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Description
Recently, the use of zinc oxide (ZnO) nanowires as an interphase in composite materials has been demonstrated to increase the interfacial shear strength between carbon fiber and an epoxy matrix. In this research work, the strong adhesion between ZnO and carbon fiber is investigated to elucidate the interactions at the interface that result in high interfacial strength. First, molecular dynamics (MD) simulations are performed to calculate the adhesive energy between bare carbon and ZnO. Since the carbon fiber surface has oxygen functional groups, these were modeled and MD simulations showed the preference of ketones to strongly interact with ZnO, however, this was not observed in the case of hydroxyls and carboxylic acid. It was also found that the ketone molecules ability to change orientation facilitated the interactions with the ZnO surface. Experimentally, the atomic force microscope (AFM) was used to measure the adhesive energy between ZnO and carbon through a liftoff test by employing highly oriented pyrolytic graphite (HOPG) substrate and a ZnO covered AFM tip. Oxygen functionalization of the HOPG surface shows the increase of adhesive energy. Additionally, the surface of ZnO was modified to hold a negative charge, which demonstrated an increase in the adhesive energy. This increase in adhesion resulted from increased induction forces given the relatively high polarizability of HOPG and the preservation of the charge on ZnO surface. It was found that the additional negative charge can be preserved on the ZnO surface because there is an energy barrier since carbon and ZnO form a Schottky contact. Other materials with the same ionic properties of ZnO but with higher polarizability also demonstrated good adhesion to carbon. This result substantiates that their induced interaction can be facilitated not only by the polarizability of carbon but by any of the materials at the interface. The versatility to modify the magnitude of the induced interaction between carbon and an ionic material provides a new route to create interfaces with controlled interfacial strength.
ContributorsGalan Vera, Magdian Ulises (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2013
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
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
Production from a high pressure gas well at a high production-rate encounters the risk of operating near the choking condition for a compressible flow in porous media. The unbounded gas pressure gradient near the point of choking, which is located near the wellbore, generates an effective tensile stress on the porous rock frame. This tensile stress almost always exceeds the tensile strength of the rock and it causes a tensile failure of the rock, leading to wellbore instability. In a porous rock, not all pores are choked at the same flow rate, and when just one pore is choked, the flow through the entire porous medium should be considered choked as the gas pressure gradient at the point of choking becomes singular. This thesis investigates the choking condition for compressible gas flow in a single microscopic pore. Quasi-one-dimensional analysis and axisymmetric numerical simulations of compressible gas flow in a pore scale varicose tube with a number of bumps are carried out, and the local Mach number and pressure along the tube are computed for the flow near choking condition. The effects of tube length, inlet-to-outlet pressure ratio, the number of bumps and the amplitude of the bumps on the choking condition are obtained. These critical values provide guidance for avoiding the choking condition in practice.
ContributorsYuan, Jing (Author) / Chen, Kangping (Thesis advisor) / Wang, Liping (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objectives: Although childhood obesity has received growing attention, parents still fail to recognize overweight and obesity in their children. Accurate identification of overweight or obesity in their child is associated with the parent's responsiveness to interventions aimed at preventing weight-related health issues. Recent research shows that a child's age and gender are associated with parental misperception of their child's weight status, but little is known about the interaction of these factors across various age groups. This study examined the association between a wide range of parent, child, and household factors and the accuracy of parental perception of their child's body weight status compared to parent-measured body weight status. Methods: Data were collected from a random-digit-dial telephone survey of 1708 households located in five low-income New Jersey cities with large minority populations. A subset of 548 children whose parents completed the survey and returned a worksheet of parent-measured heights and weights were the focus of the analysis. Bivariate and multivariate analyses were performed to determine the factors significantly associated with parental perception of their child's body weight status. Results: Based on parent-measure heights and weights, 36% of the children were overweight or obese (OWOB). Only 21% of OWOB children were perceived by their parents as OWOB. Child gender, child body mass index (BMI) and parent BMI were significant independent predictors of parents' accuracy at perceiving their child's body weight status. Conclusion: Boys, OWOB children, and children of OWOB parents had significantly greater odds of parental underestimation of their body weight status. Parents had better recognition of OWOB in their daughters, especially older daughters, than in their sons, suggesting parental gender bias in identifying OWOB in children. Further research is needed regarding parental gender bias and its implications in OWOB identification in children.
ContributorsBader, Wendy (Author) / Ohri-Vachaspati, Punam (Thesis advisor) / Lloyd, Kristen (Committee member) / Crespo, Noe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objectives Through a cross-sectional observational study, this thesis evaluates the relationship between food insecurity and weight status, eating behaviors, the home food environment, meal planning and preparation, and perceived stress as it relates to predominantly Hispanic/Latino parents in Phoenix, Arizona. The purpose of this study was to address gaps in the literature by examining differences in "healthy" and "unhealthy" eating behaviors, foods available in the home, how time and low energy impact meal preparation, and the level of stress between food security groups. Methods Parents, 18 years or older, were recruited during two pre-scheduled health fairs, from English as a second language classes, or from the Women, Infants, and Children's clinic at a local community center, Golden Gate Community Center, in Phoenix, Arizona. An interview, electronic, or paper survey were offered in either Spanish or English to collect data on the variables described above. In addition to the survey, height and weight were collected for all participants to determine BMI and weight status. One hundred and sixty participants were recruited. Multivariate linear and logistic regression models, adjusting for weight status, education, race/ethnicity, income level, and years residing in the U.S., were used to assess the relationship between food security status and weight status, eating behaviors, the home food environment, meal planning and preparation, and perceived stress. Results Results concluded that food insecurity was more prevalent among parents reporting lower income levels compared to higher income levels (p=0.017). In adjusted models, higher perceived cost of fruits (p=0.004) and higher perceived level of stress (p=0.001) were associated with food insecurity. Given that the sample population was predominately women, a post-hoc analysis was completed on women only. In addition to the two significant results noted in the adjusted analyses, the women-only analysis revealed that food insecure mothers reported lower amounts of vegetables served with meals (p=0.019) and higher use of fast-food when tired or running late (p=0.043), compared to food secure mothers. Conclusion Additional studies are needed to further assess differences in stress levels between food insecure parents and food insecure parents, with special consideration for directionality and its relationship to weight status.
ContributorsVillanova, Christina (Author) / Bruening, Meg (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Vega-Lopez, Sonia (Committee member) / Arizona State University (Publisher)
Created2014
Description
Fruit and vegetable (FV) consumption continues to lag far behind US Department of Agriculture (USDA) recommendations. Interventions targeting individuals' dietary behaviors address only a small fraction of dietary influences. Changing the food environment by increasing availability of and excitement for FV through local food production has shown promise as a method for enhancing intake. However, the extent to which local production is sufficient to meet recommended FV intakes, or actual intakes, of specific populations remains largely unconsidered. This study was the first of its kind to evaluate the capacity to support FV intake of Arizona's population with statewide production of FV. We created a model to evaluate what percentage of Dietary Guidelines for Americans (DGA) recommendations, as well as actual consumption, state-level FV production could meet in a given year. Intake and production figures were amended to include estimates of only fresh, non-tropical FV. Production was then estimated by month and season to illustrate fluctuations in availability of FV. Based on our algorithm, Arizona production met 184.5% of aggregate fresh vegetable recommendations, as well as 351.9% of estimated intakes of Arizonans, but met only 29.7% of recommended and 47.8% of estimated intake of fresh, non-tropical fruit. Much of the excess vegetable production can be attributed to the dark-green vegetable sub-group category, which could meet 3204.6% and 3160% of Arizonans' aggregated recommendations and estimated intakes, respectively. Only minimal seasonal variations in the total fruit and total vegetable categories were found, but production of the five vegetable sub-groups varied between the warm and cool seasons by 19-98%. For example, in the starchy vegetable group, cool season (October to March) production met only 3.6% of recommendations, but warm season (April to November) production supplied 196.5% of recommendations. Results indicate that Arizona agricultural production has the capacity to meet a large proportion of the population's FV needs throughout much of the year, while at the same time remaining a major producer of dark-green vegetables for out-of-state markets.
ContributorsVaudrin, Nicole (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Bruening, Meg (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Villalobos, J. Rene (Committee member) / Arizona State University (Publisher)
Created2013
Description
The objective of this thesis was to compare various approaches for classification of the `good' and `bad' parts via non-destructive resonance testing methods by collecting and analyzing experimental data in the frequency and time domains. A Laser Scanning Vibrometer was employed to measure vibrations samples in order to determine the spectral characteristics such as natural frequencies and amplitudes. Statistical pattern recognition tools such as Hilbert Huang, Fisher's Discriminant, and Neural Network were used to identify and classify the unknown samples whether they are defective or not. In this work, a Finite Element Analysis software packages (ANSYS 13.0 and NASTRAN NX8.0) was used to obtain estimates of resonance frequencies in `good' and `bad' samples. Furthermore, a system identification approach was used to generate Auto-Regressive-Moving Average with exogenous component, Box-Jenkins, and Output Error models from experimental data that can be used for classification
ContributorsJameel, Osama (Author) / Redkar, Sangram (Thesis advisor) / Arizona State University (Publisher)
Created2013
Description
This work presents two complementary studies that propose heuristic methods to capture characteristics of data using the ensemble learning method of random forest. The first study is motivated by the problem in education of determining teacher effectiveness in student achievement. Value-added models (VAMs), constructed as linear mixed models, use students’ test scores as outcome variables and teachers’ contributions as random effects to ascribe changes in student performance to the teachers who have taught them. The VAMs teacher score is the empirical best linear unbiased predictor (EBLUP). This approach is limited by the adequacy of the assumed model specification with respect to the unknown underlying model. In that regard, this study proposes alternative ways to rank teacher effects that are not dependent on a given model by introducing two variable importance measures (VIMs), the node-proportion and the covariate-proportion. These VIMs are novel because they take into account the final configuration of the terminal nodes in the constitutive trees in a random forest. In a simulation study, under a variety of conditions, true rankings of teacher effects are compared with estimated rankings obtained using three sources: the newly proposed VIMs, existing VIMs, and EBLUPs from the assumed linear model specification. The newly proposed VIMs outperform all others in various scenarios where the model was misspecified. The second study develops two novel interaction measures. These measures could be used within but are not restricted to the VAM framework. The distribution-based measure is constructed to identify interactions in a general setting where a model specification is not assumed in advance. In turn, the mean-based measure is built to estimate interactions when the model specification is assumed to be linear. Both measures are unique in their construction; they take into account not only the outcome values, but also the internal structure of the trees in a random forest. In a separate simulation study, under a variety of conditions, the proposed measures are found to identify and estimate second-order interactions.
ContributorsValdivia, Arturo (Author) / Eubank, Randall (Thesis advisor) / Young, Dennis (Committee member) / Reiser, Mark R. (Committee member) / Kao, Ming-Hung (Committee member) / Broatch, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
In recent years, overall consumption of meat products has been decreasing, and at the same time vegetarianism is on the rise. A variety of factors are likely driving changes in consumers' attitudes towards, and consumption of, meat products. Although concern regarding animal welfare may contribute to these trends, growing consumer interest in the roles that production and processing of meat play in terms of environmental degradation could also impact individuals' decisions about the inclusion of meat in their diets. Because these factors could be related to moral attitudes as well, the purpose of this study was to explore the relations among meat consumption, general environmental attitudes, and moral `foundations' of decision-making, including concern about minimizing `harm' and maximizing `care,' as well as issues of `purity' and `sanctity.' A survey was conducted among current college students using the New Ecological Paradigm scale and the Moral Foundations Questionnaire to assess environmental and moral attitudes. A food frequency questionnaire was used to assess meat consumption. Multiple linear regression analyses explored the relations of environmental and moral attitudes with meat consumption, controlling for potential confounding variables. The results showed no significant correlations among meat consumption, environmental attitudes or moral foundations of harm/care and purity/sanctity.
ContributorsSpringer, LeeAnn (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Hekler, Eric (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Hall, Rick (Committee member) / Arizona State University (Publisher)
Created2013