Design Optimization of Gas Generator Hybrid Propulsion Boosters

A methodology used in support of a study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specific optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates

Predicting the depositional environments and transportation mechanisms of sediments using granulometric parameters, bivariate and multivariate analyses

Grain size distribution and classes present in sedimentary rocks are responsive to the physical changes of the transporting media and the basin of deposition. Analyzing grain size data is germane in reconstructing the sedimentary processes including identifying the palaeoenvironment of deposition. Twenty-three (23) samples, mainly sandstones, collected within latitude 6055’-6059’N and Longitude 005044’-005053’E in the Anambra Basin, were subjected to granulometric analysis, where grain size parameters (mean grain size, sorting, skewness and kurtosis) sensitive to environmental conditions were calculated. These parameters were integrated with bivariate and multivariate analyses. Graphic mean (Mz) in the study area range from 1.1 to 2.27 ɸ with an average value of 1.7 ɸ, suggesting that grains are predominantly fine to medium; sorting range from 0.71 to 1.36 ɸ with an average value of 1.02 ɸ, suggesting sediments are moderately sorted; skewness range from -0.57 to 0.51 ɸ with an average value of 1.28 ɸ suggesting coarsely skewed to fine skewed with a predominating near symmetrical skewness and kurtosis range from 0.57 to 1.51ɸ, with an average of 1.28 ɸ suggesting a very platykurtic to leptokurtic character. Bivariate scatter plots of the grains size parameters predicted the environment of deposition as shallow marine. Multivariate analysis calculated from established functions suggested environments that range from beach (backshore) to shallow marine (subtidal). The integration of the granulometric parameters, bivariate and multivariate plots predict an environment that is dominated by high energy indicating that the sediments of the study area were deposited in shallow marine environment. In addition, the Visher and Passega’s C-M diagrams characterized the transport mechanism of the sediments as predominantly by saltation although traction and suspension modes also play some roles

“The Power of Love : The Role of Sexual Communal Motivations and Relationship Power in Sexual Risk Taking

College-age students are an at-risk population for an unplanned pregnancy. Current sexual health interventions focus on methods of preventing pregnancy but fail to address communal motivations (being oriented towards the needs of others) which are important in relationships. Current interventions are long and require an increased attention span which is less effective today because the current generation of adolescents has a decreased attention span. The present study develops a WISE sexual health intervention (a simple yet targeted intervention) that incorporates sexual communal motivations to reduce unplanned pregnancy in college-age students. It was hypothesized that participants will have increased condom use intentions and future condom use behaviors in the experimental condition compared to the control condition. Relationship power (RP) was hypothesized to moderate sexual communal motivations, and influence condom use intentions and future condom use behavior. Participants with high RP were also hypothesized to have a significant increase in condom use intention and future condom use behavior in the experimental condition compared to the control condition. Participants watched a short sexual health education video followed by a reflection task where participants reflected on the material presented in the video (control) or applied the material to their life (experimental). Although preliminary results suggest no difference between the control and experimental condition in predicting condom use motivations and condom use intentions, exploratory findings found being other-oriented through communal motivations was influential regardless of condition. The present findings have implications for developing an impactful intervention to address unplanned pregnancy

A Model Of Visual Recognition Implemented Using Neural Networks

The ability to recognise and classify objects in the environment is an important property of biological vision. It is highly desirable that artificial vision systems also have this ability. This thesis documents research into the use of artificial neural networks to implement a prototype model of visual object recognition. The prototype model, describing a computtional architecture, is derived from relevant physiological and psychological data, and attempts to resolve the use of structural decomposition and invariant feature detection. To validate the research a partial implementation of the model has been constructed using multiple neural networks. A linear feed-forward network performs pre-procesing after being trained to approximate a conventional statistical data compression algorithm. The output of this pre-processing forms a feature vector that is categorised using an Adaptive Resonance Theory network capable of recognising arbitrary analog patterns. The implementation has been applied to the task of recognising static images of human faces. Experimental results show that the implementation is able to achieve a 100% successful recognition rate with performance that degrades gracefully. The implentation is robust against facial changes minor occlusions and it is flexible enough to categorise data from any domain

An examination and analysis of the Boltzmann machine, its mean field theory approximation, and learning algorithm

It is currently believed that artificial neural network models may form the basis for inte1ligent computational devices. The Boltzmann Machine belongs to the class of recursive artificial neural networks and uses a supervised learning algorithm to learn the mapping between input vectors and desired outputs. This study examines the parameters that influence the performance of the Boltzmann Machine learning algorithm. Improving the performance of the algorithm through the use of a naïve mean field theory approximation is also examined. The study was initiated to examine the hypothesis that the Boltzmann Machine learning algorithm, when used with the mean field approximation, is an efficient, reliable, and flexible model of machine learning. An empirical analysis of the performance of the algorithm supports this hypothesis. The performance of the algorithm is investigated by applying it to training the Boltzmann Machine, and its mean field approximation, the exclusive-Or function. Simulation results suggest that the mean field theory approximation learns faster than the Boltzmann Machine, and shows better stability. The size of the network and the learning rate were found to have considerable impact upon the performance of the algorithm, especially in the case of the mean field theory approximation. A comparison is made with the feed forward back propagation paradigm and it is found that the back propagation network learns the exclusive-Or function eight times faster than the mean field approximation. However, the mean field approximation demonstrated better reliability and stability. Because the mean field approximation is local and asynchronous it has an advantage over back propagation with regard to a parallel implementation. The mean field approximation is domain independent and structurally flexible. These features make the network suitable for use with a structural adaption algorithm, allowing the network to modify its architecture in response to the external environment

Summary of booster propulsion/vehicle impact study results

Hydrogen, RP-1, propane, and methane were identified by propulsion technology studies as the most probable fuel candidates for the boost phase of future launch vehicles. The objective of this study was to determine the effects of booster engines using these fuels and coolant variations on representative future launch vehicles. An automated procedure for integrated launch vehicle, engine sizing, and design optimization was used to optimize two stage and single stage concepts for minimum dry weight. The two stage vehicles were unmanned and used a flyback booster and partially reusable orbiter. The single stage designs were fully reusable, manned flyback vehicles. Comparisons of these vehicle designs, showing the effects of using different fuels, as well as sensitivity and trending data, are presented. In addition, the automated design technique is described

Organic geochemical analysis of shaly facies from two wells within Anambra Basin, Southeastern Nigeria

Organic geochemical analysis of two selected wells penetrating shale facies of the Anambra basin was conducted with the view of evaluating the section in terms of quantity and quality of organic matter, genetic potential, organic matter type, thermal maturity as well as determining the type of hydrocarbon that could be generated. Geochemical parameters such as Total Organic Carbon (TOC), S1 (representing free and adsorbed hydrocarbons present), S2 (representing hydrocarbons generated directly from the kerogen), S3 (carbon dioxide CO2 present) and maximum temperature (Tmax) as well as Hydrogen Index (HI), Oxygen Index (OI), Production Index (PI) and Genetic Potential (GP) were derived and calculated from the pyrolysis data. Result indicated that Well 1 samples have an average TOC of 1.21 wt % which is considered good in organic matter quantity and fair in quality, while Well 2 samples are organically lean, poor in quantity and quality with average TOC value of 0.15 wt %. The Genetic Potential (GP) expressed as (S1+S2) for Well 1 and Well 2 averages 2.03 and 0.68 mg HC/g respectively, indicating, a poor generational potential. The HI, OI and S2/S3 values of Well 1 samples are 146.56 mg HC/g, 226.78 mg HC/g and 0.86 respectively which on plots suggest the kerogen as type IV although few samples fall within the type III area. This contrasts with Well 2 samples having HI, OI and S2/S3 values as 343.67 mg HC/g, 276.78 mg HC/g and 1.26 respectively. Thus making the kerogen type to be interpreted as type III. Judging from Tmax (average of 441.670C for Well 1 and 470.440C for Well 2) and PI (average of 0.13 for Well 1 and 0.24 for Well 2) values, Well 1 samples are within the oil generating window whereas Well 2 samples are overmatured generating dry gas. Deductions from the result of geochemical analysis, depicts that the kerogen of Well 1 samples will generate oil while that of Well 2 samples have propensity to generate dry gas

Interpreting Force Concept Inventory Scores: NormalizedGain and SAT Scores

Preinstruction SAT scores and normalized gains (G) on the force concept inventory (FCI) were examined for individual students in interactive engagement (IE) courses in introductory mechanics at one high school (N=335) and one university (N=292), and strong, positive correlations were found for both populations (r=0.57 and r=0.46, respectively). These correlations are likely due to the importance of cognitive skills and abstract reasoning in learning physics. The larger correlation coefficient for the high school population may be a result of the much shorter time interval between taking the SAT and studying mechanics, because the SAT may provide a more current measure of abilities when high school students begin the study of mechanics than it does for college students, who begin mechanics years after the test is taken. In prior research a strong correlation between FCI G and scores on Lawson\u27s Classroom Test of Scientific Reasoning for students from the same two schools was observed. Our results suggest that, when interpreting class average normalized FCI gains and comparing different classes, it is important to take into account the variation of students\u27 cognitive skills, as measured either by the SAT or by Lawson\u27s test. While Lawson\u27s test is not commonly given to students in most introductory mechanics courses, SAT scores provide a readily available alternative means of taking account of students\u27 reasoning abilities. Knowing the students\u27 cognitive level before instruction also allows one to alter instruction or to use an intervention designed to improve students\u27 cognitive level

How do sociodemographic characteristics influence UK civilian opinions of UK armed forces Iraq and Afghanistan veterans? A mixed-method approach.

Evidence suggests that UK veterans are seen as victims with concern for their perceived mental health needs. This study examined sociodemographic factors that contribute to victimizing conceptualizations of British Army Iraq and Afghanistan veterans. UK participants (N = 234) provided three word associations to 'British Army Iraq Veteran' and 'British Army Afghanistan Veteran' and answered sociodemographic questions. A multiple linear regression outlines that low national pride, mission opposition and higher levels of education predict elevated victimizing word associations. Narrative accounts from UK interviews (N = 21) suggest that participants who perceived the recent conflicts as illegitimate conceptualize veterans as passive, naïve actors who had to submit to the agency of the anthropomorphic described government. This allowed holding overtly appreciative though belittling attitudes toward veterans, while opposing the missions. To dissociate veterans from victimizing perceptions, better knowledge about service and justifications for deployments need to be provided. Study limitations, including over sampling of young adult females, are discussed

Exploring the victimization of British veterans: comparing British beliefs about veterans with beliefs about soldiers.

Evidence suggests that most of the UK public appreciate currently serving UK Armed Forces personnel but are less positive in their beliefs about veterans. This research examined the social representations held by civilian participants of UK veterans and serving soldiers to understand why veterans may be seen more negatively. An open-ended word association task was completed by 234 UK participants where they were asked to provide three initial responses to the words “veteran” and “soldier” and to evaluate their responses in accordance to prototypicality. The 1,404 resultant associations were grouped into 14 thematic clusters. Using the hierarchical evocation method, the results suggest “heroizing associations” to be a defining core element for “soldier” and “veteran” but “victimizing associations” to be an element only for “veteran.” Principal component analyses suggest victimizing associations are related to war and deindividuated associations; “heroizing associations” are related to characterizations of the veteran’s personality. Implications and future directions are discussed