451 research outputs found
EXPLORING DEFENSE MECHANISMS: UNRAVELING SOCIAL ANXIETY AND ASIAN-AMERICAN IDENTITY IN TURNING RED MOVIE TRANSCRIPT (2022)
No full textPenelitian ini bertujuan untuk mengeksplorasi bagaimana pengaruh latar belakang identitas dari karakter utama dalam film “Turning Red” memunculkan kecemasan sosial dan bagaimana karakter tersebut mencerminkan mekanisme pertahanan dalam menghadapi kecemasan sosial. Menggunakan teori hibriditas Homi K. Bhabha dan teori kecemasan serta mekanisme pertahanan Sigmund Freud, penulis menganalisis dialog dalam transkrip film untuk mengungkap kompleksitas identitas hibrida Meilin sebagai remaja Asia-Amerika yang diapit oleh dua budaya berbeda. Meilin mengalami kecemasan realistis, neurotic, dan moral akibat tekanan budaya keluarganya dan pengaruh lingkungan Barat. Untuk mengatasi kecemasan, Meilin menunjukkan berbagai mekanisme pertahanan seperti represi, formasi, proyeksi, penyangkalan, identifikasi, sublimasi, dan agresi. Hibriditas menciptakan “ruang ketiga” bagi Meilin untuk bernegosiasi dan berkembang antara dua budaya tersebut menjadi tidak sepenuhnya Asia namun juga tidak sepenuhnya Amerika.
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This research aims to explore how the influence of the identity background of the main character in the film "Turning Red" gives rise to social anxiety and how this character reflects defense mechanisms in dealing with social anxiety. Using Homi K. Bhabha's theory of hybridity and Sigmund Freud's theory of anxiety and defense mechanisms, the author analyzes the dialogue in the film transcript to reveal the complexity of Meilin's hybrid identity as an Asian-American teenager sandwiched between two different cultures. Meilin experiences realistic, neurotic and moral anxiety due to the pressure of her family's culture and the influence of the Western environment. To overcome anxiety, Meilin exhibits various defense mechanisms such as repression, formation, projection, denial, identification, sublimation, and aggression. Hybridity creates a “third space” for Meilin to negotiate and develop between the two cultures to be not fully Asian but also not fully American
Numerical Investigation of Biotransport in a Tumor with Uncertain Material Properties
No full textIn biomedical engineering, it is a challenge to deliver therapeutic agents to the entire tumor region effectively due to its material heterogeneity. Therefore, one basic issue that needs to be resolved is whether there is an efficient way to quantify the effects of structural irregularities on drug delivery in tumors. In this work, different from previous studies, which treat the material property of tumors as a uniform one or a heterogeneous one but with deterministic values, we approximate tumor material properties as random fields, and develop stochastic models to analyze the resultant heterogeneous biotransport. Specifically, the uncertain permeability is modeled as a log-normal random field, and represented by a truncated Karhunen-Loeve (KL) expansion. The uncertain porosity is modeled as a log-normal random variable. On propagating the randomness in the inputs (i.e., permeability and porosity) into the governing partial differential equations, as a result, uncertain flow features such as pressure, velocity and concentration fields can be quantified mathematically. We demonstrate that our stochastic model is an effective representation of the uncertain heterogeneous structure in tumors, and can be used to efficiently quantify the impact of material heterogeneities on drug delivery process in porous media
Improving Vertical Axis Turbine Performance with Active Blade Pitch Control: Mechanism Design and Fundamental Physics Analysis
No full textCompared to their horizontal counterparts, vertical-axis turbines (VATs) have several advantages, such as low manufacturing, installation, operation and maintenance costs, low noise emission, and are less harmful to birds and insects. In this study, we propose to develop active turbine blade pitch control methods to conquer the challenges encountered by the VAT technology. There are many control approaches that offer performance improvements. This thesis explores the potential performance improvements that the constant angle of attack (AoA) control function offers. The constant AoA function was developed to facilitate implementation into a real turbine. To validate the new control approach ANSYS-Fluent was used to simulate the 2D VATs at different Tip Speed Ratios (TSRs) and wind speeds (WS)to better understand the scope of performance improvement of this control. To understand capability of the control, flow physics is studied for different constant AoA control strategies across a wide range of TSR and WS. The individual behavior of a constant AoA case was investigated using the torque coefficient graphs and the instantaneous velocity flow fields. These efforts gave invaluable insight into the fundamental physics that governed the turbine?s performance and how the control affected the fluid. The overall effect that an individual control case had on the performance of the turbine was analyzed using the power coefficient (CP ) graphs. The comparison between the best performance of the control function and that of the no control baseline ranged from an increase in the CP , a measure of energy harvesting efficiency, of 27.4% to 704.0%
PARALLEL P-ADAPTIVE IMPLICIT HIGH-ORDER FLUX RECONSTRUCTION METHODS FOR UNDER-RESOLVED TURBULENT FLOW SIMULATION
No full textA simplified flux reconstruction method, i.e., the compact direct flux reconstruction method, is developed using the compact finite difference approach within the standard element. It can be regarded as a differentiation form of the direct flux reconstruction method. Implicit high-order time integration methods are employed to achieve high-order spatiotemporal accuracy and circumvent the restriction on the time step size. To efficiently solve the nonlinear and linear systems resulting from the high-order discretization, we employ the Newton--Krylov solver as well as the p-multigrid solver. Specifically, the matrix-free implementation of the generalized minimal residual method is employed to significantly reduce memory consumption. The element-Jacobi preconditioner is used for the generalized minimal residual method and it also serves as a smoother for the p-multigrid solver. The impact of the polynomial hierarchy on the convergence speed of the V-cycle p-multigrid solver is discussed to reveal that the polynomial difference between two adjacent levels should be half of the polynomial degree on the finer level. The local preconditioning technique is employed to solve the Navier--Stokes equations at low Mach numbers. The local preconditioning can preserve the accuracy of high-order methods when the Mach number is small and accelerate the convergence of implicit methods. To further increase the efficiency of high-order methods when solving massive turbulent flows, a dynamic p-adaptation method is developed with a dynamic load balancing technique. When the p-adaptive implicit high-order method is applied to under-resolved turbulence simulation, it can significantly decrease the total number of solution points (up to 76%) as well as the run time (up to 70%). Overall, in this work, implicit high-order numerical methods with various acceleration techniques, namely, implicit time stepping, local preconditioning, p-multigrid solver, and p-adaptation, are developed and studied as our endeavor towards the efficient, accurate, and robust simulation of turbulent flows, including low-Mach-number problems
High-fidelity Fluid-structure Interaction Study of the Turbine-based Renewable Energy Harvesting Mechanism
No full textUnderstanding unsteady fluid dynamics is an indispensable step when designing and analyzing the turbine-based renewable energy harvesting mechanism. In this study, we have developed and adopted advanced simulation and analysis tools. Specifically, we have developed high-order CFD methods for moving grids to study FSI problems at low Reynolds numbers; we have adopted commercial software, coupled with user-specific codes, to study complex aero-hydrodynamics from vertical axis wind/water turbines (VAWTs) and offshore wind turbine system. When studying turbine-based renewable energy harvesting, it is challenging to model turbine rotors rotating at relatively high speed. Fast dynamic grid technology is a bottleneck of efficient simulation of rotor dynamics. We have developed a high-order flux reconstruction/correction procedure via reconstruction (FR/CPR) formulation for unsteady flow simulation with dynamic grid algorithms. Specifically, the high-order FR formulation for the Navier-Stokes equations in an arbitrary Lagrangian-Eulerian (ALE) format is developed for numerical simulation on moving domains. A hybrid moving grid algorithm consisting of algebraic grid smoothing and grid regeneration methods is developed to resolve domains with large deformation.
It is challenging to guarantee satisfactory self-starting capability and high-power efficiency simultaneously in a VAWT design. To address this challenge, a new hybrid Darrieus-Modifed-Savonius (HDMS) VAWT is designed and numerically tested using a fluid-structure interaction (FSI) approach based on high-fidelity CFD. A systematic study is conducted to analyze the effects of the moment of inertia, turbine structure, and external load on the self-starting capability and power efficiency under both wind and water condition. In the study under water conditions, the relationship between the power coefficient and Reynolds number is unveiled. Moreover, different configurations of this HDMS VAWT are tested under water conditions. Additionally, we also investigate the performance of our HDMS VAWT in open channel flows to compare its performance with that in single-phase flows.
In traditional offshore Horizontal Axis Wind Turbine (HAWT) foundation design, Morison equation is usually adopted to calculate the force of water acting on the foundation. However, this method can overestimate the force. To reduce the levelized cost of energy (LCOE) of the offshore wind, a comprehensive study of simulating mono-plie foundation under wave conditions of an offshore HAWT is needed. We have conducted a two-phase water-air simulation to quantify hydrodynamics of the water flow over the monopile foundation. This study is then used in a comprehensive aero-hydro-structural analysis of a 5 MW offshore wind turbine system.
In addition, the high-order CFD solver is coupled with a stable and accuracy FSI scheme. Three different FSI problems triggered by vortex induced vibration (VIV) are investigated here, namely zero-mass cylinder oscillation, an oscillating-foil-based energy harvesting mechanism, and a non-linear energy sink (NES). It is found that the high-order partitioned FSI framework can effectively handle those challenging FSI problems
AERODYNAMIC ANALYSIS OF STATIONARY AND FLAPPING WINGS IN UNSTEADY FLOW ENVIRONMENTS AT LOW REYNOLDS NUMBERS
No full textThis thesis investigates nonlinear flow physics of flapping wings in unsteady ambient flow environments at low Reynolds numbers, where most birds, insects, and small unmanned aerial vehicles (UAVs) maneuver or operate, with high-fidelity numerical simulations enabled by high-order accurate computational fluid dynamics (CFD) methods. The first objective of this research is to investigate gust-wing interaction and to unravel the mechanism of gust mitigation with flapping wings. The interaction of a gust with a stationary airfoil produces large undesirable unsteady forces, which exceed the peak static lift coefficient. A simple pitch-down maneuver and oscillating airfoil motion were tested to mitigate the gust. A rapid pitch-down maneuver in response to a gust sometimes exceeds the negative stall angle, causing an inadvertent stall. A step-wise change in the angle of attack, as the gust develops, is shown to be effective at mitigating the negative effects of the gust. However, if the gust continues to grow in magnitude, this strategy may be ineffective. Low amplitude wing oscillations are then tested as a novel method for gust mitigation. Increasing the oscillating airfoil's reduced frequency dominates the gust. The second objective of the research is to examine highly nonlinear flow physics of stationary/flapping wings in unsteady ambient flow environments at low Reynolds numbers. The dependence of a pitching airfoil's thrust on Reynolds and Strouhal numbers is investigated first, and it is discovered that an unsteady flow environment can enhance its thrust production. The thrust scaling law of a pitching airfoil, when operating in highly unsteady flow environments, is extended as a function of Reynolds number, Strouhal number, and turbulence intensity. To quantify the effect of the unsteady flow environment on pitching airfoil thrust production, an effective Reynolds number concept is also introduced. It is also found that moderate freestream turbulence (~5%) can alter the formation of laminar separation bubbles near a stationary wing's leading edge and obtain larger lift coefficients when compared to those in a uniform freestream. This is critical for UAV design and control at low Reynolds numbers as large-scale flow separation can create undesired stall effects over wings at moderate angles of attack due to the weak resistance of unfavorable pressure gradients at low Reynolds numbers. In conclusion, on using high-fidelity numerical simulation tools, this research contributes to novel design and control of future unconventional UAVs by providing key insights into unsteady aerodynamics in highly unstructured real-world flight environments
Catalyst Coating of a Perovskite Film and Particles Exsoluted from the Perovskite Film
No full textA hybrid catalyst coating composed of a conformal thin film with exsoluted PrOₓ nano-particles. The conformal PNM thin film can be a perovskite composition of PrNi0.5Mn0.5O₃ (PNM). The PrOₓ nano-particles dramatically enhance the oxygen reduction reaction kinetics via a high concentration of oxygen vacancies while the thin PNM film effectively suppresses strontium segregation from the cathode of an intermediate-temperature solid oxide fuel cell.Georgia Tech Research Corporatio
Promotion of oxygen reduction reaction on a double perovskite electrode by a water-induced surface modification
No full textHighly efficient air electrodes are a key component of reversible fuel cells for energy storage and conversion; however, the development of efficient electrodes that are stable against water vapor remains a grand challenge. Here we report an air-electrode, composed of double perovskite material PrBa0.8Ca0.2Co2O5+delta (PBCC) backbone coated with nanoparticles (NPs) of BaCoO3-delta (BCO), that exhibits remarkable electrocatalytic activity for oxygen reduction reaction (ORR) while maintaining excellent tolerance to water vapor. When tested in a symmetrical cell exposed to wet air with 3 vol% H2O at 750 degrees C, the electrode shows an area specific resistance of similar to 0.03 omega cm(2) in an extended period of time. The performance enhancement is attributed mainly to the electrocatalytic activity of the BCO NPs dispersed on the surface of the porous PBCC electrode. Moreover, in situ Raman spectroscopy is used to probe reaction intermediates (e.g., oxygen species) on electrode surfaces, as the electrochemical properties of the electrodes are characterized under the same conditions. The direct correlation between surface chemistry and electrochemical behavior of an electrode is vital to gaining insight into the mechanisms of the electrocatalytic processes in fuel cells and electrolysers
Data-Driven Meteorological-Feature-Informed Wind Power Prediction with Machine Learning Decision Trees
No full textUncertainties exist in wind resource assessments during wind farm pre-construction that create under-performance biases in turbine output power. While wind speed is the main factor in power output, other factors, such as lapse rate and considering wind variation throughout the rotor layer, also have an effect on the predicted power output. To mitigate these uncertainties and to improve the estimation of annual energy production of a wind project, this work uses a decision tree machine learning model to assess the effectiveness of hub height wind speed, rotor equivalent wind speed, and lapse rate as variables in power prediction. Data from a scanning Doppler lidar and a meteorological tower are used to train regression trees and predict the output of a two-megawatt wind turbine. To further address how wind speed is characterized throughout the rotor layer, the decision tree model is trained for four vertical wind profile classifications which showcase the need for multiple calculations of wind speed at various levels of the rotor layer. This approach uses the atmospheric data to correlate the power outputs to wind profiles and meteorological characteristics to be able to predict power responses according to physical patterns. Four sets of predictors are used to train the decision tree model and test its prediction capability: hub height wind speed, rotor equivalent wind speed, hub height wind speed combined with lapse rate, and rotor equivalent wind speed combined with lapse rate. Results indicate that when compared to traditional power curve methods, the decision tree combining rotor equivalent wind speed and lapse rate improves prediction accuracy by 22% for the given data set, while also proving to be the most effective method in power prediction for all classified vertical wind profile types. It was observed that models that incorporated lapse rate into predictions performed better than those without it, showcasing the importance of considering atmospheric criteria in wind power prediction analyses
A study of the impact of numerical dissipation on meso-scale simulations of hurricane intensification with observational heating
No full textNumerous aspects of human existence, both material and immaterial, can be disrupted by a hurricane. In this work, the computational fluid dynamics of hurricane rapid intensification (RI) are studied by running idealized simulations with two different codes: a community-based, finite-difference/split-explicit model (WRF) and a spectral-element/semi-implicit model (NUMA). Rapid intensification is what RI stands for, how a hurricane gets stronger quickly. The main goal of this study is to find out how implicit numerical dissipation (IND) affects the energy of the vortex's response to heating, which describes the fundamental dynamics of the hurricane RI process. The heating that is taken into account here is derived from data. These observations include four-dimensional, fully nonlinear, latent heating/cooling rates estimated using airborne Doppler radar readings acquired during RI in a hurricane. The results show that WRF has more IND than NUMA, with a decrease in several intensity parameters, such as (1) the time-integrated mean kinetic energy values that WRF predicts are 20% lower than those that NUMA predicts and (2) the peak, localized wind speeds that WRF predicts are 12 meters per second slower than those that NUMA predicts. To make a time series of intensity similar to NUMA, the eddy diffusivity values in WRF need to be less than those in NUMA by about 50%. Various analyses are conducted comparing WRF with NUMA. Kinetic energy budgets reveal that the pressure contribution is the primary cause in the model variations, with WRF generating an average ?23% lower vortex energy input. The IND is associated with the low-order spatial discretization of the pressure gradient in WRF. In addition, the mean contribution of the eddy transport term to the vortex intensification is determined to be ?20% positive. These findings have significant implications for the academic and operational forecasting communities that employ WRF and similar numerical methods
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