Consideration of the environmental impact of aircraft has become critical in commercial aviation. The continued growth in air traffic has come with increasing concerns and demands to reduce aircraft emissions and this has imposed new constraints on the de- sign and development of future airplane concepts. In this work, an environmental design framework has been developed to design and optimize aircraft for specific environmental metrics. Multidisciplinary design optimization is used to optimize aircraft by simulta- neously considering airframe, engine and mission design. The environmental metrics considered include fuel burn, landing-takeoff NOx and fuel burn per distance flown. Additional concepts such as the design of large aircraft for short ranges are also presented. Multi-objective optimization is also used to illustrate the tradeoffs between the various environmental objective functions.

In the formation process of soot in the flames of even-carbon-numbered fuels, acetylene and its derivatives are suspected to be dominant. The addition of an odd-carbon-numbered fuel into these flames introduces methyl radicals and/or C3 chemistries, which are believed to (de)activate certain chemical pathways towards the production of soot. The resultant soot formation rate of the mixture could be higher than the sum of the respective rates of the mixture components, i.e., synergistic eff ect. In this work, the mixtures of butane isomers, ethylene-butane isomers, and propane-butane isomers were studied on a co-flow and a counterflow burner. Chemical effects were isolated from those of thermal and dilution by mixing isomers and comparing the mixtures including one isomer to those including the counterpart. Line of sight attenuation (LOSA) and laser-light extinction techniques were used for measuring soot volume fraction. The results provide information on synergistic effects in soot formation for the fuels used.

In the field of Evolutionary Robotics, the design, development and application of artificial neural networks as controllers have derived their inspiration from biology. Biologists and artificial intelligence researchers are trying to understand the effects of neural network learning during the lifetime of the individuals on evolution of these individuals by qualitative and quantitative analyses. The conclusion of these analyses can help develop optimized artificial neural networks to perform any given task. The purpose of this thesis is to study the effects of learning on evolution. This has been done by applying Temporal Difference Reinforcement Learning methods to the evolution of Artificial Neural Tissue controller. The controller has been assigned the task to collect resources in a designated area in a simulated environment. The performance of the individuals is measured by the amount of resources collected. A comparison has been made between the results obtained by incorporating learning in evolution and evolution alone. The effects of learning parameters: learning rate, training period, discount rate, and policy on evolution have also been studied. It was observed that learning delays the performance of the evolving individuals over the generations. However, the non zero learning rate throughout the evolution process signifies natural selection preferring individuals possessing plasticity.

A parallel, block-based, three-dimensional, hexahedral finite-volume scheme with adaptive mesh refinement has been developed for the solution of the 10-moment Gaussian closure for the modelling of fully three-dimensional micro-scale, non-equilibrium flows. The Gaussian closure has been shown to be a more effective tool for modelling rarefied flows lying within the transition regime than the Navier-Stokes equations, which encounter mathematical difficulties approaching free-molecular flows, and is computationally less expensive than particle-based methods for flows approaching the continuum limit. The hyperbolic nature of the moment equations is computationally attractive and the generalized transport equations can be solved in an accurate and efficient manner using Godunov-type finite-volume schemes as considered here. Details are given of the Gaussian closure, along with extensions for diatomic gases and slip-flow boundaries. Numerical results for several canonical flows demonstrate the potential of these moment closures and the parallel solution scheme for accurately predicting fully three-dimensional non-equilibrium flow behaviour.

Many space vehicles have been launched with large flexible components such as booms and solar panels. These large space structures (LSSs) have the potential to make attitude control unstable due to their lightly damped vibration. These vibrations can be controlled using a collection of control moment gyros (CMGs). CMGs consist of a spinning wheel in gimbals and produce a torque when the orientation of the wheel is changed. This study investigates the optimal distribution of these CMGs on LSSs for vibration suppression. The investigation considers a beam and a plate structure with evenly placed CMGs. The optimization allocates the amount of stored angular momentum possessed by these CMGs according to a cost function dependent on how quickly vibration motions are damped and how much control effort is exerted. The optimization results are presented and their effect on the motions of the beam and plate are investigated.

The effects of pressure on various properties of ten different syngas fueled flames were analyzed using one and two dimensional simulations. One-dimensional premixed flames were modeled in CANTERA. Flame speed, adiabatic flame temperature and thermal diffusivity as functions of equivalence ratio and pressure were quantified for the fuels using four chemical kinetic mechanisms. Data from the different mechanisms displayed good agreement with data from previous experimental benchmarks. Two-dimensional axisymmetric co-flow flames were simulated in a state of the art computational framework for modeling laminar flames. Flame structure comparisons were made with past experimental and numerical results as well as with theoretical predictions. Good agreement in stoichiometric flame height was observed with past theoretical and numerical flame height measurements. Visible flame heights had little correlation with the stoichiometric flame heights. The flame radius was also noted to be proportional to p^-0.35 at high pressures instead of p^-0.5 as predicted by theory.

An innovative dynamics and control algorithm is developed for a dual-nanosatellite formation flying mission. The principal function of this algorithm is to use regular GPS state measurements to determine the controlled satellite's tracking error from a set of reference trajectories in the local-vertical/local-horizontal reference frame. A linear state-feedback control law--designed using a linear quadratic regulator method--calculates the optimal thrusts necessary to correct this error and communicates the thrust directions to the attitude control system and the thrust durations to the propulsion system. The control system is developed to minimize the conflicting metrics of tracking error and ΔV requirements. To reconfigure the formation, an optimization algorithm is designed using the analytical solution to the state-space equation and the Hill-Clohessy-Wiltshire state transition matrix to solve for dual-thrust reconfiguration maneuvers. The resulting trajectories require low ΔV, use finite-time thrusts and are accurate in a fully nonlinear orbital environment. This algorithm will be used to control the CanX-4&5 formation flying demonstration mission. In addition, an iterative method which numerically generates quasi periodic trajectories for a satellite formation is presented. This novel technique utilizes a shooting approach to the Newton method to close the relative deputy trajectory over a specific number of orbits, then fits the actual perturbed motion of the deputy with a Fourier series to enforce periodicity. This process is applied to two well-known satellite formations: a projected circular orbit and a J2-invariant formation. Compared to conventional formations, these resulting quasi-periodic trajectories require a dramatically lower control effort to maintain and could therefore be used to extend ΔV-limited formation flying missions. Finally, an analytical study of the stability of the formation flying algorithm is conducted. To facilitate the proof, the control algorithm is converted into a discrete-time linear time-varying system. Stability of the system is determined via discrete Floquet theory. This analysis is applied to the CanX-4&5 control laws for tracking along-track orbits, projected circular orbits, and quasi J2-invariant formations.

Single-dielectric-barrier-discharge (SDBD) plasma actuators have shown much promise as an actuator for active flow control. Proper design and optimization of plasma actuators requires a model capable of accurately predicting the induced flow for a range of geometrical and excitation parameters. A number of models have been proposed in the literature, but have primarily been developed in isolation on independent geometries, frequencies and voltages. This study presents a comparison of four popular plasma actuator models over a range of actuation parameters for three different actuator geometries typical of actuators used in the literature. The results show that the hybrid model of Lemire & Vo (2011) is the only model capable of predicting the appropriate trends of the induced velocity for different geometries. Additionally, several modifications of this model have been integrated into a new proposed model for the plasma actuator, introducing a number of improvements.

Single-dielectric-barrier-discharge (SDBD) plasma actuators have shown much promise as an actuator for active flow control. Proper design and optimization of plasma actuators requires a model capable of accurately predicting the induced flow for a range of geometrical and excitation parameters. A number of models have been proposed in the literature, but have primarily been developed in isolation on independent geometries, frequencies and voltages. This study presents a comparison of four popular plasma actuator models over a range of actuation parameters for three different actuator geometries typical of actuators used in the literature. The results show that the hybrid model of Lemire & Vo (2011) is the only model capable of predicting the appropriate trends of the induced velocity for different geometries. Additionally, several modifications of this model have been integrated into a new proposed model for the plasma actuator, introducing a number of improvements.

Practical aerodynamic shape design problems must balance performance optimization over a range of on-design operating conditions with constraint satisfaction at off-design operating conditions. A multipoint optimization formulation can be used to represent on-design and off-design conditions with corresponding objective or constraint functions. Two methods are presented for obtaining optimal airfoil designs that satisfy all design objectives and constraints. The first method uses an unconstrained optimization algorithm where optimal design is achieved by minimizing a weighted sum of objective functions at each of the conditions. To address competing design objectives between on-design and off-design conditions, an automated procedure is used to weight off-design objective functions to limit their influence on the overall optimization. The second method uses the constrained optimization algorithm SNOPT, allowing aerodynamic constraints imposed at off-design conditions to be treated explicitly. Both methods are applied to the design of an airfoil for a hypothetical aircraft, which is formulated as an 18-point multipoint optimization.