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- All Subjects: engineering
- Creators: Bakkaloglu, Bertan
- Creators: Liu, Yongming
Description
Pulse Density Modulation- (PDM-) based class-D amplifiers can reduce non-linearity and tonal content due to carrier signal in Pulse Width Modulation - (PWM-) based amplifiers. However, their low-voltage analog implementations also require a linear- loop filter and a quantizer. A PDM-based class-D audio amplifier using a frequency-domain quantization is presented in this paper. The digital-intensive frequency domain approach achieves high linearity under low-supply regimes. An analog comparator and a single-bit quantizer are replaced with a Current-Controlled Oscillator- (ICO-) based frequency discriminator. By using the ICO as a phase integrator, a third-order noise shaping is achieved using only two analog integrators. A single-loop, singlebit class-D audio amplifier is presented with an H-bridge switching power stage, which is designed and fabricated on a 0.18 um CMOS process, with 6 layers of metal achieving a total harmonic distortion plus noise (THD+N) of 0.065% and a peak power efficiency of 80% while driving a 4-ohms loudspeaker load. The amplifier can deliver the output power of 280 mW.
ContributorsLee, Junghan (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kiaei, Sayfe (Committee member) / Ozev, Sule (Committee member) / Song, Hongjiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT To meet stringent market demands, manufacturers must produce Radio Frequency (RF) transceivers that provide wireless communication between electronic components used in consumer products at extremely low cost. Semiconductor manufacturers are in a steady race to increase integration levels through advanced system-on-chip (SoC) technology. The testing costs of these devices tend to increase with higher integration levels. As the integration levels increase and the devices get faster, the need for high-calibre low cost test equipment become highly dominant. However testing the overall system becomes harder and more expensive. Traditionally, the transceiver system is tested in two steps utilizing high-calibre RF instrumentation and mixed-signal testers, with separate measurement setups for transmitter and receiver paths. Impairments in the RF front-end, such as the I/Q gain and phase imbalance and nonlinearity, severely affect the performance of the device. The transceiver needs to be characterized in terms of these impairments in order to guarantee good performance and specification requirements. The motivation factor for this thesis is to come up with a low cost and computationally simple extraction technique of these impairments. In the proposed extraction technique, the mapping between transmitter input signals and receiver output signals are used to extract the impairment and nonlinearity parameters. This is done with the help of detailed mathematical modeling of the transceiver. While the overall behavior is nonlinear, both linear and nonlinear models to be used under different test setups are developed. A two step extraction technique has been proposed in this work. The extraction of system parameters is performed by using the mathematical model developed along with a genetic algorithm implemented in MATLAB. The technique yields good extraction results with reasonable error. It uses simple mathematical operation which makes the extraction fast and computationally simple when compared to other existing techniques such as traditional two step dedicated approach, Nonlinear Solver (NLS) approach, etc. It employs frequency domain analysis of low frequency input and output signals, over cumbersome time domain computations. Thus a test method, including detailed behavioral modeling of the transceiver, appropriate test signal design along with a simple algorithm for extraction is presented.
ContributorsSreenivassan, Aiswariya (Author) / Ozev, Sule (Thesis advisor) / Kiaei, Sayfe (Committee member) / Bakkaloglu, Bertan (Committee member) / Arizona State University (Publisher)
Created2011
Description
The partially-depleted (PD) silicon Metal Semiconductor Field Effect Transistor (MESFET) is becoming more and more attractive for analog and RF applications due to its high breakdown voltage. Compared to conventional CMOS high voltage transistors, the silicon MESFET can be fabricated in commercial standard Silicon-on-Insulator (SOI) CMOS foundries without any change to the process. The transition frequency of the device is demonstrated to be 45GHz, which makes the MESFET suitable for applications in high power RF power amplifier designs. Also, high breakdown voltage and low turn-on resistance make it the ideal choice for switches in the switching regulator designs. One of the anticipated applications of the MESFET is for the pass device for a low dropout linear regulator. Conventional NMOS and PMOS linear regulators suffer from high dropout voltage, low bandwidth and poor stability issues. In contrast, the N-MESFET pass transistor can provide an ultra-low dropout voltage and high bandwidth without the need for an external compensation capacitor to ensure stability. In this thesis, the design theory and problems of the conventional linear regulators are discussed. N-MESFET low dropout regulators are evaluated and characterized. The error amplifier used a folded cascode architecture with gain boosting. The source follower topology is utilized as the buffer to sink the gate leakage current from the MESFET. A shunt-feedback transistor is added to reduce the output impedance and provide the current adaptively. Measurement results show that the dropout voltage is less than 150 mV for a 1A load current at 1.8V output. Radiation measurements were done for discrete MESFET and fully integrated LDO regulators, which demonstrate their radiation tolerance ability for aerospace applications.
ContributorsChen, Bo (Author) / Thornton, Trevor (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Reductive dechlorination by members of the bacterial genus Dehalococcoides is a common and cost-effective avenue for in situ bioremediation of sites contaminated with the chlorinated solvents, trichloroethene (TCE) and perchloroethene (PCE). The overarching goal of my research was to address some of the challenges associated with bioremediation timeframes by improving the rates of reductive dechlorination and the growth of Dehalococcoides in mixed communities. Biostimulation of contaminated sites or microcosms with electron donor fails to consistently promote dechlorination of PCE/TCE beyond cis-dichloroethene (cis-DCE), even when the presence of Dehalococcoides is confirmed. Supported by data from microcosm experiments, I showed that the stalling at cis-DCE is due a H2 competition in which components of the soil or sediment serve as electron acceptors for competing microorganisms. However, once competition was minimized by providing selective enrichment techniques, I illustrated how to obtain both fast rates and high-density Dehalococcoides using three distinct enrichment cultures. Having achieved a heightened awareness of the fierce competition for electron donor, I then identified bicarbonate (HCO3-) as a potential H2 sink for reductive dechlorination. HCO3- is the natural buffer in groundwater but also the electron acceptor for hydrogenotrophic methanogens and homoacetogens, two microbial groups commonly encountered with Dehalococcoides. By testing a range of concentrations in batch experiments, I showed that methanogens are favored at low HCO3 and homoacetogens at high HCO3-. The high HCO3- concentrations increased the H2 demand which negatively affected the rates and extent of dechlorination. By applying the gained knowledge on microbial community management, I ran the first successful continuous stirred-tank reactor (CSTR) at a 3-d hydraulic retention time for cultivation of dechlorinating cultures. I demonstrated that using carefully selected conditions in a CSTR, cultivation of Dehalococcoides at short retention times is feasible, resulting in robust cultures capable of fast dechlorination. Lastly, I provide a systematic insight into the effect of high ammonia on communities involved in dechlorination of chloroethenes. This work documents the potential use of landfill leachate as a substrate for dechlorination and an increased tolerance of Dehalococcoides to high ammonia concentrations (2 g L-1 NH4+-N) without loss of the ability to dechlorinate TCE to ethene.
ContributorsDelgado, Anca Georgiana (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Cadillo-Quiroz, Hinsby (Committee member) / Halden, Rolf U. (Committee member) / Rittmann, Bruce E. (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT Ongoing research into wireless transceivers in the 60 GHz band is required to address the demand for high data rate communications systems at a frequency where signal propagation is challenging even over short ranges. This thesis proposes a mixer architecture in Complementary Metal Oxide Semiconductor (CMOS) technology that uses a voltage controlled oscillator (VCO) operating at a fractional multiple of the desired output signal. The proposed topology is different from conventional subharmonic mixing in that the oscillator phase generation circuitry usually required for such a circuit is unnecessary. Analysis and simulations are performed on the proposed mixer circuit in an IBM 90 nm RF process on a 1.2 V supply. A typical RF transmitter system is considered in determining the block requirements needed for the mixer to meet the IEEE 802.11ad 60 GHz Draft Physical Layer Specification. The proposed circuit has a conversion loss of 21 dB at 60 GHz with a 5 dBm LO power at 20 GHz. Input-referred third-order intercept point (IIP3) is 2.93 dBm. The gain and linearity of the proposed mixer are sufficient for Orthogonal Frequency Division Multiplexing (OFDM) modulation at 60 GHz with a transmitted data rate of over 4 Gbps.
ContributorsMartino, Todd Jeffrey (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Aberle, James T., 1961- (Committee member) / Arizona State University (Publisher)
Created2010
Description
The constant scaling of supply voltages in state-of-the-art CMOS processes has led to severe limitations for many analog circuit applications. Some CMOS processes have addressed this issue by adding high voltage MOSFETs to their process. Although it can be a completely viable solution, it usually requires a changing of the process flow or adding additional steps, which in turn, leads to an increase in fabrication costs. Si-MESFETs (silicon-metal-semiconductor-field-effect-transistors) from Arizona State University (ASU) on the other hand, have an inherent high voltage capability and can be added to any silicon-on-insulator (SOI) or silicon-on-sapphire (SOS) CMOS process free of cost. This has been proved at five different commercial foundries on technologies ranging from 0.5 to 0.15 μm. Another critical issue facing CMOS processes on insulated substrates is the scaling of the thin silicon channel. Consequently, the future direction of SOI/SOS CMOS transistors may trend away from partially depleted (PD) transistors and towards fully depleted (FD) devices. FD-CMOS are already being implemented in multiple applications due to their very low power capability. Since the FD-CMOS market only figures to grow, it is appropriate that MESFETs also be developed for these processes. The beginning of this thesis will focus on the device aspects of both PD and FD-MESFETs including their layout structure, DC and RF characteristics, and breakdown voltage. The second half will then shift the focus towards implementing both types of MESFETs in an analog circuit application. Aside from their high breakdown ability, MESFETs also feature depletion mode operation, easy to adjust but well controlled threshold voltages, and fT's up to 45 GHz. Those unique characteristics can allow certain designs that were previously difficult to implement or prohibitively expensive using conventional technologies to now be achieved. One such application which benefits is low dropout regulators (LDO). By utilizing an n-channel MESFET as the pass transistor, a LDO featuring very low dropout voltage, fast transient response, and stable operation can be achieved without an external capacitance. With the focus of this thesis being MESFET based LDOs, the device discussion will be mostly tailored towards optimally designing MESFETs for this particular application.
ContributorsLepkowski, William (Author) / Thornton, Trevor (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Goryll, Michael (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2010
Description
This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.
ContributorsHensberry, Kevin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Structural/system health monitoring (SHM) and prognostic health management (PHM) are vital techniques to ensure engineering system reliability and safety during the service. As multi-functionality and enhanced performance are in demand, modern engineering systems including aerospace, mechanical, and civil applications have become more complex. The constituent and architectural complexity, and multisource sensing sources in modern engineering systems may limit the monitoring capabilities of conventional approaches and require more advanced SHM/PHM techniques. Therefore, a hybrid methodology that incorporates information fusion, nondestructive evaluation (NDE), machine learning (ML), and statistical analysis is needed for more effective damage diagnosis/prognosis and system safety management.This dissertation presents an automated aviation health management technique to enable proactive safety management for both aircraft and national airspace system (NAS). A real-time, data-driven aircraft safety monitoring technique using ML models and statistical models is developed to enable an early-stage upset detection capability, which can improve pilot’s situational awareness and provide a sufficient safety margin. The detection accuracy and computational efficiency of the developed monitoring techniques is validated using commercial unlabeled flight data recorder (FDR) and reported accident FDR dataset. A stochastic post-upset prediction framework is developed using a high-fidelity flight dynamics model to predict the post-impacts in both aircraft and air traffic system. Stall upset scenarios that are most likely occurred during loss of control in-flight (LOC-I) operation are investigated, and stochastic flight envelopes and risk region are predicted to quantify their severities.
In addition, a robust, automatic damage diagnosis technique using ultrasonic Lamb waves and ML models is developed to effectively detect and classify fatigue damage modes in composite structures. The dispersion and propagation characteristics of the Lamb waves in a composite plate are investigated. A deep autoencoder-based diagnosis technique is proposed to detect fatigue damage using anomaly detection approach and automatically extract damage sensitive features from the waves. The patterns in the features are then further analyzed using outlier detection approach to classify the fatigue damage modes. The developed diagnosis technique is validated through an in-situ fatigue tests with periodic active sensing.
The developed techniques in this research are expected to be integrated with the existing safety strategies to enhance decision making process for improving engineering system safety without affecting the system’s functions.
ContributorsLee, Hyunseong (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Fard, Masoud Yekani (Committee member) / Tang, Pingbo (Committee member) / Campbell, Angela (Committee member) / Arizona State University (Publisher)
Created2021
Description
National Airspace Systems (NAS) are complex cyber-physical systems that require swift air traffic management (ATM) to ensure flight safety and efficiency. With the surging demand for air travel and the increasing intricacy of aviation systems, the need for advanced technologies to support air traffic management and air traffic control (ATC) service has become more crucial than ever. Data-driven models or artificial intelligence (AI) have been conceptually investigated by various parties and shown immense potential, especially when provided with a vast volume of real-world data. These data include traffic information, weather contours, operational reports, terrain information, flight procedures, and aviation regulations. Data-driven models learn from historical experiences and observations and provide expeditious recommendations and decision support for various operation tasks, directly contributing to the digital transformation in aviation. This dissertation reports several research studies covering different aspects of air traffic management and ATC service utilizing data-driven modeling, which are validated using real-world big data (flight tracks, flight events, convective weather, workload probes). These studies encompass a range of topics, including trajectory recommendations, weather studies, landing operations, and aviation human factors. Specifically, the topics explored are (i) trajectory recommendations under weather conditions, which examine the impact of convective weather on last on-file flight plans and provide calibrated trajectories based on convective weather; (ii) multi-aircraft trajectory predictions, which study the intention of multiple mid-air aircraft in the near-terminal airspace and provide trajectory predictions; (iii) flight scheduling operations, which involve probabilistic machine learning-enhanced optimization algorithms for robust and efficient aircraft landing sequencing; (iv) aviation human factors, which predict air traffic controller workload level from flight traffic data with conformalized graph neural network. The uncertainties associated with these studies are given special attention and addressed through Bayesian/probabilistic machine learning. Finally, discussions on high-level AI-enabled ATM research directions are provided, hoping to extend the proposed studies in the future. This dissertation demonstrates that data-driven modeling has great potential for aviation digital twins, revolutionizing the aviation decision-making process and enhancing the safety and efficiency of ATM. Moreover, these research directions are not merely add-ons to existing aviation practices but also contribute to the future of transportation, particularly in the development of autonomous systems.
ContributorsPang, Yutian (Author) / Liu, Yongming (Thesis advisor) / Yan, Hao (Committee member) / Zhuang, Houlong (Committee member) / Marvi, Hamid (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2023
Description
The design of energy absorbing structures is driven by application specific requirements like the amount of energy to be absorbed, maximum transmitted stress that is permissible, stroke length, and available enclosing space. Cellular structures like foams are commonly leveraged in nature for energy absorption and have also found use in engineering applications. With the possibility of manufacturing complex cellular shapes using additive manufacturing technologies, there is an opportunity to explore new topologies that improve energy absorption performance. This thesis aims to systematically understand the relationships between four key elements: (i) unit cell topology, (ii) material composition, (iii) relative density, and (iv) fields; and energy absorption behavior, and then leverage this understanding to develop, implement and validate a methodology to design the ideal cellular structure energy absorber. After a review of the literature in the domain of additively manufactured cellular materials for energy absorption, results from quasi-static compression of six cellular structures (hexagonal honeycomb, auxetic and Voronoi lattice, and diamond, Gyroid, and Schwarz-P) manufactured out of AlSi10Mg and Nylon-12. These cellular structures were compared to each other in the context of four design-relevant metrics to understand the influence of cell design on the deformation and failure behavior. Three new and revised metrics for energy absorption were proposed to enable more meaningful comparisons and subsequent design selection. Triply Periodic Minimal Surface (TPMS) structures were found to have the most promising overall performance and formed the basis for the numerical investigation of the effect of fields on the energy absorption performance of TPMS structures. A continuum shell-based methodology was developed to analyze the large deformation behavior of field-driven variable thickness TPMS structures and validated against experimental data. A range of analytical and stochastic fields were then evaluated that modified the TPMS structure, some of which were found to be effective in enhancing energy absorption behavior in the structures while retaining the same relative density. Combining findings from studies on the role of cell geometry, composition, relative density, and fields, this thesis concludes with the development of a design framework that can enable the formulation of cellular material energy absorbers with idealized behavior.
ContributorsShinde, Mandar (Author) / Bhate, Dhruv (Thesis advisor) / Peralta, Pedro (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023