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Decentralized control for cooperative load transport
No full textAugust 2021School of EngineeringCoordinated control of multiple robots has always been a popular topic in the robotics control field. The reason behind it is that a cooperative control strategy can easily overcome the limited capability of a single robot. For example, using various small robots to transport a payload versus one giant robot can avoid purchasing the expensive giant robot and keep the maintenance effort low. In this thesis, we examine the task of controlling multiple robots to transport a rigid load in a decentralized manner. The main concept is to design a controller which can command a swarm of mobile manipulators to collaboratively carry a payload that exceeds the capability of a single robot. Based on this target, we propose a decentralized controller inspired by admittance control in robotics control literature. The proposed controller addresses robot’s motions and forces without sharing other participated robots’ kinematic and dynamic information. It ensures that each robot can converge to the desired force setpoint and simultaneously achieve the same predefined velocity. This control strategy is evaluated on two physical robot hardware implementations. A total of five different experiments are conducted and the corresponding results are included to demonstrate the effectiveness of the proposed scheme.M
A mathematical model for freight -efficient land use planning
No full textMay 2022School of EngineeringThis research develops the first analytical model to support Freight Efficient Land-Use (FELU) design and planning while explicitly considering the effects of land-use decisions on supply chains. To do so a facility location model with entropy maximization is developed. The model seeks to minimize social costs associated with supply chain activity. The formulation developed as part of this research is the first one that explicitly: (1) considers the effects of land-use decisions on supply chains, and specifically, on the delivery tour patterns emanating from distribution centers; and (2) seeks to minimize the total associated social costs. Currently, there are no methodologies that capture the interconnection between land-use location decisions and their impacts along the supply chain. Addressing this gap in the literature is critical considering the tremendous impacts land-use decisions have on the efficiency of both upstream and downstream supply chains. A case study of New York City is presented in which four different industry sectors are modeled. Optimal locations for building distribution centers are showed. The results from the model display how there is a constant tradeoff between being close to main attractors of cargo, how expensive the location cost is, and the operational cost of trucks. In addition, it is showed how by incorporating an environmental justice component into the model the selection of optimum locations for distribution centers changes. Ultimately, this research aims to improve land-use regional planning processes by means of fostering more compact supply chains—reducing Vehicles Miles Travelled (VMTs) to increase efficiency—as well as more sustainable economies in which efficiency, livability and environmental objectives go hand in hand.Ph
Post-damage reconfiguration for rotorcraft with control redundancy
No full textDecember 2021School of EngineeringAircraft survivability in the event of component failure or some loss of control effectiveness is a critical area of research, particularly with regards to the control system design. While this has been thoroughly researched for fixed-wing aircraft since the 1980s, there has been a lack of a similar body of work for rotorcraft. This lack is mainly due to the absence of control redundancy on a conventional single main rotor helicopter. A fully compounded helicopter bridges this gap by adding fixed-wing control surfaces (flaps, ailerons, stabilator, and rudder) and compound-specific auxiliary controls (propeller thrust and main rotor speed). When the platform of interest possesses a significant amount of control redundancy, the allocation of these controls plays a vital role in the system's performance and longevity. The design choices made can allow for tolerance to a range of different control failures. The availability of redundant control effectors allows for an exploration of its ability to tolerate damage on an aircraft, thereby improving its survivability. Furthermore, there is little understanding of a rotorcraft's flight dynamics and transient behavior when damage occurs, and the controls are reconfigured to tolerate such damage. This exploration forms the crux of this dissertation. On a UH-60 Black Hawk, the stabilator can act as a redundant control effector at moderate to high-speed flight conditions. A steady-state trim analysis is performed to demonstrate the feasibility of trimmed flight in various conditions with different locked servo actuator positions for the forward, aft, and lateral actuators. After failure, the controls are reconfigured to partially reallocate the control authority in the longitudinal axis from the main rotor longitudinal cyclic to the stabilator. Flight simulation results demonstrate the ability of this reallocation to compensate for locked-in-place failure of the forward main rotor swashplate servo actuator, as well as the ability of the aircraft to recover safely through a rolling landing maneuver. A similar range of locked positions of main rotor swashplate actuators is demonstrated to be feasible for aircraft recovery using control of the stabilator. So far, stabilator use has been shown to work in an adaptive sense, where the control mixing is remapped in flight once failure is detected. Next, it is shown to perform well when the defined mixing utilizes the stabilator even on the undamaged aircraft, removing the need to detect and identify specific failures on the aircraft. Further investigation considered the benefit of allowing for more or less longitudinal authority to be given to the stabilator in different flight conditions in the context of handling qualities ratings for the aircraft in pitch attitude and vertical rate response. Stabilator hardover failure is also examined. This work is then extended onto the compound helicopter platform. A reconfigurable control allocation method is applied on a compound helicopter in order to utilize the redundant control effectors in the feedback loop to compensate for locked-in-place actuator failures. A range of tolerable positions for locked-in-place actuator failures is established for the aircraft at a cruise speed of 150 knots. A full authority model following linear dynamic inversion control architecture is implemented for the nonlinear simulation model. It is shown to successfully compensate for actuator failures when the feedback control and the pseudoinverse control allocation method redistributes the control authority to the working actuators, assuming fault detection has taken place. Finally, a comparison of the robustness of a baseline pseudoinverse control allocation to an adaptive redistributed pseudoinverse method when the aircraft is subjected to different actuator failure at their extreme positions is examined. This is carried out through handling qualities based assessment and dynamic nonlinear flight simulations.Ph
Investigation of coprime sound diffusers using one-fifth scale modeling
No full textDecember 2015School of ArchitectureIn acoustics, a room is often characterized by factors such as its ability to absorb, reflect, and spread the sound in it. The spreading of sound is generally accomplished with diffusers, which scatter sound based on the angle of incidence and frequency. These diffusers come in all shapes and sizes, which can be wall and floor mounted as well as encompass a volume of the room. Recent work in other fields has allowed for investigations on how this work could be implemented to diffuser theory. In one field of acoustics, sparse sensing for microphone arrays has led to the creation of the coprime linear array. The coprime array concepts can be applied to volumetric diffusers using cylinders. These are arranged in pairs of co-prime arrays in which the number of cylinders consist of two mutually prime numbers of elements for a sparse arrangement. Coprime sound diffusers are tested experimentally using one-fifth scale measurements as well as an acoustic goniometer to see how beneficial this diffuser could be in real world applications.M
Algae bioreactor building envelope - energy saving and CO2 sequestion information display shading system
No full textDecember 2021School of ArchitectureIn recent years, several algae-based facade systems have been integrated into buildings. They have high ecological performance, working as a multi-functional system to reduce energy use and capture carbon dioxide (CO2). Compared with other dynamic building envelopes, the algae bio-reactive building envelope (ABBE) is unique to other dynamic building envelopes because it contains a bio-driven dynamic building skin rather than the traditional mechanically driven skin. Although algae bioreactor building systems have the potential to replace existing mechanical dynamic shading, their implementation has been limited due to the high costs associated with their research, development, and implementation. Much of ABBE research has focused on early concept exploration and feasibility discussions rather than the development and testing of actual implementations. The only real-world built project, the Bio Intelligent Quotient, investigates an algae bioreactor building envelope's energy gain and biomass harvest. However, solely using ABBEs’ ability- to harvest energy to justify its usefulness may not be enough to support ABBE research and development at scale. This thesis discusses how algae bioreactors react to buildings' environments and demonstrates the significance of bio-driven dynamic shading in buildings in addition to the energy perspective. This research aims to bring algae into cities using algae bioreactors on building envelopes. Algae bioreactors that respond to CO2 concentration, lighting, and temperature can be used as information display that show environmental conditions. Using algae's extraordinary properties, this study establishes a connection between environmental information and building appearance while also capturing CO2, generating electricity, storing thermal mass, and providing shading for indoor environments. Moreover, shading has enormous potential to help to reduce buildings’ CO2 emissions and energy use.
How algae bioreactors respond to people's living conditions, such as lighting, air (CO2), or temperature, are also examined through using built prototype experiments and computer simulation. To accomplish this, I use a prototype that focuses on creating algae façade color variation, which means creating interaction between algae appearance and environmental conditions. Additionally, I use digital simulations to test how much energy the bioreactors receive from solar on a whole-scale building and speculate about how environmental factors influence algae bioreactor building envelope appearance.
An algae bioreactors building envelope is an environmentally reactive two-layer building skin that can indicate environmental conditions. Combining environmental data visualization and a bio-driven dynamic shading strategy gives designers a new design for building envelopes.M
InDO: the Institute Demographic Ontology
No full textGraduate education institutes in the United States (US) have been working on programs to increase the number of students and faculty from marginalized communities. When choosing to pursue a doctoral degree, the common question is ‘where is the best fit for me?’ Aspiring graduate students may feel the need for a reference point - someone with a similar background who has experienced or is currently experiencing the doctoral process, whether that be a student or a faculty member. Currently, there is no single location where that question can be answered for those in marginal communities, however answering that question also has an impact on the student’s post-graduation career path. In lieu of a single person, and to help provide information critical to answering the question, we built the Institute Demographic Ontology (InDO). InDO integrates US graduate institute’s doctoral recipient demographic data with data describing broad field of study, fine field of study, and the pursued career path to produce a knowledge graph for each prospective student’s query. The terminology is structured in five levels of hierarchy providing room for the most abstract top level (basic components used to describe an institute’s demographics), to the most concrete bottom levels (particular graduate program offered by the institute, along with corresponding provenance). Our resource (InDO) could be used by students within a marginalized community in the US to infer whether a given institute has the resources to support a given program, based on demographic information such as number of doctorates awarded in a given field. We design a use case where an InDO-based knowledge graph is created incorporating some of the National Science Foundation (NSF) Doctoral Recipient Survey 2019 data. Our use case demonstrates the usage of InDO in the real world while providing a way to access NSF data in a machine readable format. Evaluation of our ontology is done with a set of competency questions created from the perspective of an aspirant marginalized graduate student who would be willing to use our system to gather information for making an informed decision. InDO provides an ontological foundation towards building a social machine as an aid to higher education and graduate mobility in the US
Comparative performance evaluation of conventional and superjunction vertical 4H-silicon carbide high-voltage power mosfets
No full textMay 2022School of Engineering4H-SiC exhibits a 10× higher critical breakdown field than silicon, enabling its high-voltage power devices possible to achieve >1000x smaller specific on-resistance (RON,sp) than Si-based devices at the same breakdown voltage (BV). In addition, high-voltage superjunction (SJ) devices have better performance than conventional devices due to a lower drift specific on-resistance, reducing the conduction power loss. In this thesis, we comparatively evaluate 0.6-10kV-rated, vertical power DMOS and UMOS FETs with their SJ counterparts, in 4H-SiC, in terms of their static and dynamic switching performances.
The static conduction loss of these transistors is estimated from the specific on-resistance, which is calculated using analytical expressions for each region. We utilize the specific total charge QT,sp for the dynamic switching power loss, extracted from TCAD (Sentaurus) simulations. Also, the turn-on time (ton), turn-off time (toff), and switching energy loss per cycle (Esw/cycle) are determined.
The specific on-resistance is reduced by 89 and 78% for SJ UMOS and DMOS, respectively, compared to their conventional counterparts at 3.3kV due to higher pillar doping and lower drift layer resistance. The QT,sp reduction is reduced by 8 and 20% at all BV ratings. The lower RON,sp of UMOS devices is due to a higher channel density than DMOS devices, hence better RCH,sp. The turn-off time is higher for UMOS FETs because of higher QT,sp, hence, higher switching energy losses per cycle.
Moreover, the SJ UMOS FET with the narrowest pillar width exhibits substantial reduction (up to 24, and 99 %) in our NFOM (RON,sp . QT,sp) compared to conventional UMOS FET at 0.6 to 10kV respectively because drift layer resistance dominates at high BV ratings. Meanwhile, the reduction is 30%, 30%, and 81% in SJ DMOS at the same breakdown voltage ratings. SJ UMOS has a higher switching losses due to a 67% higher QT,sp compared to SJ DMOS, but it has a significant lower 47% in RON,sp, achieving the lowest FOM, with a reduction of 53 to at least 31% compared to SJ DMOS FET at the same BV ratings respectively because the specific on-resistance of both devices approaches the same value at high BV ratings.
In summary, the SJ UMOS FET has the best performance in terms of the lowest FOM among the SJ and conventional power MOSFETs compared, inferring to have the lowest total (conduction and switching) energy loss.M
Probabilistic acousto-ultrasonic active-sensing structural health monitoring based on gaussian process and stochastic time series models
No full textAugust 2021School of EngineeringIn the context of engineering structures, structural safety, maintenance and life-cycle management processes are a major factor in sustainability. In particular, the aerospace industry is one that depends heavily on schedule-based procedures in order to sustain proper life-cycle management, ensure safety, and improve performance. Most of such procedures include some type of Non-destructive Evaluation (NDE) techniques, in which aircraft need to be inspected on a regular basis on the ground before operations can be resumed regardless of structural state. This framework, although very effective in the sustainability efforts of the aerospace industry, suffers from a number of drawbacks; the most economically-prominent of which are cost, increased downtime, less-than-optimal safety management paradigm (damage can occur and grow between scheduled procedures) and the limited applicability of fully-autonomous operations. As such, research endeavors in the past 40 years have been directed towards developing sustainability efforts that can be applied online (limiting downtime and increasing safety) and in an automated fashion (limiting the need for costly man hours, and also allowing for autonomous operation). Aside from the implementation of such frameworks in the industry of rotating machinery, the collection of these online frameworks falls under the field of Structural Health Monitoring (SHM). Because of the complexity of aircraft operations, manifested in multiple operational cycles, and, within each cycle, the varying operational and environmental conditions, the aerospace industry poses as a very rich arena for development of SHM techniques \cite{Dong-Kim18}. When it comes to active-sensing guided-wave SHM in particular, where piezoelectric sensors communicate with each other, owing to the fact that most of the currently-employed approaches are of a deterministic nature, i.e. they do not account for operational, environmental and modelling uncertainties, the complexity of aerospace SHM creates a number of challenges in the face of researchers in the active-sensing SHM field today. Namely, emerging SHM technologies need to be accurate and robust in the face of stochastic time-varying and non-linear structural responses, as well as incipient damage types and complex failure modes that can be easily masked by the effects of varying operational and environmental conditions. In addition, with the advancement in on-board data acquisition technologies, SHM frameworks need to be data-intelligent i.e. they need to be capable of using data efficiently. Thus, there lies a need for the development of active-sensing SHM frameworks, where proper understanding, modeling, and analysis of stochastic structural responses under varying states and damage characteristics is achieved for clearing the road towards achieving the aforementioned ultimate goal of SHM systems. This is where \textit{probabilistic SHM} comes in. This thesis attempts to pave the way towards fully-probabilistic frameworks for active-sensing, guided-wave SHM. With focus on damage detection and quantification, statistical and probabilistic techniques are put forward that not only properly model uncertainties in the data coming from the system being interrogated, but also surpass currently-used methods in accuracy. In addition, this thesis addresses the issue of data-intelligence of probabilistic models through a number of approaches. The first problem tackled in this thesis is statistical damage detection, where statistics based on non-parametric time series representations are proposed and applied to test cases to compare their detection performance with standard state-of-the-art damage indicators. Then, once damage is detected, the problem of data-intelligence is addressed through proposing a statistical signal path selection algorithm, again based on non-parametric time series models, which classifies signal paths into damage-intersecting and non-intersecting, where only the former is used in training damage quantification models. After that, probabilistic damage quantification is addressed next through proposing three frameworks based on the probabilistic machine learning techniques within the family of Gaussian Process (GP) models. The first probabilistic damage quantification framework uses industry-standard damage indicators to build the GP models. The second GP framework uses one of the damage detection statistics mentioned above. The third quantification framework uses GP models that are trained using time-varying parametric time series representations. Other work don in this thesis include the integration of physics-based load-compensation models with GP models for situations where critical data is missing in the training space. Also multi-output GP models are proposed to leverage information from across a sensor network for better damage quantification. All in all, the methods presented in this thesis are intended to bring the active-sensing, guided-wave SHM community one step closer to a full probabilistic treatment of SHM problems; the research herein should be considered as a stepping stone towards that goal. This being said, from the studies conducted in this thesis, a plethora of open research questions that need to be answered emerge, with some of them mentioned at the end of the thesis.Ph
Shortest path network interdiction under uncertainty
No full textAugust 2022School of ScienceThis research considers three extensions of the shortest path network interdiction problem to protect against parameter uncertainty. The shortest path interdiction problem is a game of two players with conflicting agendas and capabilities: an evader, who traverses the arcs of a network from a source node to a sink node using the path of shortest length, and an interdictor, who maximizes the length of the evader's shortest path by interdicting arcs on the network. It is usually assumed that the parameters defining the network are known exactly by both players. In the first variant, we consider the situation where the evader assumes the nominal parameter values while the interdictor uses robust optimization techniques to account for parameter uncertainty or sensor degradation. Solving the shortest path interdiction problem with asymmetric uncertainty protects the interdictor from investing in the obvious strategy if that strategy hinges on key interdictions performing as promised. It also provides an alternate strategy that mitigates the risk of these worst-case possibilities. In the second variant, we extend past the previous model to allow the interdictor to interdict an arc multiple times or bolster an arc to further combat parameter uncertainty. We formulate these problems as nonlinear mixed integer trilevel programs and show that they can be converted into mixed integer linear programs with second order cone constraints. The third variant extends an existing variant of the shortest path network interdiction problem where the evader has asymmetric knowledge of the network parameters. The interdictor knows exactly what the evader's misassumptions are and can leverage that information for an improved outcome. Our extension allows for interdictor uncertainty as to exactly what the evader assumes as the network parameters. We develop a decomposition algorithm to solve this model. For all models, we use random geometric networks and transportation networks to perform computational studies and demonstrate the unique decision strategies that our variants produce.Ph
Study on the corrosion behavior of Inconel 625 in molten chloride salt
No full textAugust 2021School of EngineeringConcentrated solar power (CSP) has been used as one of the most important clean and renewable energy sources. Molten chloride salts, which possess excellent thermal-physical properties with low economic cost, have become the most promising heat transfer media and thermal energy storage media for new generation CSP in recent years. However, molten chloride salts are very corrosive to the thermal components and containment materials such as piping, storage tanks and heat exchangers. Extensive studies have been devoted to the corrosion behaviors of nitrate and fluoride salts which are commonly used in traditional solar power plants and molten salt nuclear reactors respectively. But there has been relatively little research on the corrosion behavior of molten chloride salts to Ni-based alloy film. The goal of this study is to study the corrosion behaviors of the Inconel 625 film in molten chloride salt, and to explore methods of improving the corrosion resistance of the film by combining both high-temperature corrosion experiments and cellular automata (CA) simulations. In order to achieve this goal, three task have been conducted in this study: (i) Explore the microstructure of the Inconel 625 film obtained by magnetron sputtering; (ii) Investigate the corrosion behavior of molten chloride salt to Inconel 625 film and improve the corrosion resistance of Inconel 625 by growing the grain size of the film; (iii) Develop a cellular automata program to mimic the diffusion-reaction process of molten salt. Surface morphology and film phase identification are studied by scanning electron microscope (SEM) and X-ray diffraction (XRD) respectively. The SEM scan shows that the grain size of the films obtained by magnetron sputtering grows with the rising deposition temperature. Based on the XRD patterns, all these films display planes of (111) and (222) of Ni3Cr2, but the film deposited at 600 °C exhibits a unique peak at 51° corresponding to (200) of Ni3Cr2. XRD rocking curves show a decreasing FWHM value with increased grain size, which indicates that film deposited at higher temperature has relatively higher degree of crystallinity. A seven-slab reflectometry model (Sapphire - Inner contamination - Inconel sublayer - Principal Inconel - Oxide - Outer contamination - Air) has been successfully developed and verified to study the layered structure of Inconel 625 films with atomic-scale spatial resolution along the surface normal. The model reveals that ~2 nm thick Inconel sublayer is found underneath the principal Inconel film. A thin NiO oxide layer is found on top of the principle Inconel. The thickness of NiO layer is observed to decrease with growing deposition temperature. Two very thin contaminations are identified both on the substrate and on the oxide film respectively. The corrosion tests are conducted to study the corrosion behaviors of Inconel 625 in molten salt, which indicate that Cr is the most readily attacked element in Inconel 625. It is also found that Mo enrichment occurs in most Cr-depleted regions. Among salt ingredients, Mg and Cl are two most commonly observed elements in the corroded films. The comparison of corrosion tests for films with different grain size demonstrates that the increase of the film grain size alleviates the Cr depletion and consequently improves the corrosion resistance of Inconel 625. We successfully developed a CA model with a graphical user interface to simulate the corrosion processes of films with different grain size. It is found that the film with larger grain size is more corrosion resistant and the ratio of Cr and Ni decreases with generation, which are consistent with experimental results. In addition, all surface roughness curves exhibit very large fluctuations in the course of corrosion. The sharp roughness rise is usually caused by the corrosion along vertical grain boundaries while the sudden drop is attributed by the detachment of grains from the film. These findings are beneficial in predicting and improving the material properties of Ni-based alloys, and thus provide guidance for the materials selection in third generation CSP.Ph