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Description
Over the past century, the world has become increasingly more complex. Modern systems (i.e blockchain, internet of things (IoT), and global supply chains) are inherently difficult to comprehend due to their high degree of connectivity. Understanding the nature of complex systems becomes an acutely more critical skill set for managing

Over the past century, the world has become increasingly more complex. Modern systems (i.e blockchain, internet of things (IoT), and global supply chains) are inherently difficult to comprehend due to their high degree of connectivity. Understanding the nature of complex systems becomes an acutely more critical skill set for managing socio-technical infrastructure systems. As existing education programs and technical analysis approaches fail to teach and describe modern complexities, resulting consequences have direct impacts on real-world systems. Complex systems are characterized by exhibiting nonlinearity, interdependencies, feedback loops, and stochasticity. Since these four traits are counterintuitive, those responsible for managing complex systems may struggle in identifying these underlying relationships and decision-makers may fail to account for their implications or consequences when deliberating systematic policies or interventions.

This dissertation details the findings of a three-part study on applying complex systems modeling techniques to exemplar socio-technical infrastructure systems. In the research articles discussed hereafter, various modeling techniques are contrasted in their capacity for simulating and analyzing complex, adaptive systems. This research demonstrates the empirical value of a complex system approach as twofold: (i) the technique explains systems interactions which are often neglected or ignored and (ii) its application has the capacity for teaching systems thinking principles. These outcomes serve decision-makers by providing them with further empirical analysis and granting them a more complete understanding on which to base their decisions.

The first article examines modeling techniques, and their unique aptitudes are compared against the characteristics of complex systems to establish which methods are most qualified for complex systems analysis. Outlined in the second article is a proof of concept piece on using an interactive simulation of the Los Angeles water distribution system to teach complex systems thinking skills for the improved management of socio-technical infrastructure systems. Lastly, the third article demonstrates the empirical value of this complex systems approach for analyzing infrastructure systems through the construction of a systems dynamics model of the Arizona educational-workforce system, across years 1990 to 2040. The model explores a series of dynamic hypotheses and allows stakeholders to compare policy interventions for improving educational and economic outcome measures.
ContributorsNaufel, Lauren Rae McBurnett (Author) / Bekki, Jennifer (Thesis advisor) / Kellam, Nadia (Thesis advisor) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
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Description
The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed

The applications utilizing nanoparticles have grown in both industrial and academic areas because of the very large surface area to volume ratios of these particles. One of the best ways to process and control these nanoparticles is fluidization. In this work, a new microjet and vibration assisted (MVA) fluidized bed system was developed in order to fluidize nanoparticles. The system was tested and the parameters optimized using two commercially available TiO2 nanoparticles: P25 and P90. The fluidization quality was assessed by determining the non-dimensional bed height as well as the non-dimensional pressure drop. The non-dimensional bed height for the nanosized TiO2 in the MVA system optimized at about 5 and 7 for P25 and P90 TiO2, respectively, at a resonance frequency of 50 Hz. The non-dimensional pressure drop was also determined and showed that the MVA system exhibited a lower minimum fluidization velocity for both of the TiO2 types as compared to fluidization that employed only vibration assistance. Additional experiments were performed with the MVA to characterize the synergistic effects of vibrational intensity and gas velocity on the TiO2 P25 and P90 fluidized bed heights. Mathematical relationships were developed to correlate vibrational intensity, gas velocity, and fluidized bed height in the MVA. The non-dimensional bed height in the MVA system is comparable to previously published P25 TiO2 fluidization work that employed an alcohol in order to minimize the electrostatic attractions within the bed. However, the MVA system achieved similar results without the addition of a chemical, thereby expanding the potential chemical reaction engineering and environmental remediation opportunities for fluidized nanoparticle systems.

In order to aid future scaling up of the MVA process, the agglomerate size distribution in the MVA system was predicted by utilizing a force balance model coupled with a two-fluid model (TFM) simulation. The particle agglomerate size that was predicted using the computer simulation was validated with experimental data and found to be in good agreement.

Lastly, in order to demonstrate the utility of the MVA system in an air revitalization application, the capture of CO2 was examined. CO2 breakthrough time and adsorption capacities were tested in the MVA system and compared to a vibrating fluidized bed (VFB) system. Experimental results showed that the improved fluidity in the MVA system enhanced CO2 adsorption capacity.
ContributorsAn, Keju (Author) / Andino, Jean (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Adrian, Ronald (Committee member) / Emady, Heather (Committee member) / Kasbaoui, Mohamed (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Optical metasurfaces, i.e. artificially engineered arrays of subwavelength building blocks supporting abrupt and substantial light confinement, was employed to demonstrate a novel generation of devices for circularly polarized detection, full-Stokes polarimetry and all-optical modulation with ultra-compact footprint and chip-integrability.

Optical chirality is essential for generation, manipulation and detection of circularly polarized

Optical metasurfaces, i.e. artificially engineered arrays of subwavelength building blocks supporting abrupt and substantial light confinement, was employed to demonstrate a novel generation of devices for circularly polarized detection, full-Stokes polarimetry and all-optical modulation with ultra-compact footprint and chip-integrability.

Optical chirality is essential for generation, manipulation and detection of circularly polarized light (CPL), thus finds many applications in quantum computing, communication, spectroscopy, biomedical diagnosis, imaging and sensing. Compared to natural chiral materials, chiral metamaterials and metasurfaces enable much stronger chirality on subwavelength scale; therefore, they are ideal for device miniaturization and system integration. However, they are usually associated with low performance due to limited fabrication tolerance and high dissipation mainly caused by plasmonic materials. Here, a bio-inspired submicron-thick chiral metamaterial structure was designed and demonstrated experimentally with high contrast (extinction ratio >35) detection of CPL with different handedness and high efficiency (>80%) of the overall device. Furthermore, integration of left- and right-handed CPL detection units with nanograting linear polarization filters enabled full-Stokes polarimetry of arbitrarily input polarization states with high accuracy and very low insertion loss, all on a submillimeter single chip. These unprecedented highly efficient and high extinction ratio devices pave the way for on-chip polarimetric measurements.

All-optical modulation is widely used for optical interconnects, communication, information processing, and ultrafast spectroscopy. Yet, there’s deficiency of ultrafast, compact and energy-efficient solutions all in one device. Here, all-optical modulation of light in the near- and mid-infrared regimes were experimentally demonstrated based on a graphene-integrated plasmonic nanoantenna array. The remarkable feature of the device design is its simultaneous near-field enhancement for pump and probe (signal) beams, owing to the localized surface plasmon resonance excitation, while preserving the ultrafast photocarrier relaxation in graphene. Hence, a distinct modulation at 1560nm with record-low pump fluence (<8μJ/cm^2) was reported with ~1ps response time. Besides, relying on broadband interaction of graphene with incident light, a first-time demonstration of graphene-based all-optical modulation in mid-infrared spectral region (6-7μm) was reported based on the above double-enhancement design concept. Relying on the tunability of metasurface design, the proposed device can be used for ultrafast optical modulation from near-infrared to terahertz regime.
ContributorsBasiri, Ali (Author) / Yao, Yu (Thesis advisor) / Ning, Cun-Zheng (Committee member) / Palais, Joseph (Committee member) / Zhang, Yong-Hang (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Traditionally nanoporous gold is created by selective dissolution of silver or copper from a binary silver-gold or copper-gold alloy. These alloys serve as prototypical model systems for a phenomenon referred to as stress-corrosion cracking. Stress-corrosion cracking is the brittle failure of a normally ductile material occurring in a

Traditionally nanoporous gold is created by selective dissolution of silver or copper from a binary silver-gold or copper-gold alloy. These alloys serve as prototypical model systems for a phenomenon referred to as stress-corrosion cracking. Stress-corrosion cracking is the brittle failure of a normally ductile material occurring in a corrosive environment under a tensile stress. Silver-gold can experience this type of brittle fracture for a range of compositions. The corrosion process in this alloy results in a bicontinuous nanoscale morphology composed of gold-rich ligaments and voids often referred to as nanoporous gold. Experiments have shown that monolithic nanoporous gold can sustain high speed cracks which can then be injected into parent-phase alloy. This work compares nanoporous gold created from ordered and disordered copper-gold using digital image analysis and electron backscatter diffraction. Nanoporous gold from both disordered copper-gold and silver-gold, and ordered copper-gold show that grain orientation and shape remain largely unchanged by the dealloying process. Comparing the morphology of the nanoporous gold from ordered and disordered copper-gold with digital image analysis, minimal differences are found between the two and it is concluded that they are not statistically significant. This reveals the robust nature of nanoporous gold morphology against small variations in surface diffusion and parent-phase crystal structure.
Then the corrosion penetration down the grain boundary is compared to the depth of crack injections in polycrystal silver-gold. Based on statistical comparison, the crack-injections penetrate into the parent-phase grain boundary beyond the corrosion-induced porosity. To compare crack injections to stress-corrosion cracking, single crystal silver-gold samples are employed. Due to the cleavage-like nature of the fracture surfaces, electron backscatter diffraction is possible and employed to compare the crystallography of stress-corrosion crack surfaces and crack-injection surfaces. From the crystallographic similarities of these fracture surfaces, it is concluded that stress-corrosion can occur via a series of crack-injection events. This relationship between crack injections and stress corrosion cracking is further examined using electrochemical data from polycrystal silver-gold samples during stress-corrosion cracking. The results support the idea that crack injection is a mechanism for stress-corrosion cracking.
ContributorsKarasz, Erin (Author) / Sieradzki, Karl (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Peralta, Pedro (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2020
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Description
The intrinsic material properties of diamond are attractive for use in high power limiter/receiver protector (RP) systems, especially the ones required at the input of radio transceivers. The RP device presents a low capacitance and high resistance to low input signals, thereby adding negligible insertion loss to these desired signals.

The intrinsic material properties of diamond are attractive for use in high power limiter/receiver protector (RP) systems, especially the ones required at the input of radio transceivers. The RP device presents a low capacitance and high resistance to low input signals, thereby adding negligible insertion loss to these desired signals. However, at high input radio frequency (RF) power levels, the RP turns on with a resistance much smaller than the 50 Ω characteristic impedance, reflecting most of the potentially damaging input power away from the receiver input. P-type-intrinsic-n-type (PIN) diodes made of Silicon and Gallium Arsenide used in today’s conventional RP systems have certain limitations at high-power. The wide bandgap of diamond combined with its higher thermal conductivity give it a superior RF power handling capability that can protect sensitive RF front-end components from high power incident signals.

Vertical diamond PIN diodes were proposed and fabricated with an n+-i-p++ structure consisting of: a very thin and heavily phosphorus-doped n-type diamond layer and an intrinsic diamond layer grown on a heavily boron-doped diamond substrate with a (111) crystallographic orientation. Direct current (DC) and RF small-signal characterization was carried out by attaching the diamond sample in a shunted coplanar waveguide (CPW) configuration.

The small-signal lumped element model of the diode impedance under forward-bias was validated with a fit to the measured data, and provides a roadmap for the optimization of parameters for the implementation of diamond Schottky PIN diodes to be successfully used in receiver protector/limiter applications at S-band. The experimental results with the device growth and fabrication show promise and can help in further elevating the device RF figure of merit, in turn enabling the path for commercialization of these diamond-based devices.
ContributorsAhmad, Mohammad Faizan (Author) / Thornton, Trevor J. (Thesis advisor) / Goodnick, Stephen M. (Committee member) / Nemanich, Robert J. (Committee member) / Arizona State University (Publisher)
Created2020
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Description
This dissertation explores the use of deterministic scheduling theory for the design and development of practical manufacturing scheduling strategies as alternatives to current scheduling methods, particularly those used to minimize completion times and increase system capacity utilization. The efficient scheduling of production systems can make the difference between a thriving

This dissertation explores the use of deterministic scheduling theory for the design and development of practical manufacturing scheduling strategies as alternatives to current scheduling methods, particularly those used to minimize completion times and increase system capacity utilization. The efficient scheduling of production systems can make the difference between a thriving and a failing enterprise, especially when expanding capacity is limited by the lead time or the high cost of acquiring additional manufacturing resources. A multi-objective optimization (MOO) resource constrained parallel machine scheduling model with setups, machine eligibility restrictions, release and due dates with user interaction is developed for the scheduling of complex manufacturing systems encountered in the semiconductor and plastic injection molding industries, among others. Two mathematical formulations using the time-indexed Integer Programming (IP) model and the Diversity Maximization Approach (DMA) were developed to solve resource constrained problems found in the semiconductor industry. A heuristic was developed to find fast feasible solutions to prime the IP models. The resulting models are applied in two different ways: constructing schedules for tactical decision making and constructing Pareto efficient schedules with user interaction for strategic decision making aiming to provide insight to decision makers on multiple competing objectives.
Optimal solutions were found by the time-indexed IP model for 45 out of 45 scenarios in less than one hour for all the problem instance combinations where setups were not considered. Optimal solutions were found for 18 out of 45 scenarios in less than one hour for several combinations of problem instances with 10 and 25 jobs for the hybrid (IP and heuristic) model considering setups. Regarding the DMA MOO scheduling model, the complete efficient frontier (9 points) was found for a small size problem instance in 8 minutes, and a partial efficient frontier (29 points) was found for a medium sized problem instance in 183 hrs.
ContributorsMunoz-Estrada, Luis Fernando (Author) / Villalobos, Jesus R (Thesis advisor) / Fowler, John (Thesis advisor) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Prior research has provided evidence to suggest that veterans exhibit unique assets that benefit them in engineering education and engineering industry. However, there is little evidence to determine whether their assets are due to military service or other demographic factors such as age, maturity, or gender. The aim of this

Prior research has provided evidence to suggest that veterans exhibit unique assets that benefit them in engineering education and engineering industry. However, there is little evidence to determine whether their assets are due to military service or other demographic factors such as age, maturity, or gender. The aim of this study is to discover, better understand, and disseminate the unique assets that veterans gained through military service and continue to employ as engineering students or professional engineers. This strength-based thematic analysis investigated the semi-structured narrative interviews of 18 military veterans who are now engineering students or professionals in engineering industry. Using the Funds of Knowledge framework, veterans’ Funds of Knowledge were identified and analyzed for emergent themes. Participants exhibited 10 unique veterans’ Funds of Knowledge. Utilizing analytical memos, repeated reflection, and iterative analysis, two overarching themes emerged, Effective Teaming in Engineering and Adapting to Overcome Challenges. Additionally, a niche concept of Identity Crafting was explored using the unique narratives of two participants. This study provides empirical evidence of military veterans experientially learning valuable assets in engineering from their military service. A better understanding of the veterans’ Funds of Knowledge presented in this study provides valuable opportunities for their utilization in engineering education and engineering industry.
ContributorsSheppard, Michael Scott (Author) / Kellam, Nadia N (Thesis advisor) / Bekki, Jennifer M (Committee member) / Brunhaver, Samantha R (Committee member) / Arizona State University (Publisher)
Created2020
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Description
A defining feature of many United States (U.S.) doctoral engineering programs is their large proportion of international students. Despite the large student body and the significant impacts that they bring to the U.S. education and economy, a scarcity of research on engineering doctoral students has taken into consideration the existence

A defining feature of many United States (U.S.) doctoral engineering programs is their large proportion of international students. Despite the large student body and the significant impacts that they bring to the U.S. education and economy, a scarcity of research on engineering doctoral students has taken into consideration the existence of international students and the consequential diversity in citizenship among all students. This study was designed to bridge the research gap to improve the understanding of sense of belonging from the perspective of international engineering doctoral students.

A multi-phase mixed methods research approach was taken for this study. The qualitative strand focused on international engineering doctoral students’ sense of belonging and its constructs. Semi-structured interview data were collected from eight international students enrolled at engineering doctoral programs at four different institutions. Thematic analysis and further literature review produced a conceptual structure of sense of belonging among international engineering doctoral students: authentic-self, problem behavior, academic self-efficacy, academic belonging, sociocultural belonging, and perceived institutional support.

The quantitative strand of this study broadened the study’s population to all engineering doctoral students, including domestic students, and conducted comparative analyses between international and domestic student groups. An instrument to measure the Engineering Doctoral Students’ Quality of Interaction (EDQI instrument) was developed while considering the multicultural nature of interactions and the discipline-specific characteristics of engineering doctoral programs. Survey data were collected from 653 engineering doctoral students (383 domestic and 270 international) at 36 R1 institutions across the U.S. Exploratory Factor Analysis results confirmed the construct validity and reliability of the data collected from the instrument and indicated the factor structures for the students’ perceived quality interactions among domestic and international student groups. A set of separate regression analyses results indicated the significance of having meaningful interactions to students’ sense of belonging and identified the groups of people who make significant impacts on students’ sense of belonging for each subgroup. The emergent findings provide an understanding of the similarities and differences in the contributors of sense of belonging between international and domestic students, which can be used to develop tailored support structures for specific student groups.
ContributorsLee, Eunsil (Author) / Bekki, Jennifer (Thesis advisor) / Carberry, Adam (Thesis advisor) / Kellam, Nadia (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Access to real-time situational information including the relative position and motion of surrounding objects is critical for safe and independent travel. Object or obstacle (OO) detection at a distance is primarily a task of the visual system due to the high resolution information the eyes are able to receive from

Access to real-time situational information including the relative position and motion of surrounding objects is critical for safe and independent travel. Object or obstacle (OO) detection at a distance is primarily a task of the visual system due to the high resolution information the eyes are able to receive from afar. As a sensory organ in particular, the eyes have an unparalleled ability to adjust to varying degrees of light, color, and distance. Therefore, in the case of a non-visual traveler, someone who is blind or low vision, access to visual information is unattainable if it is positioned beyond the reach of the preferred mobility device or outside the path of travel. Although, the area of assistive technology in terms of electronic travel aids (ETA’s) has received considerable attention over the last two decades; surprisingly, the field has seen little work in the area focused on augmenting rather than replacing current non-visual travel techniques, methods, and tools. Consequently, this work describes the design of an intuitive tactile language and series of wearable tactile interfaces (the Haptic Chair, HaptWrap, and HapBack) to deliver real-time spatiotemporal data. The overall intuitiveness of the haptic mappings conveyed through the tactile interfaces are evaluated using a combination of absolute identification accuracy of a series of patterns and subjective feedback through post-experiment surveys. Two types of spatiotemporal representations are considered: static patterns representing object location at a single time instance, and dynamic patterns, added in the HaptWrap, which represent object movement over a time interval. Results support the viability of multi-dimensional haptics applied to the body to yield an intuitive understanding of dynamic interactions occurring around the navigator during travel. Lastly, it is important to point out that the guiding principle of this work centered on providing the navigator with spatial knowledge otherwise unattainable through current mobility techniques, methods, and tools, thus, providing the \emph{navigator} with the information necessary to make informed navigation decisions independently, at a distance.
ContributorsDuarte, Bryan Joiner (Author) / McDaniel, Troy (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Venkateswara, Hemanth (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Over the past decade, machine learning research has made great strides and significant impact in several fields. Its success is greatly attributed to the development of effective machine learning algorithms like deep neural networks (a.k.a. deep learning), availability of large-scale databases and access to specialized hardware like Graphic Processing Units.

Over the past decade, machine learning research has made great strides and significant impact in several fields. Its success is greatly attributed to the development of effective machine learning algorithms like deep neural networks (a.k.a. deep learning), availability of large-scale databases and access to specialized hardware like Graphic Processing Units. When designing and training machine learning systems, researchers often assume access to large quantities of data that capture different possible variations. Variations in the data is needed to incorporate desired invariance and robustness properties in the machine learning system, especially in the case of deep learning algorithms. However, it is very difficult to gather such data in a real-world setting. For example, in certain medical/healthcare applications, it is very challenging to have access to data from all possible scenarios or with the necessary amount of variations as required to train the system. Additionally, the over-parameterized and unconstrained nature of deep neural networks can cause them to be poorly trained and in many cases over-confident which, in turn, can hamper their reliability and generalizability. This dissertation is a compendium of my research efforts to address the above challenges. I propose building invariant feature representations by wedding concepts from topological data analysis and Riemannian geometry, that automatically incorporate the desired invariance properties for different computer vision applications. I discuss how deep learning can be used to address some of the common challenges faced when working with topological data analysis methods. I describe alternative learning strategies based on unsupervised learning and transfer learning to address issues like dataset shifts and limited training data. Finally, I discuss my preliminary work on applying simple orthogonal constraints on deep learning feature representations to help develop more reliable and better calibrated models.
ContributorsSom, Anirudh (Author) / Turaga, Pavan (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Spanias, Andreas (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2020