Current emission prediction models in the conceptual design phase are based on historical data and empirical correlations. Two main reasons contributing to the current state of emission models are complexity of the phenomena involved in the combustor and relatively low priority of having a more detailed emissions model at the conceptual design phase. However, global environmental concerns and aviation industry growth highlight the importance of improving the current emissions prediction approaches. There is a need to have an emission prediction model in the conceptual design phase to reduce the prediction uncertainties and perform parametric studies for different combustor types and operating conditions. The research objective of this thesis is to develop a methodology to have an initial estimate of gas turbines' emissions, capture their trends and bring more information forward to the conceptual design phase regarding the emission levels. This methodology is based on initial sizing of the combustor and determining its flow-fractions at each section using a 1D flow analysis. A network of elementary chemical reactors is considered and its elements are sized from the results of the 1D flow analysis to determine the level of emissions at the design and operating conditions. Additional phenomena that have significant effects on the prediction of emissions are also considered which are: 1) droplet evaporation and diffusion burning, and 2) fuel-air mixture non-uniformity. A simplified transient model is developed to determine the evaporation rate for a given droplet size distribution and to obtain the amount of vaporized fuel before they ignite. A probabilistic unmixedness model is also employed to consider the range of equivalence ratio distribution for the fraction of the fuel that is vaporized and mixed with air. An emission model is created for the single annular combustor (SAC) configuration and applied to two combustors to test the prediction and parametric capabilities of the model. Both uncertainty and sensitivity analyses are performed to assess the capability of the model to reduce the prediction uncertainty of the model compared to the simpler models without considering the droplet evaporation and mixture non-uniformity. The versatility of the model is tested by creating an emission model for a Rich-Quench-Lean (RQL) combustor, and the results are compared to limited actual data. In general, the approach shows a good performance predicting the NOx emission level compared to CO emission level and capturing their trends. Especially in the RQL combustor case, a more detailed model is required to improve the prediction of the CO emission level.

Thesis (Ph. D.)--School of Industrial and Systems Engineering, Georgia Institute of Technology, 2004. Directed by Paul H. Kvam. / Vita. Includes bibliographical references (leaves 108-113).

Thesis (M.S. in Astronautical Engineering)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Agrawal, Brij N. Second Reader: Titus, Harold. "September 1990." Description based on title screen as viewed on December 17, 2009. DTIC Identifier(s): Attitude Control Systems, Flexible Structures, Spacecraft, Structural Response, Resonant Frequency, Experimental Design, Model Tests, Active Control, Gifts Computer Program, Dynamic Response, Computerized Simulation, Control Theory, Modal Analysis, Laboratory Tests, Theses. Author(s) subject terms: Attitude Control, Flexible Structures. Includes bibliographical references (p. 52). Also available in print.

Place is highly connected with outdoor education; it is defined by the location of the learning process and it designates both practically and theoretically ways to foster to students a strong bond with natural places. Place attachment refers to this bond or, in other words, the love relationship, one can develop with a place. This research tries to investigate if there is a causal relationship between outdoor education and development of place attachment. A quasi-experimental design research was conducted to 31 teenagers, 12-13 years old. A questionnaire, for measuring the level of place attachment to the natural surroundings of their school, was distributed at two different timelines. Four different dimensions of place attachment were measured; place identity, place dependence, social bonding and nature bonding. The experimental group participated in the program “Attachment to my Local Natural Landscape”, which was developed especially for this study and promoted direct connection with the land, through outdoor activities. The control group received no intervention. The results demonstrated that the program influenced only the female participants of the experimental group. No significant differences were indicated between the two groups after the implementation of the program. The small sample and the short length program implemented were important limitations of this study, which demand further future research to extract more clear results.

No description available.

In industrial experimentation, time and material costs are often at a premium. In designing an experiment, one needs to balance the desire for sufficient experimental runs to provide adequate data analysis, with the need to conduct a cost-effective experiment. A common compromise is the use of fractional factorial (FF) designs, in which only a fraction of the total possible runs is utilized. After discussing the basic concepts of FF designs, we introduce the fractional factorial split-plot (FFSP) design. Such designs occur frequently, because certain factors are often harder to vary than others, thus imposing randomization restric- tions. This thesis examines two techniques aimed at reducing run size that have not been greatly explored in the FFSP setting — nonregular designs and semifoldover designs. We show that these designs offer competitive alternatives to the more standard regular and full foldover designs and we produce tables of optimal designs in both scenarios.

No description available.

Technology evolves quickly, with innovative ideas growing everywhere. Still, no technology is anywhere near challenging the mouse and keyboard for navigation of your standard computer. This study focuses on comparing the traditional technologies of mouse and keyboard with the new technology of gestures - in this case Leap Motion - in purpose of finding how the usage differs and what the potential users want from the competing technology. The experiment was executed in a controlled environment, with as few external factors as possible. We found that although the test subjects found Leap Motion fun, the test subjects do not want to surf the web with gestures. Comparing the efficiency of use, mouse and keyboard took much less time, although this was expected due to experience with the traditional technology. The test subjects proposed Leap Motion to be used for playing games, 3D-modelling and for people with disabilities. Our conclusion, however, was that this technology could be successfully used in everything from hospitals to the industry, or in public places where it is important not to spread infections. We also discuss the pros and cons of Leap Motion in comparison with other gestural technologies.

In industrial experimentation, time and material costs are often at a premium. In designing an experiment, one needs to balance the desire for sufficient experimental runs to provide adequate data analysis, with the need to conduct a cost-effective experiment. A common compromise is the use of fractional factorial (FF) designs, in which only a fraction of the total possible runs is utilized. After discussing the basic concepts of FF designs, we introduce the fractional factorial split-plot (FFSP) design. Such designs occur frequently, because certain factors are often harder to vary than others, thus imposing randomization restric- tions. This thesis examines two techniques aimed at reducing run size that have not been greatly explored in the FFSP setting — nonregular designs and semifoldover designs. We show that these designs offer competitive alternatives to the more standard regular and full foldover designs and we produce tables of optimal designs in both scenarios.

This thesis studies the linear model, estimators of the treatment means, and opti¬mality criteria for designs and analysis of spatially arranged experiments. Four types of commonly used spatial correlation structures are discussed, and a neighbourhood of covariance matrices is investigated. Various properties about the neighbourhood are explored. When the covariance matrix of the error process is unknown, but be-longs to a neighbourhood of a covariance matrix, a modified generalized least squares estimator (GLSE) is proposed. This estimator seems more efficient than the ordinary least squares estimator in many practical applications. We also propose a criterion to find minimax designs that are efficient for a neighbourhood of correlations. When the number of plots is small, minimax designs can be computed exactly. When the number of plots is large, a simulated annealing algorithm is applied to find minimax or near minimax designs. Minimax designs for the least squares and generalized least squares estimators are compared in details. In general, we recommend using GLSE and the minimax design based on GLSE.