal material for the new class of “soft thermal systems”, which is introduced in this work. Understanding such thermal systems will be a key element in enabling technology that require high levels of stretchability, such as thermoregulatory garments, soft electronics, wearable electronics, and high-powered robotics. Shape change inherent to SHX operation has the potential to violate many conventional assumptions used in HX design and thus requires the development of new theoretical approaches to predict performance. To create a basis for understanding these devices, this work highlights two sequential studies. First, the effects of transitioning to a surface deformable, SHX under steady state static conditions in the setting of a liquid cooling device for thermoregulation, electronics and robotics applications was explored. In this study, a thermomechanical model was built and validated to predict the thermal performance and a system wide analysis to optimize such devices was carried out. Second, from a more fundamental perspective, the effects of SHXs undergoing transient shape deformation during operation was explored. A phase shift phenomenon in cooling performance dependent on stretch rate, stretch extent and thermal diffusivity was discovered and explained. With the use of a time scale analysis, the extent of quasi-static assumption viability in modeling such systems was quantified and multiple shape modulation regime limits were defined. Finally, nuance considerations and future work of using liquid metal-silicone composites in SHXs were discussed.
ContributorsKotagama, Praveen (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Green, Matthew (Committee member) / Arizona State University (Publisher)
Created2020
Description
Gas Dynamic Virtual Nozzles (GDVN) produce microscopic flow-focused liquid jets and are widely used for sample delivery in serial femtosecond crystallography (SFX) and time-resolved solution scattering. Recently, 2-photon polymerization (2PP) made it possible to produce 3D-printed GDVNs with submicron printing resolution. Comparing with hand- fabricated nozzles, reproducibility, and less developing effort, and similarity of the performance of different 3D printed nozzles are among the advantages of using 3D printing techniques to develop GDVN’s. Submicron printing resolution also makes it possible to easily improve GDVN performance by optimizing the design of nozzles. In this study, 3D printed nozzles were developed to achieve low liquid and gas flow rates and high liquid jet velocities. A double-pulsed nanosecond laser imaging system was used to perform Particle Tracking Velocimetry (PTV) in order to determine jet velocities and assess jet stability/reproducibility. The testing results of pure water jets focused with He sheath gas showed that some designs can easily achieve stable liquid jets with velocities of more than 80 m/s, with pure water flowing at 3 microliters/min, and helium sheath gas flowing at less than 5 mg/min respectively. A numerical simulation pipeline was also used to characterize the performance of different 3D printed GDVNs. The results highlight the potential of making reproducible GDVNs with minimum fabrication effort, that can meet the requirements of present and future SFX and time-resolved solution scattering research.
ContributorsNazari, Reza (Author) / Adrian, Ronald (Thesis advisor) / Kirian, Richard (Thesis advisor) / Herrmann, Marcus (Committee member) / Phelan, Patrick (Committee member) / Weierstall, Uwe (Committee member) / Arizona State University (Publisher)
Created2020
Description
Traditionally, for applications that require heat transfer (e.g. heat exchangers),metals have been the go-to material for manufacturers because of their high thermal as
well as structural properties. However, metals have some notable drawbacks. They are
not corrosion-resistant, offer no freedom of design, have a high cost of production, and
sourcing the material itself. Even though polymers on their own don’t show great
prospects in the field of thermal applications, their composites perform better than their
counterparts. Nanofillers, when added to a polymer matrix not only increase their
structural strength but also their thermal performance. This work aims to tackle two of
those problems by using the additive manufacturing method, stereolithography to solve
the problem of design freedom, and the use of polymer nanocomposite material for
corrosion-resistance and increase their overall thermal performance. In this work, three
different concentrations of polymer composite materials were studied: 0.25 wt%, 0.5
wt%, and 1wt% for their thermal conductivity. The samples were prepared by
magnetically stirring them for a period of 10 to 24 hours depending on their
concentrations and then sonicating in an ice bath further for a period of 2 to 3 hours.
These samples were then tested for their thermal conductivities using a Hot Disk TPS
2500S. Scanning Electron Microscope (SEM) to study the dispersion of the nanoparticles
in the matrix. Different theoretical models were studied and used to compare
experimental data to the predicted values of effective thermal conductivity. An increase
of 7.9 % in thermal conductivity of the composite material was recorded for just 1 wt%
addition of multiwalled carbon nanotubes (MWCNTs).
well as structural properties. However, metals have some notable drawbacks. They are
not corrosion-resistant, offer no freedom of design, have a high cost of production, and
sourcing the material itself. Even though polymers on their own don’t show great
prospects in the field of thermal applications, their composites perform better than their
counterparts. Nanofillers, when added to a polymer matrix not only increase their
structural strength but also their thermal performance. This work aims to tackle two of
those problems by using the additive manufacturing method, stereolithography to solve
the problem of design freedom, and the use of polymer nanocomposite material for
corrosion-resistance and increase their overall thermal performance. In this work, three
different concentrations of polymer composite materials were studied: 0.25 wt%, 0.5
wt%, and 1wt% for their thermal conductivity. The samples were prepared by
magnetically stirring them for a period of 10 to 24 hours depending on their
concentrations and then sonicating in an ice bath further for a period of 2 to 3 hours.
These samples were then tested for their thermal conductivities using a Hot Disk TPS
2500S. Scanning Electron Microscope (SEM) to study the dispersion of the nanoparticles
in the matrix. Different theoretical models were studied and used to compare
experimental data to the predicted values of effective thermal conductivity. An increase
of 7.9 % in thermal conductivity of the composite material was recorded for just 1 wt%
addition of multiwalled carbon nanotubes (MWCNTs).
ContributorsGide, Kunal Manoj (Author) / Nian, Qiong (Thesis advisor) / Kwon, Beomjin (Committee member) / Li, Xiangjia (Committee member) / Arizona State University (Publisher)
Created2020
Description
One potential application of multi-robot systems is collective transport, a task in which multiple mobile robots collaboratively transport a payload that is too large or heavy to be carried by a single robot. Numerous control schemes have been proposed for collective transport in environments where robots can localize themselves (e.g., using GPS) and communicate with one another, have information about the payload's geometric and dynamical properties, and follow predefined robot and/or payload trajectories. However, these approaches cannot be applied in uncertain environments where robots do not have reliable communication and GPS and lack information about the payload. These conditions characterize a variety of applications, including construction, mining, assembly in space and underwater, search-and-rescue, and disaster response.
Toward this end, this thesis presents decentralized control strategies for collective transport by robots that regulate their actions using only their local sensor measurements and minimal prior information. These strategies can be implemented on robots that have limited or absent localization capabilities, do not explicitly exchange information, and are not assigned predefined trajectories. The controllers are developed for collective transport over planar surfaces, but can be extended to three-dimensional environments.
This thesis addresses the above problem for two control objectives. First, decentralized controllers are proposed for velocity control of collective transport, in which the robots must transport a payload at a constant velocity through an unbounded domain that may contain strictly convex obstacles. The robots are provided only with the target transport velocity, and they do not have global localization or prior information about any obstacles in the environment. Second, decentralized controllers are proposed for position control of collective transport, in which the robots must transport a payload to a target position through a bounded or unbounded domain that may contain convex obstacles. The robots are subject to the same constraints as in the velocity control scenario, except that they are assumed to have global localization. Theoretical guarantees for successful execution of the task are derived using techniques from nonlinear control theory, and it is shown through simulations and physical robot experiments that the transport objectives are achieved with the proposed controllers.
Toward this end, this thesis presents decentralized control strategies for collective transport by robots that regulate their actions using only their local sensor measurements and minimal prior information. These strategies can be implemented on robots that have limited or absent localization capabilities, do not explicitly exchange information, and are not assigned predefined trajectories. The controllers are developed for collective transport over planar surfaces, but can be extended to three-dimensional environments.
This thesis addresses the above problem for two control objectives. First, decentralized controllers are proposed for velocity control of collective transport, in which the robots must transport a payload at a constant velocity through an unbounded domain that may contain strictly convex obstacles. The robots are provided only with the target transport velocity, and they do not have global localization or prior information about any obstacles in the environment. Second, decentralized controllers are proposed for position control of collective transport, in which the robots must transport a payload to a target position through a bounded or unbounded domain that may contain convex obstacles. The robots are subject to the same constraints as in the velocity control scenario, except that they are assumed to have global localization. Theoretical guarantees for successful execution of the task are derived using techniques from nonlinear control theory, and it is shown through simulations and physical robot experiments that the transport objectives are achieved with the proposed controllers.
ContributorsFarivarnejad, Hamed (Author) / Berman, Spring (Thesis advisor) / Mignolet, Marc (Committee member) / Tsakalis, Konstantinos (Committee member) / Artemiadis, Panagiotis (Committee member) / Gil, Stephanie (Committee member) / Arizona State University (Publisher)
Created2020
Description
Bicycles and motorcycles offer maneuverability, energy efficiency and acceleration that four wheeled vehicles cannot offer given similar budget for. Two wheeled vehicles have drastically different dynamics from four wheeled vehicles due to their instability and gyroscopic effect from their wheels.
This thesis focuses on self-stabilization of a motorcycle using an active control momentum gyroscope (CMG) and validation of this multi-degree-of-freedom system’s mathematical model. Physical platform was created to mimic the simulation as accurately as possible and all components used were justified. This process involves derivation of a 3 Degree-of-Freedom (DOF) system’s forward kinematics and its Jacobian matrix, simulation analysis of different controller algorithms, setting the system and subsystem specifications, and real system experimentation and data analysis.
A Jacobian matrix was used to calculate accurately decomposed resultant angular velocities which are used to create the dynamics model of the system torque using the Euler-Lagrange method. This produces a nonlinear second order differential equation that is modeled using MATLAB/Simulink. PID, and cascaded feedback loop are tested in this Simulink model. Cascaded feedback loop shows most promises in the simulation analysis. Therefore, system specifications are calculated according to the data produced by this controller method. The model validation is executed using the Vicon motion capture system which captured the roll angle of the motorcycle. This work contributes to creating a set of procedures for creating a validated dynamic model for a CMG stabilized motorcycle which can be used to create variants of other self-stabilizing motorcycle system.
This thesis focuses on self-stabilization of a motorcycle using an active control momentum gyroscope (CMG) and validation of this multi-degree-of-freedom system’s mathematical model. Physical platform was created to mimic the simulation as accurately as possible and all components used were justified. This process involves derivation of a 3 Degree-of-Freedom (DOF) system’s forward kinematics and its Jacobian matrix, simulation analysis of different controller algorithms, setting the system and subsystem specifications, and real system experimentation and data analysis.
A Jacobian matrix was used to calculate accurately decomposed resultant angular velocities which are used to create the dynamics model of the system torque using the Euler-Lagrange method. This produces a nonlinear second order differential equation that is modeled using MATLAB/Simulink. PID, and cascaded feedback loop are tested in this Simulink model. Cascaded feedback loop shows most promises in the simulation analysis. Therefore, system specifications are calculated according to the data produced by this controller method. The model validation is executed using the Vicon motion capture system which captured the roll angle of the motorcycle. This work contributes to creating a set of procedures for creating a validated dynamic model for a CMG stabilized motorcycle which can be used to create variants of other self-stabilizing motorcycle system.
ContributorsMoon, Hansol (Author) / Zhang, Wenlong (Thesis advisor) / Frank, Daniel (Committee member) / Delp, Deana (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2020
Description
Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. The proposed study focuses on the data-driven approach to predict the mechanical properties of additively manufactured metals, specifically Ti-6Al-4V. Extensive data for Ti-6Al-4V using three different Powder Bed Fusion (PBF) additive manufacturing processes: Selective Laser Melting (SLM), Electron Beam Melting (EBM), and Direct Metal Laser Sintering (DMLS) are collected from the open literature. The data is used to develop models to estimate the mechanical properties of Ti-6Al-4V. For this purpose, two models are developed which relate the fabrication process parameters to the static and fatigue properties of the AM Ti-6Al-4V. To identify the behavior of the relationship between the input and output parameters, each of the models is developed on both linear multi-regression analysis and non-linear Artificial Neural Network (ANN) based on Bayesian regularization. Uncertainties associated with the performance prediction and sensitivity with respect to processing parameters are investigated. Extensive sensitivity studies are performed to identify the important factors for future optimal design. Some conclusions and future work are drawn based on the proposed study with investigated material.
ContributorsSharma, Antriksh (Author) / Liu, Yongming (Thesis advisor) / Nian, Qiong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020