Optimal trajectory design has been extensively studied across multiple disciplines adopting different techniques for implementation and execution. It has been utilized in past space trajectory missions to either optimize the amount of fuel spent or minimize the time of flight to meet mission requirements. Coupled Radial Basis Functions (CRBFs) are a new way to solve these optimal control problems, and this thesis applies CRBFs to spacecraft trajectory optimization design problems. CRBFs are real-valued radial basis functions (RBFs) that utilize a conical spline while also not being affected by the value of the shape parameter. The CRBF approach is applied to nonlinear optimal control problems. We adopt the indirect formulation so that the necessary and boundary conditions are derived from the system dynamical equations. As a result, a set of nonlinear algebraic equations (NAEs) is generated. The NAEs are then solved using a standard solver in MATLAB and the results are produced. CRBFs do not rely heavily on initial extensive analysis of the problem, which makes it very intuitive to use. The states, control, and co-states are defined as the equations to be solved and approximated using CRBFs. The results show that CRBFs can be applied to space trajectory optimization problems to produce accurate results across state and costate variables on uniform user defined nodes across the simulation time.

To model and examine the thermal fluid phenomena involved in high-pressure, multi-nozzle spray cooling, a testbed is developed which includes a heating subsystem and an accumulator to pressurize common rail based piezoelectric injectors. Compared to conventional platforms, the implemented testbed allows for an abundance of layout arrangements and settings that provide a greater range of functionality. The volumetric flow rate of the testbed is modeled by a recurrent neural network trained from time-sequential obtained through experiments. The fidelity of the model, as well as the testbed's hardware, software, functionalities, and shortcomings are discussed.

In the past few decades, Kessler syndrome (named after Donald J. Kessler) has become a point of concern in the field of Space Situational Awareness and the future of space missions. It refers to a scenario, where space debris in Earth's orbits collides and creates an exponential increase in space debris numbers leading to more collisions and more debris. In order to handle the resulting challenges like conjunction analysis, tracking, and probability of collisions, the State Transition Matrix (STM) and Tensors (STTs) of the orbit problem play a significant role. In addition, STM and STTs are ubiquitous in spaceflight dynamics, guidance, navigation, and control applications. Several methods exist in the literature for computing the STM and the STTs of the orbit problem; however, all these methods are either restricted by a simplified gravity model, computational accuracy or computational efficiency. In this dissertation, an adaptive Analytic Continuation is studied as a procedure for computing the STM and STTs of the perturbed Two-body problem. Analytic Continuation is a Taylor series based semi-analytic integration method that utilizes recursions of high-order time derivatives and the Leibniz rule to produce a solution with arbitrary accuracy at a fraction of the computational cost of finite difference methods. In this work, the method is used to compute the STM and the second order STT for the perturbed two-body problem. An adaptation technique is developed for keeping a balance between the number of higher order time derivatives and the time-step to achieve prescribed tolerances. Analytic Continuation is also adopted in a high-fidelity estimation framework (AC-EKF) to provide accurate orbit estimation results for a space-based space surveillance network of observers. Test cases on LEO, MEO, GTO and HEO show machine precision accuracy in the symplectic nature of the gravity perturbed STM and STT irrespective of the number of orbital revolutions. Gravity and atmospheric drag perturbed STM shows at least 3 times more accurate results when compared to finite difference methods in the initial error propagation of the trajectories in a span of 10 orbit periods. Furthermore, by incorporating second order STT, the error propagation results are improved by 2 - 4 orders of magnitude. Finally, results from AC-EKF show the utility of the method to accurately predict the error covariance in the absence of sensor coverage. As future work, Analytic Continuation will be expanded to compute arbitrarily high-order STTs with applications in orbit prediction and trajectory design.

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This thesis presents experimental and finite element analysis results of eccentrically loaded carbon-fiber composite booms that can deploy solar sails. Using the collapsible tubular mast design along with the geometry from the upcoming Advance Composite Solar Sail System mission, short composite booms segments were manufactured for testing. New clamps were also designed to allow a column bending test to achieve eccentric loading. As buckling through eccentric loading has not previously seen much research, the geometry and composite layups were simplified to allow for ease of manufacturing and verification. The work presented here shows that a finite element simulation, using a new composite material model, can easily simulate the eccentric buckling of collapsible tubular mast booms. It was found that composite booms with this geometry realize two different buckling events. First, local buckles form near each set of clamps, and then a second buckling causes a loss of structural support.

In recent years, NASA has indicated a desire to return humans to the moon. With NASA planning manned missions within the next couple of decades, the concept development for these lunar vehicles has begun. The guidance, navigation, and control (GN&C) computer programs that will perform the function of safely landing a spacecraft on the moon are part of that development. The lunar descent guidance algorithm takes the horizontally oriented spacecraft from orbital speeds hundreds of kilometers from the desired landing point to the landing point at an almost vertical orientation and very low speed. Existing lunar descent GN&C algorithms date back to the Apollo era with little work available for implementation since then. Though these algorithms met the criteria of the 1960's, they are cumbersome today. At the basis of the lunar descent phase are two elements: the targeting, which generates a reference trajectory, and the real-time guidance, which forces the spacecraft to fly that trajectory. The Apollo algorithm utilizes a complex, iterative, numerical optimization scheme for developing the reference trajectory. The real-time guidance utilizes this reference trajectory in the form of a quartic rather than a more general format to force the real-time trajectory errors to converge to zero; however, there exist no guarantees under any conditions for this convergence. The proposed algorithm implements a purely analytical targeting algorithm used to generate two-dimensional trajectories "on-the-fly" or to retarget the spacecraft to another landing site altogether. It is based on the analytical solutions to the equations for speed, downrange, and altitude as a function of flight path angle and assumes two constant thrust acceleration curves. The proposed real-time guidance algorithm has at its basis the three-dimensional non-linear equations of motion and a control law that is proven to converge under certain conditions through Lyapunov analysis to a reference trajectory formatted as a function of downrange, altitude, speed, and flight path angle. The two elements of the guidance algorithm are joined in Monte Carlo analysis to prove their robustness to initial state dispersions and mass and thrust errors. The robustness of the retargeting algorithm is also demonstrated.

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Thesis (Ph. D., Microbiology, Molecular Biology and Biochemistry)--University of Idaho, March 2007. / Major professor: Ronald L. Crawford. Includes bibliographical references. Also available online (PDF file) by subscription or by purchasing the individual file.