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- All Subjects: Electrical Engineering
- All Subjects: Civil Engineering
- Creators: Arizona State University
- Creators: Holbert, Keith E.
- Creators: Spanias, Andreas
Description
Entering a new market in the construction industry is a complex task. Although many contractors have experienced the benefits of expanding their market offerings, many more have had unsuccessful experiences causing hardship for the entire organization. Standardized decision-making processes can help to increase the likelihood of success, but few specialty contractors have taken the time to develop a formal procedure. According to this research, only 6 percent of survey respondents and 7 percent of case study participants from the sheet metal industry have a formal decision process. Five sources of data (existing literature, industry survey, semi-structured interviews, factor prioritization workshops, and expert panel discussions) are consulted to understand the current market entry decision-making practices and needs of the sheet metal industry. The data help to accomplish three study objectives: (1) determine the current processes and best practices used for market entry decision-making in the sheet metal industry, (2) identify motivations leading to market entry by sheet metal contractors, and (3) develop a standardized decision process that improves market entry decision outcomes. Grounded in a firm understanding of industry practices, a three-phased decision-making framework is created to provide a structured approach to guide contractors to an informed decision. Four industry leaders with over 175 years of experience in construction reviewed and applied every step of the framework to ensure it is practical and easy to use for contractors.
ContributorsSullivan, Jera J (Author) / El Asmar, Mounir (Thesis advisor) / Gibson, G Edward (Committee member) / Sullivan, Kenneth (Committee member) / Arizona State University (Publisher)
Created2016
Description
Kinetic inductance springs from the inertia of charged mobile carriers in alternating electric fields and it is fundamentally different from the magnetic inductance which is only a geometry dependent property. The magnetic inductance is proportional to the volume occupied by the electric and magnetic fields and is often limited by the number of turns of the coil. Kinetic inductance on the other hand is inversely proportional to the density of electrons or holes that exert inertia, the unit mass of the charge carriers and the momentum relaxation time of these charge carriers, all of which can be varied merely by modifying the material properties. Highly sensitive and broadband signal amplifiers often broaden the field of study in astrophysics. Quantum-noise limited travelling wave kinetic inductance parametric amplifiers offer a noise figure of around 0.5 K ± 0.3 K as compared to 20 K in HEMT signal amplifiers and can be designed to operate to cover the entire W-band (75 GHz – 115 GHz).The research cumulating to this thesis involves applying and exploiting kinetic inductance properties in designing a W-band orthogonal mode transducer, quadratic gain phase shifter with a gain of ~49 dB over a meter of microstrip transmission line. The phase shifter will help in measuring the maximum amount of phase shift ∆ϕ_max (I) that can be obtained from half a meter transmission line which helps in predicting the gain of a travelling wave parametric amplifier. In another project, a microstrip to slot line transition is designed and optimized to operate at 150 GHz and 220 GHz frequencies, that is used as a part of horn antenna coupled microwave kinetic inductance detector proposed to operate from 138 GHz to 250 GHz. In the final project, kinetic inductance in a 2D electron gas (2DEG) is explored by design, simulation, fabrication and experimentation. A transmission line model of a 2DEG proposed by Burke (1999), is simulated and verified experimentally by fabricating a capacitvely coupled 2DEG mesa structure. Low temperature experiments were done at 77 K and 10 K with photo-doping the 2DEG. A circuit model of a 2DEG coupled co-planar waveguide model is also proposed and simulated.
ContributorsSurdi, Harshad (Author) / Mauskopf, Philip (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2016
Description
The power of science lies in its ability to infer and predict the
existence of objects from which no direct information can be obtained
experimentally or observationally. A well known example is to
ascertain the existence of black holes of various masses in different
parts of the universe from indirect evidence, such as X-ray emissions.
In the field of complex networks, the problem of detecting
hidden nodes can be stated, as follows. Consider a network whose
topology is completely unknown but whose nodes consist of two types:
one accessible and another inaccessible from the outside world. The
accessible nodes can be observed or monitored, and it is assumed that time
series are available from each node in this group. The inaccessible
nodes are shielded from the outside and they are essentially
``hidden.'' The question is, based solely on the
available time series from the accessible nodes, can the existence and
locations of the hidden nodes be inferred? A completely data-driven,
compressive-sensing based method is developed to address this issue by utilizing
complex weighted networks of nonlinear oscillators, evolutionary game
and geospatial networks.
Both microbes and multicellular organisms actively regulate their cell
fate determination to cope with changing environments or to ensure
proper development. Here, the synthetic biology approaches are used to
engineer bistable gene networks to demonstrate that stochastic and
permanent cell fate determination can be achieved through initializing
gene regulatory networks (GRNs) at the boundary between dynamic
attractors. This is experimentally realized by linking a synthetic GRN
to a natural output of galactose metabolism regulation in yeast.
Combining mathematical modeling and flow cytometry, the
engineered systems are shown to be bistable and that inherent gene expression
stochasticity does not induce spontaneous state transitioning at
steady state. By interfacing rationally designed synthetic
GRNs with background gene regulation mechanisms, this work
investigates intricate properties of networks that illuminate possible
regulatory mechanisms for cell differentiation and development that
can be initiated from points of instability.
existence of objects from which no direct information can be obtained
experimentally or observationally. A well known example is to
ascertain the existence of black holes of various masses in different
parts of the universe from indirect evidence, such as X-ray emissions.
In the field of complex networks, the problem of detecting
hidden nodes can be stated, as follows. Consider a network whose
topology is completely unknown but whose nodes consist of two types:
one accessible and another inaccessible from the outside world. The
accessible nodes can be observed or monitored, and it is assumed that time
series are available from each node in this group. The inaccessible
nodes are shielded from the outside and they are essentially
``hidden.'' The question is, based solely on the
available time series from the accessible nodes, can the existence and
locations of the hidden nodes be inferred? A completely data-driven,
compressive-sensing based method is developed to address this issue by utilizing
complex weighted networks of nonlinear oscillators, evolutionary game
and geospatial networks.
Both microbes and multicellular organisms actively regulate their cell
fate determination to cope with changing environments or to ensure
proper development. Here, the synthetic biology approaches are used to
engineer bistable gene networks to demonstrate that stochastic and
permanent cell fate determination can be achieved through initializing
gene regulatory networks (GRNs) at the boundary between dynamic
attractors. This is experimentally realized by linking a synthetic GRN
to a natural output of galactose metabolism regulation in yeast.
Combining mathematical modeling and flow cytometry, the
engineered systems are shown to be bistable and that inherent gene expression
stochasticity does not induce spontaneous state transitioning at
steady state. By interfacing rationally designed synthetic
GRNs with background gene regulation mechanisms, this work
investigates intricate properties of networks that illuminate possible
regulatory mechanisms for cell differentiation and development that
can be initiated from points of instability.
ContributorsSu, Ri-Qi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Bliss, Daniel (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2015
Description
Self-heating degrades the performance of devices in advanced technology nodes. Understanding of self-heating effects is necessary to improve device performance. Heat generation in these devices occurs at nanometer scales but heat transfer is a microscopic phenomena. Hence a multi-scale modeling approach is required to study the self-heating effects. A state of the art Monte Carlo device simulator and the commercially available Giga 3D tool from Silvaco are used in our study to understand the self heating effects. The Monte Carlo device simulator solves the electrical transport and heat generation for nanometer length scales accurately while the Giga 3D tool solves for thermal transport over micrometer length scales. The approach used is to understand the self-heating effects in a test device structure, composed of a heater and a sensor, fabricated and characterized by IMEC. The heater is the Device Under Test(DUT) and the sensor is used as a probe. Therefore, the heater is biased in the saturation region and the sensor is biased in the sub-threshold regime. Both are planar MOSFETs of gate length equal to 22 nm. The simulated I-V characteristics of the sensor match with the experimental behavior at lower applied drain voltages but differ at higher applied biases.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
The self-heating model assumes that the heat transport within the device follows Energy Balance model which may not be accurate. To properly study heat transport within the device, a state of the art Monte Carlo device simulator is necessary. In this regard, the Phonon Monte Carlo(PMC) simulator is developed. Phonons are treated as quasi particles that carry heat energy. Like electrons, phonons obey a corresponding Boltzmann Transport Equation(BTE) which can be used to study their transport. The direct solution of the BTE for phonons is possible, but it is difficult to incorporate all scattering mechanisms. In the Monte Carlo based solution method, it is easier to incorporate different relevant scattering mechanisms. Although the Monte Carlo method is computationally intensive, it provides good insight into the physical nature of the transport problem. Hence Monte Carlo based techniques are used in the present work for studying phonon transport. Monte Carlo simulations require calculating the scattering rates for different scattering processes. In the present work, scattering rates for three phonon interactions are calculated from different approaches presented in the literature. Optical phonons are also included in the transport problem. Finally, the temperature dependence of thermal conductivity for silicon is calculated in the range from 100K to 900K and is compared to available experimental data.
ContributorsShaik, Abdul Rawoof (Author) / Vasileska, Dragica (Thesis advisor) / Ferry, David (Committee member) / Goodnick, Stephan (Committee member) / Arizona State University (Publisher)
Created2016
Description
Spectral congestion is quickly becoming a problem for the telecommunications sector. In order to alleviate spectral congestion and achieve electromagnetic radio frequency (RF) convergence, communications and radar systems are increasingly encouraged to share bandwidth. In direct opposition to the traditional spectrum sharing approach between radar and communications systems of complete isolation (temporal, spectral or spatial), both systems can be jointly co-designed from the ground up to maximize their joint performance for mutual benefit. In order to properly characterize and understand cooperative spectrum sharing between radar and communications systems, the fundamental limits on performance of a cooperative radar-communications system are investigated. To facilitate this investigation, performance metrics are chosen in this dissertation that allow radar and communications to be compared on the same scale. To that effect, information is chosen as the performance metric and an information theoretic radar performance metric compatible with the communications data rate, the radar estimation rate, is developed. The estimation rate measures the amount of information learned by illuminating a target. With the development of the estimation rate, standard multi-user communications performance bounds are extended with joint radar-communications users to produce bounds on the performance of a joint radar-communications system. System performance for variations of the standard spectrum sharing problem defined in this dissertation are investigated, and inner bounds on performance are extended to account for the effect of continuous radar waveform optimization, multiple radar targets, clutter, phase noise, and radar detection. A detailed interpretation of the estimation rate and a brief discussion on how to use these performance bounds to select an optimal operating point and achieve RF convergence are provided.
ContributorsChiriyath, Alex Rajan (Author) / Bliss, Daniel W (Thesis advisor) / Cochran, Douglas (Committee member) / Kosut, Oliver (Committee member) / Richmond, Christ D (Committee member) / Arizona State University (Publisher)
Created2018
Description
Energy harvesting from ambient is important to configuring Wireless Sensor Networks (WSN) for environmental data collecting. In this work, highly flexible thermoelectric generators (TEGs) have been studied and fabricated to supply power to the wireless sensor notes used for data collecting in hot spring environment. The fabricated flexible TEGs can be easily deployed on the uneven surface of heated rocks at the rim of hot springs. By employing the temperature gradient between the hot rock surface and the air, these TEGs can generate power to extend the battery lifetime of the sensor notes and therefore reduce multiple batteries changes where the environment is usually harsh in hot springs. Also, they show great promise for self-powered wireless sensor notes. Traditional thermoelectric material bismuth telluride (Bi2Te3) and advanced MEMS (Microelectromechanical systems) thin film techniques were used for the fabrication. Test results show that when a flexible TEG array with an area of 3.4cm2 was placed on the hot plate surface of 80°C in the air under room temperature, it had an open circuit voltage output of 17.6mV and a short circuit current output of 0.53mA. The generated power was approximately 7mW/m2.
On the other hand, high pressure, temperatures that can reach boiling, and the pH of different hot springs ranging from <2 to >9 make hot spring ecosystem a unique environment that is difficult to study. WSN allows many scientific studies in harsh environments that are not feasible with traditional instrumentation. However, wireless pH sensing for long time in situ data collection is still challenging for two reasons. First, the existing commercial-off-the-shelf pH meters are frequent calibration dependent; second, biofouling causes significant measurement error and drift. In this work, 2-dimentional graphene pH sensors were studied and calibration free graphene pH sensor prototypes were fabricated. Test result shows the resistance of the fabricated device changes linearly with the pH values (in the range of 3-11) in the surrounding liquid environment. Field tests show graphene layer greatly prevented the microbial fouling. Therefore, graphene pH sensors are promising candidates that can be effectively used for wireless pH sensing in exploration of hot spring ecosystems.
On the other hand, high pressure, temperatures that can reach boiling, and the pH of different hot springs ranging from <2 to >9 make hot spring ecosystem a unique environment that is difficult to study. WSN allows many scientific studies in harsh environments that are not feasible with traditional instrumentation. However, wireless pH sensing for long time in situ data collection is still challenging for two reasons. First, the existing commercial-off-the-shelf pH meters are frequent calibration dependent; second, biofouling causes significant measurement error and drift. In this work, 2-dimentional graphene pH sensors were studied and calibration free graphene pH sensor prototypes were fabricated. Test result shows the resistance of the fabricated device changes linearly with the pH values (in the range of 3-11) in the surrounding liquid environment. Field tests show graphene layer greatly prevented the microbial fouling. Therefore, graphene pH sensors are promising candidates that can be effectively used for wireless pH sensing in exploration of hot spring ecosystems.
ContributorsHan, Ruirui (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Yu, Hongbin (Committee member) / Garnero, Edward (Committee member) / Li, Mingming (Committee member) / Arizona State University (Publisher)
Created2018
Description
High-efficiency DC-DC converters make up one of the important blocks of state-of-the-art power supplies. The trend toward high level of transistor integration has caused load current demands to grow significantly. Supplying high output current and minimizing output current ripple has been a driving force behind the evolution of Multi-phase topologies. Ability to supply large output current with improved efficiency, reduction in the size of filter components, improved transient response make multi-phase topologies a preferred choice for low voltage-high current applications.
Current sensing capability inside a system is much sought after for applications which include Peak-current mode control, Current limiting, Overload protection. Current sensing is extremely important for current sharing in Multi-phase topologies. Existing approaches such as Series resistor, SenseFET, inductor DCR based current sensing are simple but their drawbacks such low efficiency, low accuracy, limited bandwidth demand a novel current sensing scheme.
This research presents a systematic design procedure of a 5V - 1.8V, 8A 4-Phase Buck regulator with a novel current sensing scheme based on replication of the inductor current. The proposed solution consists of detailed system modeling in PLECS which includes modification of the peak current mode model to accommodate the new current sensing element, derivation of power-stage and Plant transfer functions, Controller design. The proposed model has been verified through PLECS simulations and compared with a transistor-level implementation of the system. The time-domain parameters such as overshoot and settling-time simulated through transistor-level
implementation is in close agreement with the results obtained from the PLECS model.
Current sensing capability inside a system is much sought after for applications which include Peak-current mode control, Current limiting, Overload protection. Current sensing is extremely important for current sharing in Multi-phase topologies. Existing approaches such as Series resistor, SenseFET, inductor DCR based current sensing are simple but their drawbacks such low efficiency, low accuracy, limited bandwidth demand a novel current sensing scheme.
This research presents a systematic design procedure of a 5V - 1.8V, 8A 4-Phase Buck regulator with a novel current sensing scheme based on replication of the inductor current. The proposed solution consists of detailed system modeling in PLECS which includes modification of the peak current mode model to accommodate the new current sensing element, derivation of power-stage and Plant transfer functions, Controller design. The proposed model has been verified through PLECS simulations and compared with a transistor-level implementation of the system. The time-domain parameters such as overshoot and settling-time simulated through transistor-level
implementation is in close agreement with the results obtained from the PLECS model.
ContributorsBurli, Venkatesh (Author) / Bakkaloglu, Bertan (Thesis advisor) / Garrity, Douglas (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
Description
In this dissertation, two problems are addressed in the verification and control of Cyber-Physical Systems (CPS):
1) Falsification: given a CPS, and a property of interest that the CPS must satisfy under all allowed operating conditions, does the CPS violate, i.e. falsify, the property?
2) Conformance testing: given a model of a CPS, and an implementation of that CPS on an embedded platform, how can we characterize the properties satisfied by the implementation, given the properties satisfied by the model?
Both problems arise in the context of Model-Based Design (MBD) of CPS: in MBD, the designers start from a set of formal requirements that the system-to-be-designed must satisfy.
A first model of the system is created.
Because it may not be possible to formally verify the CPS model against the requirements, falsification tries to verify whether the model satisfies the requirements by searching for behavior that violates them.
In the first part of this dissertation, I present improved methods for finding falsifying behaviors of CPS when properties are expressed in Metric Temporal Logic (MTL).
These methods leverage the notion of robust semantics of MTL formulae: if a falsifier exists, it is in the neighborhood of local minimizers of the robustness function.
The proposed algorithms compute descent directions of the robustness function in the space of initial conditions and input signals, and provably converge to local minima of the robustness function.
The initial model of the CPS is then iteratively refined by modeling previously ignored phenomena, adding more functionality, etc., with each refinement resulting in a new model.
Many of the refinements in the MBD process described above do not provide an a priori guaranteed relation between the successive models.
Thus, the second problem above arises: how to quantify the distance between two successive models M_n and M_{n+1}?
If M_n has been verified to satisfy the specification, can it be guaranteed that M_{n+1} also satisfies the same, or some closely related, specification?
This dissertation answers both questions for a general class of CPS, and properties expressed in MTL.
1) Falsification: given a CPS, and a property of interest that the CPS must satisfy under all allowed operating conditions, does the CPS violate, i.e. falsify, the property?
2) Conformance testing: given a model of a CPS, and an implementation of that CPS on an embedded platform, how can we characterize the properties satisfied by the implementation, given the properties satisfied by the model?
Both problems arise in the context of Model-Based Design (MBD) of CPS: in MBD, the designers start from a set of formal requirements that the system-to-be-designed must satisfy.
A first model of the system is created.
Because it may not be possible to formally verify the CPS model against the requirements, falsification tries to verify whether the model satisfies the requirements by searching for behavior that violates them.
In the first part of this dissertation, I present improved methods for finding falsifying behaviors of CPS when properties are expressed in Metric Temporal Logic (MTL).
These methods leverage the notion of robust semantics of MTL formulae: if a falsifier exists, it is in the neighborhood of local minimizers of the robustness function.
The proposed algorithms compute descent directions of the robustness function in the space of initial conditions and input signals, and provably converge to local minima of the robustness function.
The initial model of the CPS is then iteratively refined by modeling previously ignored phenomena, adding more functionality, etc., with each refinement resulting in a new model.
Many of the refinements in the MBD process described above do not provide an a priori guaranteed relation between the successive models.
Thus, the second problem above arises: how to quantify the distance between two successive models M_n and M_{n+1}?
If M_n has been verified to satisfy the specification, can it be guaranteed that M_{n+1} also satisfies the same, or some closely related, specification?
This dissertation answers both questions for a general class of CPS, and properties expressed in MTL.
ContributorsAbbas, Houssam Y (Author) / Fainekos, Georgios (Thesis advisor) / Duman, Tolga (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2015
Description
A new loop configuration capable of reducing power radiation magnitudes lower than conventional loops has been developed. This configuration is demonstrated for the case of two coaxial loops of 0.1 meter radius coupled via the magnetic reactive field. Utilizing electromagnetism theory, techniques from antenna design and a new near field design initiative, the ability to design a magnetic field has been investigated by using a full wave simulation tool. The method for realization is initiated from first order physics model, ADS and onto a full wave situation tool for the case of a non-radiating helical loop. The exploration into the design of a magnetic near field while mitigating radiation power is demonstrated using an real number of twists to form a helical wire loop while biasing the integer twisted loop in a non-conventional moebius termination. The helix loop setup as a moebius loop convention can also be expressed as a shorted antenna scheme. The 0.1 meter radius helix antenna is biased with a 1MHz frequency that categorized the antenna loop as electrically small. It is then demonstrated that helical configuration reduces the electric field and mitigates power radiation into the far field. In order to compare the radiated power reduction performance of the helical loop a shielded loop is used as a baseline for comparison. The shielded loop system of the same geometric size and frequency is shown to have power radiation expressed as -46.1 dBm. The power radiated mitigation method of the helix loop reduces the power radiated from the two loop system down to -98.72 dBm.
ContributorsMoreno, Fernando (Author) / Diaz, Rodolfo (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2015
Description
Nonlinear responses in the dynamics of climate system could be triggered by small change of forcing. Interactions between different components of Earth’s climate system are believed to cause abrupt and catastrophic transitions, of which anthropogenic forcing is a major and the most irreversible driver. Meantime, in the face of global climate change, extreme climatic events, such as extreme precipitations, heatwaves, droughts, etc., are projected to be more frequent, more intense, and longer in duration. These nonlinear responses in climate dynamics from tipping points to extreme events pose serious threats to human society on a large scale. Understanding the physical mechanisms behind them has potential to reduce related risks through different ways. The overarching objective of this dissertation is to quantify complex interactions, detect tipping points, and explore propagations of extreme events in the hydroclimate system from a new structure-based perspective, by integrating climate dynamics, causal inference, network theory, spectral analysis, and machine learning. More specifically, a network-based framework is developed to find responses of hydroclimate system to potential critical transitions in climate. Results show that system-based early warning signals towards tipping points can be located successfully, demonstrated by enhanced connections in the network topology. To further evaluate the long-term nonlinear interactions among the U.S. climate regions, causality inference is introduced and directed complex networks are constructed from climatology records over one century. Causality networks reveal that the Ohio valley region acts as a regional gateway and mediator to the moisture transport and thermal transfer in the U.S. Furthermore, it is found that cross-regional causality variability manifests intrinsic frequency ranging from interannual to interdecadal scales, and those frequencies are associated with the physics of climate oscillations. Besides the long-term climatology, this dissertation also aims to explore extreme events from the system-dynamic perspective, especially the contributions of human-induced activities to propagation of extreme heatwaves in the U.S. cities. Results suggest that there are long-range teleconnections among the U.S. cities and supernodes in heatwave spreading. Findings also confirm that anthropogenic activities contribute to extreme heatwaves by the fact that causality during heatwaves is positively associated with population in megacities.
ContributorsYang, Xueli (Author) / Yang, Zhihua (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Li, Qi (Committee member) / Xu, Tianfang (Committee member) / Zeng, Ruijie (Committee member) / Arizona State University (Publisher)
Created2023