Matching Items (70)
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- All Subjects: Mechanical Engineering
- Creators: Phelan, Patrick
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
Description
Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.
ContributorsKrishnamurthy, Raghavendra (Author) / Calhoun, Ronald J (Thesis advisor) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Fraser, Matthew (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Locomotion of microorganisms is commonly observed in nature and some aspects of their motion can be replicated by synthetic motors. Synthetic motors rely on a variety of propulsion mechanisms including auto-diffusiophoresis, auto-electrophoresis, and bubble generation. Regardless of the source of the locomotion, the motion of any motor can be characterized by the translational and rotational velocity and effective diffusivity. In a uniform environment the long-time motion of a motor can be fully characterized by the effective diffusivity. In this work it is shown that when motors possess both translational and rotational velocity the motor transitions from a short-time diffusivity to a long-time diffusivity at a time of pi/w. The short-time diffusivities are two to three orders of magnitude larger than the diffusivity of a Brownian sphere of the same size, increase linearly with concentration, and scale as v^2/2w. The measured long-time diffusivities are five times lower than the short-time diffusivities, scale as v^2/{2Dr [1 + (w/Dr )^2]}, and exhibit a maximum as a function of concentration. The variation of a colloid's velocity and effective diffusivity to its local environment (e.g. fuel concentration) suggests that the motors can accumulate in a bounded system, analogous to biological chemokinesis. Chemokinesis of organisms is the non-uniform equilibrium concentration that arises from a bounded random walk of swimming organisms in a chemical concentration gradient. In non-swimming organisms we term this response diffusiokinesis. We show that particles that migrate only by Brownian thermal motion are capable of achieving non-uniform pseudo equilibrium distribution in a diffusivity gradient. The concentration is a result of a bounded random-walk process where at any given time a larger percentage of particles can be found in the regions of low diffusivity than in regions of high diffusivity. Individual particles are not trapped in any given region but at equilibrium the net flux between regions is zero. For Brownian particles the gradient in diffusivity is achieved by creating a viscosity gradient in a microfluidic device. The distribution of the particles is described by the Fokker-Planck equation for variable diffusivity. The strength of the probe concentration gradient is proportional to the strength of the diffusivity gradient and inversely proportional to the mean probe diffusivity in the channel in accordance with the no flux condition at steady state. This suggests that Brownian colloids, natural or synthetic, will concentrate in a bounded system in response to a gradient in diffusivity and that the magnitude of the response is proportional to the magnitude of the gradient in diffusivity divided by the mean diffusivity in the channel.
ContributorsMarine, Nathan Arasmus (Author) / Posner, Jonathan D (Thesis advisor) / Adrian, Ronald J (Committee member) / Frakes, David (Committee member) / Phelan, Patrick E (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Human fingertips contain thousands of specialized mechanoreceptors that enable effortless physical interactions with the environment. Haptic perception capabilities enable grasp and manipulation in the absence of visual feedback, as when reaching into one's pocket or wrapping a belt around oneself. Unfortunately, state-of-the-art artificial tactile sensors and processing algorithms are no match for their biological counterparts. Tactile sensors must not only meet stringent practical specifications for everyday use, but their signals must be processed and interpreted within hundreds of milliseconds. Control of artificial manipulators, ranging from prosthetic hands to bomb defusal robots, requires a constant reliance on visual feedback that is not entirely practical. To address this, we conducted three studies aimed at advancing artificial haptic intelligence. First, we developed a novel, robust, microfluidic tactile sensor skin capable of measuring normal forces on flat or curved surfaces, such as a fingertip. The sensor consists of microchannels in an elastomer filled with a liquid metal alloy. The fluid serves as both electrical interconnects and tunable capacitive sensing units, and enables functionality despite substantial deformation. The second study investigated the use of a commercially-available, multimodal tactile sensor (BioTac sensor, SynTouch) to characterize edge orientation with respect to a body fixed reference frame, such as a fingertip. Trained on data from a robot testbed, a support vector regression model was developed to relate haptic exploration actions to perception of edge orientation. The model performed comparably to humans for estimating edge orientation. Finally, the robot testbed was used to perceive small, finger-sized geometric features. The efficiency and accuracy of different haptic exploratory procedures and supervised learning models were assessed for estimating feature properties such as type (bump, pit), order of curvature (flat, conical, spherical), and size. This study highlights the importance of tactile sensing in situations where other modalities fail, such as when the finger itself blocks line of sight. Insights from this work could be used to advance tactile sensor technology and haptic intelligence for artificial manipulators that improve quality of life, such as prosthetic hands and wheelchair-mounted robotic hands.
ContributorsPonce Wong, Ruben Dario (Author) / Santos, Veronica J (Thesis advisor) / Artemiadis, Panagiotis K (Committee member) / Helms Tillery, Stephen I (Committee member) / Posner, Jonathan D (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Tesla turbo-machinery offers a robust, easily manufactured, extremely versatile prime mover with inherent capabilities making it perhaps the best, if not the only, solution for certain niche applications. The goal of this thesis is not to optimize the performance of the Tesla turbine, but to compare its performance with various working fluids. Theoretical and experimental analyses of a turbine-generator assembly utilizing compressed air, saturated steam and water as the working fluids were performed and are presented in this work. A brief background and explanation of the technology is provided along with potential applications. A theoretical thermodynamic analysis is outlined, resulting in turbine and rotor efficiencies, power outputs and Reynolds numbers calculated for the turbine for various combinations of working fluids and inlet nozzles. The results indicate the turbine is capable of achieving a turbine efficiency of 31.17 ± 3.61% and an estimated rotor efficiency 95 ± 9.32%. These efficiencies are promising considering the numerous losses still present in the current design. Calculation of the Reynolds number provided some capability to determine the flow behavior and how that behavior impacts the performance and efficiency of the Tesla turbine. It was determined that turbulence in the flow is essential to achieving high power outputs and high efficiency. Although the efficiency, after peaking, begins to slightly taper off as the flow becomes increasingly turbulent, the power output maintains a steady linear increase.
ContributorsPeshlakai, Aaron (Author) / Phelan, Patrick (Thesis advisor) / Trimble, Steve (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2012
Description
Multi-touch tablets and smart phones are now widely used in both workplace and consumer settings. Interacting with these devices requires hand and arm movements that are potentially complex and poorly understood. Experimental studies have revealed differences in performance that could potentially be associated with injury risk. However, underlying causes for performance differences are often difficult to identify. For example, many patterns of muscle activity can potentially result in similar behavioral output. Muscle activity is one factor contributing to forces in tissues that could contribute to injury. However, experimental measurements of muscle activity and force for humans are extremely challenging. Models of the musculoskeletal system can be used to make specific estimates of neuromuscular coordination and musculoskeletal forces. However, existing models cannot easily be used to describe complex, multi-finger gestures such as those used for multi-touch human computer interaction (HCI) tasks. We therefore seek to develop a dynamic musculoskeletal simulation capable of estimating internal musculoskeletal loading during multi-touch tasks involving multi digits of the hand, and use the simulation to better understand complex multi-touch and gestural movements, and potentially guide the design of technologies the reduce injury risk. To accomplish these, we focused on three specific tasks. First, we aimed at determining the optimal index finger muscle attachment points within the context of the established, validated OpenSim arm model using measured moment arm data taken from the literature. Second, we aimed at deriving moment arm values from experimentally-measured muscle attachments and using these values to determine muscle-tendon paths for both extrinsic and intrinsic muscles of middle, ring and little fingers. Finally, we aimed at exploring differences in hand muscle activation patterns during zooming and rotating tasks on the tablet computer in twelve subjects. Towards this end, our musculoskeletal hand model will help better address the neuromuscular coordination, safe gesture performance and internal loadings for multi-touch applications.
ContributorsYi, Chong-hwan (Author) / Jindrich, Devin L. (Thesis advisor) / Artemiadis, Panagiotis K. (Thesis advisor) / Phelan, Patrick (Committee member) / Santos, Veronica J. (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2014
Optimization of the implementation of renewable resources in a municipal electric utility in Arizona
Description
A municipal electric utility in Mesa, Arizona with a peak load of approximately 85 megawatts (MW) was analyzed to determine how the implementation of renewable resources (both wind and solar) would affect the overall cost of energy purchased by the utility. The utility currently purchases all of its energy through long term energy supply contracts and does not own any generation assets and so optimization was achieved by minimizing the overall cost of energy while adhering to specific constraints on how much energy the utility could purchase from the short term energy market. Scenarios were analyzed for a five percent and a ten percent penetration of renewable energy in the years 2015 and 2025. Demand Side Management measures (through thermal storage in the City's district cooling system, electric vehicles, and customers' air conditioning improvements) were evaluated to determine if they would mitigate some of the cost increases that resulted from the addition of renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
In the 2015 simulation, wind energy was less expensive than solar to integrate to the supply mix. When five percent of the utility's energy requirements in 2015 are met by wind, this caused a 3.59% increase in the overall cost of energy. When that five percent is met by solar in 2015, it is estimated to cause a 3.62% increase in the overall cost of energy. A mix of wind and solar in 2015 caused a lower increase in the overall cost of energy of 3.57%. At the ten percent implementation level in 2015, solar, wind, and a mix of solar and wind caused increases of 7.28%, 7.51% and 7.27% respectively in the overall cost of energy.
In 2025, at the five percent implementation level, wind and solar caused increases in the overall cost of energy of 3.07% and 2.22% respectively. In 2025, at the ten percent implementation level, wind and solar caused increases in the overall cost of energy of 6.23% and 4.67% respectively.
Demand Side Management reduced the overall cost of energy by approximately 0.6%, mitigating some of the cost increase from adding renewable resources.
ContributorsCadorin, Anthony (Author) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2014
Description
As one of the most promising materials for high capacity electrode in next generation of lithium ion batteries, silicon has attracted a great deal of attention in recent years. Advanced characterization techniques and atomic simulations helped to depict that the lithiation/delithiation of silicon electrode involves processes including large volume change (anisotropic for the initial lithiation of crystal silicon), plastic flow or softening of material dependent on composition, electrochemically driven phase transformation between solid states, anisotropic or isotropic migration of atomic sharp interface, and mass diffusion of lithium atoms. Motivated by the promising prospect of the application and underlying interesting physics, mechanics coupled with multi-physics of silicon electrodes in lithium ion batteries is studied in this dissertation. For silicon electrodes with large size, diffusion controlled kinetics is assumed, and the coupled large deformation and mass transportation is studied. For crystal silicon with small size, interface controlled kinetics is assumed, and anisotropic interface reaction is studied, with a geometry design principle proposed. As a preliminary experimental validation, enhanced lithiation and fracture behavior of silicon pillars via atomic layer coatings and geometry design is studied, with results supporting the geometry design principle we proposed based on our simulations. Through the work documented here, a consistent description and understanding of the behavior of silicon electrode is given at continuum level and some insights for the future development of the silicon electrode are provided.
ContributorsAn, Yonghao (Author) / Jiang, Hanqing (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Phelan, Patrick (Committee member) / Wang, Yinming (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
In this thesis the performance of a Hybrid AC System (HACS) is modeled and optimized. The HACS utilizes solar photovoltaic (PV) panels to help reduce the demand from the utility during peak hours. The system also includes an ice Thermal Energy Storage (TES) tank to accumulate cooling energy during off-peak hours. The AC runs continuously on grid power during off-peak hours to generate cooling for the house and to store thermal energy in the TES. During peak hours, the AC runs on the power supplied from the PV, and cools the house along with the energy stored in the TES. A higher initial cost is expected due to the additional components of the HACS (PV and TES), but a lower operational cost due to higher energy efficiency, energy storage and renewable energy utilization. A house cooled by the HACS will require a smaller size AC unit (about 48% less in the rated capacity), compared to a conventional AC system. To compare the cost effectiveness of the HACS with a regular AC system, time-of-use (TOU) utility rates are considered, as well as the cost of the system components and the annual maintenance. The model shows that the HACS pays back its initial cost of $28k in about 6 years with an 8% APR, and saves about $45k in total cost when compared to a regular AC system that cools the same house for the same period of 6 years.
ContributorsJubran, Sadiq (Author) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2011
Description
A low cost expander, combustor device that takes compressed air, adds thermal energy and then expands the gas to drive an electrical generator is to be designed by modifying an existing reciprocating spark ignition engine. The engine used is the 6.5 hp Briggs and Stratton series 122600 engine. Compressed air that is stored in a tank at a particular pressure will be introduced during the compression stage of the engine cycle to reduce pump work. In the modified design the intake and exhaust valve timings are modified to achieve this process. The time required to fill the combustion chamber with compressed air to the storage pressure immediately before spark and the state of the air with respect to crank angle is modeled numerically using a crank step energy and mass balance model. The results are used to complete the engine cycle analysis based on air standard assumptions and air to fuel ratio of 15 for gasoline. It is found that at the baseline storage conditions (280 psi, 70OF) the modified engine does not meet the imposed constraints of staying below the maximum pressure of the unmodified engine. A new storage pressure of 235 psi is recommended. This only provides a 7.7% increase in thermal efficiency for the same work output. The modification of this engine for this low efficiency gain is not recommended.
ContributorsJoy, Lijin (Author) / Trimble, Steve (Thesis advisor) / Davidson, Joseph (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2011
Description
Processed pyro-gel contains castor oil with solid component of boehmite (Al-OOH). The pyro-gel is synthesized by heat to convert boehmite to gamma-Al2O3 and to a certain extent alpha-Al2O3 nano-particles and castor oil into carbon residue. The effect of heat on pyro-gel is analyzed in a series of experiments using two burning chambers with the initial temperature as the main factor. The obtained temperature distribution profiles are studied and it is observed that the gel behaves very close to the theoretical prediction under heat. The carbon residue with Al2O3 is then processed for twelve hours and then analyzed to obtain the pore distribution of the Al2O3 nano-particles and the relation between the pore volume and the pre-heat temperature is analyzed. The obtained pore distribution shows the pore volume of Al2O3 nano-particles has direct relation to the pre-heat temperature. The experimental process involving the cylindrical reactor is simulated by using a finite rate chemistry eddy-dissipation model in a non-premixed and a porous mesh. The temperature distribution profile of the processed gel for both the meshes is obtained and a comparison is done with the data obtained in the experimental analysis. The temperature distribution obtained from the simulations show they follow a very similar profile to the temperature distribution obtained from experimental analysis, thus confirming the accuracy of both the models. The variation in numerical values between the experimental and simulation analysis is discussed. A physical model is proposed to determine the pore formation based on the temperature distribution obtained from experimental analysis and simulation.
ContributorsSagi, Varun (Author) / Lee, Taewoo (Thesis advisor) / Phelan, Patrick (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2010