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- Creators: Arizona State University
- Member of: ASU Electronic Theses and Dissertations
- Status: Published
Description
Recent studies of the occurrence of post-flutter limit cycle oscillations (LCO) of the F-16 have provided good support to the long-standing hypothesis that this phenomenon involves a nonlinear structural damping. A potential mechanism for the appearance of nonlinearity in the damping are the nonlinear geometric effects that arise when the deformations become large enough to exceed the linear regime. In this light, the focus of this investigation is first on extending nonlinear reduced order modeling (ROM) methods to include viscoelasticity which is introduced here through a linear Kelvin-Voigt model in the undeformed configuration. Proceeding with a Galerkin approach, the ROM governing equations of motion are obtained and are found to be of a generalized van der Pol-Duffing form with parameters depending on the structure and the chosen basis functions. An identification approach of the nonlinear damping parameters is next proposed which is applicable to structures modeled within commercial finite element software.
The effects of this nonlinear damping mechanism on the post-flutter response is next analyzed on the Goland wing through time-marching of the aeroelastic equations comprising a rational fraction approximation of the linear aerodynamic forces. It is indeed found that the nonlinearity in the damping can stabilize the unstable aerodynamics and lead to finite amplitude limit cycle oscillations even when the stiffness related nonlinear geometric effects are neglected. The incorporation of these latter effects in the model is found to further decrease the amplitude of LCO even though the dominant bending motions do not seem to stiffen as the level of displacements is increased in static analyses.
The effects of this nonlinear damping mechanism on the post-flutter response is next analyzed on the Goland wing through time-marching of the aeroelastic equations comprising a rational fraction approximation of the linear aerodynamic forces. It is indeed found that the nonlinearity in the damping can stabilize the unstable aerodynamics and lead to finite amplitude limit cycle oscillations even when the stiffness related nonlinear geometric effects are neglected. The incorporation of these latter effects in the model is found to further decrease the amplitude of LCO even though the dominant bending motions do not seem to stiffen as the level of displacements is increased in static analyses.
ContributorsSong, Pengchao (Author) / Mignolet, Marc P (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2015
Description
Failures in the cold chain, the system of refrigerated storage and transport that provides fresh produce or other essentials to be maintained at desired temperatures and environmental conditions, lead to food and energy waste. The mini container (MC) concept is introduced as an alternative to conventional refrigerated trucks (“reefers”), particularly for small growers. The energy consumption and corresponding GHG emissions for transporting tomatoes in two cities representing contrasting climates is analyzed for conventional reefers and the proposed mini containers. The results show that, for partial reefer loads, using the MCs reduces energy consumption and GHG emissions. The transient behavior of the vapor compression refrigeration cycle is analyzed by considering each component as a “lumped” system, and the resulting sub-models are solved using the Runge Kutta 4th-order method in a MATLAB code at hot and cold ambient temperatures. The time needed to reach steady state temperatures and the temperature values are determined. The maximum required compressor work in the transient phase and at steady state are computed, and as expected, as the ambient temperature increases, both values increase. Finally, the average coefficient of performance (COP) is determined for varying heat transfer coefficient values for the condenser and for the evaporator. The results show that the average COP increases as heat transfer coefficient values for the condenser and the evaporator increase. Starting the system from rest has an adverse effect on the COP due to the higher compressor load needed to change the temperature of the condenser and the evaporator. Finally, the impact on COP is analyzed by redirecting a fraction of the cold exhaust air to provide supplemental cooling of the condenser. It is noted that cooling the condenser improves the system's performance better than cooling the fresh air at 0% of returned air to the system.To sum up, the dissertation shows that the comparison between the conventional reefer and the MC illustrates the promising advantages of the MC, then a transient analysis is developed for deeply understanding the behaviors of the system component parameters, which leads finally to improvements in the system to enhance its performance.
ContributorsSyam, Mahmmoud Muhammed (Author) / Phelan, Patrick (Thesis advisor) / Villalobos, Rene (Thesis advisor) / Huang, Huei-Ping (Committee member) / Bocanegra, Luis (Committee member) / Al Omari, Salah (Committee member) / Arizona State University (Publisher)
Created2023
Description
Groundwater contamination is of environmental and human health concern. Bioremediation is a nature-based method for contaminant treatment. Bioremediation, which relies on the ability of microorganisms to destroy or transform contaminants, must be reliable and cost-competitive in comparison to more traditional treatment methods. Two hurdles must be overcome to enhance bioremediation’s effectiveness and competitiveness: i) being able to degrade recalcitrant compounds, and ii) being able to control the growth rate and location of microorganisms involved in bioremediation in the subsurface. My dissertation adds foundational knowledge and engineering application on how to biodegrade recalcitrant emerging and legacy halogenated compounds. Generating biotransformation knowledge on the recalcitrant emerging contaminants called per- and polyfluoroalkyl substances (PFAS) may lead to solutions for protecting both people and the planet. In my dissertation, I analyzed PFAS biotransformation and microbial defluorination literature via meta-analytical and bibliometric methods to identify unexplored topics and experimental conditions. The metanalytical work identified trends in PFAS microbial biotransformation science to inform future experimental design.
The second hurdle which must be overcome is being able to control bacterial growth in the subsurface. During bioremediation implementation microbial overgrowth may clog injection wells and the subsurface, leading to reduced porosity and treatment efficacy. Contaminant treatment schemes based on aerobic cometabolism frequently exhibit overgrowth at subsurface injection points for O2 (the electron acceptor) and a labile hydrocarbon (e.g., propane). My dissertation work experimentally evaluated acetylene as a microbial inhibitor for use in controlling microbial overgrowth during trichloroethene (TCE) aerobic cometabolism. I demonstrated that acetylene reduces the likelihood of microbial overgrowth of TCE-degrading microorganisms in soil-free microcosms and aquifer soil columns while retaining TCE degradation capacity. Cumulatively, my dissertation provides foundational knowledge for academics and bioremediation practitioners to develop robust and reliable bioremediation technologies.
ContributorsSkinner, Justin Paul (Author) / Delgado, Anca G. (Thesis advisor) / Rittmann, Bruce E (Committee member) / Chu, Min Ying Jacob (Committee member) / Arizona State University (Publisher)
Created2023
Description
Visual Question Answering (VQA) is an increasingly important multi-modal task where models must answer textual questions based on visual image inputs. Numerous VQA datasets have been proposed to train and evaluate models. However, existing benchmarks exhibit a unilateral focus on textual distribution shifts rather than joint shifts across modalities. This is suboptimal for properly assessing model robustness and generalization. To address this gap, a novel multi-modal VQA benchmark dataset is introduced for the first time. This dataset combines both visual and textual distribution shifts across training and test sets. Using this challenging benchmark exposes vulnerabilities in existing models relying on spurious correlations and overfitting to dataset biases. The novel dataset advances the field by enabling more robust model training and rigorous evaluation of multi-modal distribution shift generalization. In addition, a new few-shot multi-modal prompt fusion model is proposed to better adapt models for downstream VQA tasks. The model incorporates a prompt encoder module and dual-path design to align and fuse image and text prompts. This represents a novel prompt learning approach tailored for multi-modal learning across vision and language. Together, the introduced benchmark dataset and prompt fusion model address key limitations around evaluating and improving VQA model robustness. The work expands the methodology for training models resilient to multi-modal distribution shifts.
ContributorsJyothi Unni, Suraj (Author) / Liu, Huan (Thesis advisor) / Davalcu, Hasan (Committee member) / Bryan, Chris (Committee member) / Arizona State University (Publisher)
Created2023
Description
Novel means are needed to diagnose neurodegenerative diseases (NDDs) and cancer, given delays in medical diagnosis and rising rates of disease incidence, prevalence, and mortality worldwide. Development of NDDs and cancer has been linked to environmental toxins. Ensuing epigenetic changes may serve as helpful biomarkers to diagnose amyotrophic lateral sclerosis (ALS), Parkinson’s Disease (PD), and Alzheimer’s Disease (AD) as well as various cancers sooner and more accurately. This dissertation tabulates and evaluates a spectrum of diagnostic matrixes (i.e., soil, sewage sludge, blood) and markers of disease to inform disease surveillance. A literature search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Bradford Hill criteria implicated BMAA, formaldehyde, Mn, Hg, and Zn as environmental factors with strong association to ALS risk. Another PRISMA search identified epigenetic changes (e.g., DNA methylation) in NDD patients associated with environmental toxic exposures to air pollutants, heavy metals, and organic chemicals. Of the 180 environmental toxins hypothesized to be associated with AD, PD, or ALS, four heavy metals (As, Cd, Mn, and Hg) were common to these NDDs. Sources, as well as evidence and proxies of human exposure to these heavy metals and Pb were investigated here, namely the metal industries, and metal concentrations in topsoil, sewage sludge, and blood. Concentrations of Cd and Pb in sewage sludge were found to be significantly correlated with NDD prevalence rates in co-located populations (state-level) with odds ratios of 2.91 and 4.08, respectively. Markers of exposure and disease in urine and feces were also evaluated using PRISMA, finding 73 of 94 epigenetic biomarker panels to be valid for tracking primarily gastric and urinary cancers. In all studies, geospatial analyses indicated a preference in study cohorts located in the U.S., Europe, and the northern hemisphere, leaving underserved many populous regions particularly in the southern hemisphere. This dissertation draws attention to sewage sludge as a currently underutilized proxy matrix for assessing toxic human exposures and further identified a spectrum of particularly attractive, non-invasive biomarkers for future diagnostic use to promote early detection, survivability, and quality of life of individuals at risk of NDDs and cancer.
ContributorsNewell, Melanie Engstrom (Author) / Halden, Rolf U. (Thesis advisor) / Mastroeni, Diego (Committee member) / Lee, Heewook (Committee member) / Arizona State University (Publisher)
Created2023