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- All Subjects: engineering
- Creators: Mignolet, Marc
Description
High Pressure Superheater 1 (HPSH1) is the first heat exchange tube bank inside the Heat Recovery Steam Generator (HRSG) to encounter exhaust flue gas from the gas turbine of a Combined Cycle Power Plant. Steam flowing through the HPSH1 gains heat from the flue gas prior to entering the steam turbine. During cold start-ups, rapid temperature changes in operating condition give rise to significant temperature gradients in the thick-walled components of HPSH1 (manifolds, links, and headers). These temperature gradients produce thermal-structural stresses in the components. The resulting high cycle fatigue is a major concern as this can lead to premature failure of the components. The main objective of this project was to address the thermal-structural stress field induced in HPSH1 during a typical cold start-up transient. To this end, computational fluid dynamics (CFD) was used to carry out the thermal-fluid analysis of HPSH1. The calculated temperature distributions in the component walls were the primary inputs for the finite element (FEA) model that performed structural analysis. Thermal-structural analysis was initially carried out at full-load steady state condition in order to gain confidence in the CFD and FEA methodologies. Results of the full-load steady state thermal-fluid analysis were found in agreement with the temperature values measured at specific locations on the outer surfaces of the inlet links and outlet manifold. It was found from the subsequent structural analysis that peak effective stresses were located at the connecting regions of the components and were well below the allowed stress values. Higher temperature differences were observed between the thick-walled HPSH1 components during the cold start-up transient as compared to the full-load steady state operating condition. This was because of the rapid temperature changes that occurred, especially in the steam temperature at the HPSH1 entry, and the different rates of heating or cooling for components with different wall thicknesses. Results of the transient thermal-fluid analysis will be used in future to perform structural analysis of the HPSH1. The developed CFD and FEA models are capable of analyzing various other transients (e.g., hot start-up and shut-down) and determine their influence on the durability of plant components.
ContributorsHardeep Singh (Author) / Roy, Ramendra P. (Thesis advisor) / Lee, Taewoo (Thesis advisor) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation presents methods for addressing research problems that currently can only adequately be solved using Quality Reliability Engineering (QRE) approaches especially accelerated life testing (ALT) of electronic printed wiring boards with applications to avionics circuit boards. The methods presented in this research are generally applicable to circuit boards, but the data generated and their analysis is for high performance avionics. Avionics equipment typically requires 20 years expected life by aircraft equipment manufacturers and therefore ALT is the only practical way of performing life test estimates. Both thermal and vibration ALT induced failure are performed and analyzed to resolve industry questions relating to the introduction of lead-free solder product and processes into high reliability avionics. In chapter 2, thermal ALT using an industry standard failure machine implementing Interconnect Stress Test (IST) that simulates circuit board life data is compared to real production failure data by likelihood ratio tests to arrive at a mechanical theory. This mechanical theory results in a statistically equivalent energy bound such that failure distributions below a specific energy level are considered to be from the same distribution thus allowing testers to quantify parameter setting in IST prior to life testing. In chapter 3, vibration ALT comparing tin-lead and lead-free circuit board solder designs involves the use of the likelihood ratio (LR) test to assess both complete failure data and S-N curves to present methods for analyzing data. Failure data is analyzed using Regression and two-way analysis of variance (ANOVA) and reconciled with the LR test results that indicating that a costly aging pre-process may be eliminated in certain cases. In chapter 4, vibration ALT for side-by-side tin-lead and lead-free solder black box designs are life tested. Commercial models from strain data do not exist at the low levels associated with life testing and need to be developed because testing performed and presented here indicate that both tin-lead and lead-free solders are similar. In addition, earlier failures due to vibration like connector failure modes will occur before solder interconnect failures.
ContributorsJuarez, Joseph Moses (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie M. (Thesis advisor) / Gel, Esma (Committee member) / Mignolet, Marc (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2012
Description
The stability of nanocrystalline microstructural features allows structural materials to be synthesized and tested in ways that have heretofore been pursued only on a limited basis, especially under dynamic loading combined with temperature effects. Thus, a recently developed, stable nanocrystalline alloy is analyzed here for quasi-static (<100 s-1) and dynamic loading (103 to 104 s-1) under uniaxial compression and tension at multiple temperatures ranging from 298-1073 K. After mechanical tests, microstructures are analyzed and possible deformation mechanisms are proposed. Following this, strain and strain rate history effects on mechanical behavior are analyzed using a combination of quasi-static and dynamic strain rate Bauschinger testing. The stable nanocrystalline material is found to exhibit limited flow stress increase with increasing strain rate as compared to that of both pure, coarse grained and nanocrystalline Cu. Further, the material microstructural features, which includes Ta nano-dispersions, is seen to pin dislocation at quasi-static strain rates, but the deformation becomes dominated by twin nucleation at high strain rates. These twins are pinned from further growth past nucleation by the Ta nano-dispersions. Testing of thermal and load history effects on the mechanical behavior reveals that when thermal energy is increased beyond 200 °C, an upturn in flow stress is present at strain rates below 104 s-1. However, in this study, this simple assumption, established 50-years ago, is shown to break-down when the average grain size and microstructural length-scale is decreased and stabilized below 100nm. This divergent strain-rate behavior is attributed to a unique microstructure that alters slip-processes and their interactions with phonons; thus enabling materials response with a constant flow-stress even at extreme conditions. Hence, the present study provides a pathway for designing and synthesizing a new-level of tough and high-energy absorbing materials.
ContributorsTurnage, Scott Andrew (Author) / Solanki, Kiran N (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Peralta, Pedro (Committee member) / Darling, Kristopher A (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2017
Description
With the growing penetration of plug-in electric vehicles (PEVs), the impact of the PEV charging brought to the utility grid draws more and more attention. This thesis focused on the optimization of a home energy management system (HEMS) with the presence of PEVs. For a household microgrid with photovoltaic (PV) panels and PEVs, a HEMS using model predictive control (MPC) is designed to achieve the optimal PEV charging. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed. Furthermore, the hardware development of a microgrid prototype is also described in this thesis.
ContributorsZhao, Yue (Author) / Chen, Yan (Thesis advisor) / Johnson, Nathan (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
Description
The concept of the microgrid is widely studied and explored in both academic and industrial societies. The microgrid is a power system with distributed generations and loads, which is intentionally planned and can be disconnected from the main utility grid. Nowadays, various distributed power generations (wind resource, photovoltaic resource, etc.) are emerging to be significant power sources of the microgrid.
This thesis focuses on the system structure of Photovoltaics (PV)-dominated microgrid, precisely modeling and stability analysis of the specific system. The grid-connected mode microgrid is considered, and system control objectives are: PV panel is working at the maximum power point (MPP), the DC link voltage is regulated at a desired value, and the grid side current is also controlled in phase with grid voltage. To simulate the real circuits of the whole system with high fidelity instead of doing real experiments, PLECS software is applied to construct the detailed model in chapter 2. Meanwhile, a Simulink mathematical model of the microgrid system is developed in chapter 3 for faster simulation and energy management analysis. Simulation results of both the PLECS model and Simulink model are matched with the expectations. Next chapter talks about state space models of different power stages for stability analysis utilization. Finally, the large signal stability analysis of a grid-connected inverter, which is based on cascaded control of both DC link voltage and grid side current is discussed. The large signal stability analysis presented in this thesis is mainly focused on the impact of the inductor and capacitor capacity and the controller parameters on the DC link stability region. A dynamic model with the cascaded control logic is proposed. One Lyapunov large-signal stability analysis tool is applied to derive the domain of attraction, which is the asymptotic stability region. Results show that both the DC side capacitor and the inductor of grid side filter can significantly influence the stability region of the DC link voltage. PLECS simulation models developed for the microgrid system are applied to verify the stability regions estimated from the Lyapunov large signal analysis method.
This thesis focuses on the system structure of Photovoltaics (PV)-dominated microgrid, precisely modeling and stability analysis of the specific system. The grid-connected mode microgrid is considered, and system control objectives are: PV panel is working at the maximum power point (MPP), the DC link voltage is regulated at a desired value, and the grid side current is also controlled in phase with grid voltage. To simulate the real circuits of the whole system with high fidelity instead of doing real experiments, PLECS software is applied to construct the detailed model in chapter 2. Meanwhile, a Simulink mathematical model of the microgrid system is developed in chapter 3 for faster simulation and energy management analysis. Simulation results of both the PLECS model and Simulink model are matched with the expectations. Next chapter talks about state space models of different power stages for stability analysis utilization. Finally, the large signal stability analysis of a grid-connected inverter, which is based on cascaded control of both DC link voltage and grid side current is discussed. The large signal stability analysis presented in this thesis is mainly focused on the impact of the inductor and capacitor capacity and the controller parameters on the DC link stability region. A dynamic model with the cascaded control logic is proposed. One Lyapunov large-signal stability analysis tool is applied to derive the domain of attraction, which is the asymptotic stability region. Results show that both the DC side capacitor and the inductor of grid side filter can significantly influence the stability region of the DC link voltage. PLECS simulation models developed for the microgrid system are applied to verify the stability regions estimated from the Lyapunov large signal analysis method.
ContributorsXu, Hongru (Author) / Chen, Yan (Thesis advisor) / Johnson, Nathan (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
Description
The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS). The power electronic converters are used to couple the motor with the battery stack. Including a DC/DC converter in the powertrain module is favored as it adds an additional degree of freedom to achieve flexibility in optimizing the battery module and inverter independently. However, it is essential that the converter is rated for high peak power and can maintain high efficiency while operating over a wide range of load conditions to not compromise on system efficiency. Additionally, the converter must strictly adhere to all automotive standards.
Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.
Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.
Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
ContributorsMullangi Chenchu, Hemanth (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
Description
This paper describes an effort to bring wing structural stiffness and aeroelastic considerations early in the conceptual design process with an automated tool. Stiffness and aeroelasticity can be well represented with a stochastic model during conceptual design because of the high level of uncertainty and variability in wing non-structural mass such as fuel loading and control surfaces. To accomplish this, an improvement is made to existing design tools utilizing rule based automated design to generate wing torque box geometry from a specific wing outer mold-line. Simple analysis on deflection and inferred stiffness shows how early conceptual design choices can strongly impact the stiffness of the structure. The impacts of design choices and how the buckling constraints drive structural weight in particular examples are discussed. The model is then carried further to include a finite element model (FEM) to analyze resulting mode shapes and frequencies for use in aeroelastic analysis. The natural frequencies of several selected wing torque boxes across a range of loading cases are compared.
ContributorsMiskin, Daniel L (Author) / Takahashi, Timothy T (Thesis advisor) / Mignolet, Marc (Committee member) / Murthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2018
Description
Over the years, the growing penetration of renewable energy into the electricity market has resulted in a significant change in the electricity market price. This change makes the existing forecasting method prone to error, decreasing the economic benefits. Hence, more precise forecasting methods need to be developed. This paper starts with a survey and benchmark of existing machine learning approaches for forecasting the real-time market (RTM) price. While these methods provide sufficient modeling capability via supervised learning, their accuracy is still limited due to the single data source, e.g., historical price information only. In this paper, a novel two-stage supervised learning approach is proposed by diversifying the data sources such as highly correlated power data. This idea is inspired by the recent load forecasting methods that have shown extremely well performances. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules. The first one is the mapping between the historical wind power and the historical price. The second is the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the first learned mapping between power and price. Additionally, we observed that it is not the more training data the better, leading to our validation steps to quantify the best training intervals for different datasets. We conduct comparisons of numerical results between existing methods and the proposed methods based on datasets from the Electric Reliability Council of Texas (ERCOT). For each machine learning step, we examine different learning methods, such as polynomial regression, support vector regression, neural network, and deep neural network. The results show that the proposed method is significantly better than existing approaches when renewables are involved.
ContributorsLuo, Shuman (Author) / Weng, Yang (Thesis advisor) / Lei, Qin (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2019
Description
Robotic swarms can potentially perform complicated tasks such as exploration and mapping at large space and time scales in a parallel and robust fashion. This thesis presents strategies for mapping environmental features of interest – specifically obstacles, collision-free paths, generating a metric map and estimating scalar density fields– in an unknown domain using data obtained by a swarm of resource-constrained robots. First, an approach was developed for mapping a single obstacle using a swarm of point-mass robots with both directed and random motion. The swarm population dynamics are modeled by a set of advection-diffusion-reaction partial differential equations (PDEs) in which a spatially-dependent indicator function marks the presence or absence of the obstacle in the domain. The indicator function is estimated by solving an optimization problem with PDEs as constraints. Second, a methodology for constructing a topological map of an unknown environment was proposed, which indicates collision-free paths for navigation, from data collected by a swarm of finite-sized robots. As an initial step, the number of topological features in the domain was quantified by applying tools from algebraic topology, to a probability function over the explored region that indicates the presence of obstacles. A topological map of the domain is then generated using a graph-based wave propagation algorithm. This approach is further extended, enabling the technique to construct a metric map of an unknown domain with obstacles using uncertain position data collected by a swarm of resource-constrained robots, filtered using intensity measurements of an external signal. Next, a distributed method was developed to construct the occupancy grid map of an unknown environment using a swarm of inexpensive robots or mobile sensors with limited communication. In addition to this, an exploration strategy which combines information theoretic ideas with Levy walks was also proposed. Finally, the problem of reconstructing a two-dimensional scalar field using observations from a subset of a sensor network in which each node communicates its local measurements to its neighboring nodes was addressed. This problem reduces to estimating the initial condition of a large interconnected system with first-order linear dynamics, which can be solved as an optimization problem.
ContributorsRamachandran, Ragesh Kumar (Author) / Berman, Spring M (Thesis advisor) / Mignolet, Marc (Committee member) / Artemiadis, Panagiotis (Committee member) / Marvi, Hamid (Committee member) / Robinson, Michael (Committee member) / Arizona State University (Publisher)
Created2018
Description
Switching surges are a common type of phenomenon that occur on any sort of power system network. These are more pronounced on long transmission lines and in high voltage substations. The problem with switching surges is encountered when a lot of power is transmitted across a transmission line
etwork, typically from a concentrated generation node to a concentrated load. The problem becomes significantly worse when the transmission line is long and when the voltage levels are high, typically above 400 kV. These overvoltage transients occur following any type of switching action such as breaker operation, fault occurrence/clearance and energization, and they pose a very real danger to weakly interconnected systems. At EHV levels, the insulation coordination of such lines is mainly dictated by the peak level of switching surges, the most dangerous of which include three phase line energization and single-phase reclosing. Switching surges can depend on a number of independent and inter-dependent factors like voltage level, line length, tower construction, location along the line, and presence of other equipment like shunt/series reactors and capacitors.
This project discusses the approaches taken and methods applied to observe and tackle the problems associated with switching surges on a long transmission line. A detailed discussion pertaining to different aspects of switching surges and their effects is presented with results from various studies published in IEEE journals and conference papers. Then a series of simulations are presented to determine an arrangement of substation equipment with respect to incoming transmission lines; that correspond to the lowest surge levels at that substation.
etwork, typically from a concentrated generation node to a concentrated load. The problem becomes significantly worse when the transmission line is long and when the voltage levels are high, typically above 400 kV. These overvoltage transients occur following any type of switching action such as breaker operation, fault occurrence/clearance and energization, and they pose a very real danger to weakly interconnected systems. At EHV levels, the insulation coordination of such lines is mainly dictated by the peak level of switching surges, the most dangerous of which include three phase line energization and single-phase reclosing. Switching surges can depend on a number of independent and inter-dependent factors like voltage level, line length, tower construction, location along the line, and presence of other equipment like shunt/series reactors and capacitors.
This project discusses the approaches taken and methods applied to observe and tackle the problems associated with switching surges on a long transmission line. A detailed discussion pertaining to different aspects of switching surges and their effects is presented with results from various studies published in IEEE journals and conference papers. Then a series of simulations are presented to determine an arrangement of substation equipment with respect to incoming transmission lines; that correspond to the lowest surge levels at that substation.
ContributorsShaikh, Mohammed Mubashir (Author) / Qin, Jiangchao (Thesis advisor) / Heydt, Gerald T (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018