<p dir="ltr">At the cusp of scientific discovery and innovation, mankind's next greatest challenge lies in developing capabilities to enable human presence in deep space. This entails setting up space infrastructure, travel pathways, managing spacecraft traffic, and building up deep space operation logistics. Spacecrafts that are a part of the infrastructure must be able to perform myriad of operations and transfers such as rendezvous and docking, station-keeping, loitering, collision avoidance etc. In support of this endeavour, an investigation is done to analyze and recreate the solution space for fuel-optimal trajectories and control histories required for onboard trajectory design of inexpensive spacecraft transfers and operations. This study investigates close range rendezvous (CRR), nearby orbital transfer, collision avoidance, and long range transfer maneuvers for spacecrafts whose highly complex and nonlinear behavior is modelled using the circular restricted three-body problem (CR3BP) dynamics and to which a finite-burn maneuver is augmented to model low-propulsion maneuvers. In order to study the nonlinear solution space for such maneuvers, this investigation contributes new formulations of nonlinear programming (NLP) optimal control problems solved to minimize fuel consumption, and validated by traditional methods already in use. This investigation proposes a Feature Learning based Optimal Control Method (L-OCM) to learn the solution space and recreate results in real-time. The NLP problem is solved off-line for a range of initial conditions. The set of solutions is used to generate datasets with initial conditions as inputs and the identified features of the optimal control solution as outputs. These features are inherent to reconstructing the optimal control histories of the solution and are selected keeping onboard computational capabilities in mind. Deep Neural Networks (DNNs) are trained to map the complex, nonlinear relationship between the inputs and outputs, and then implemented to find on-line solutions to any initial condition. The L-OCM method provides fuel-optimal, real-time solutions that can be implemented by a spacecraft performing operations in cislunar space.</p>

<p dir="ltr">This thesis presents a comprehensive exploration of advanced optimization strategies for addressing mixed-integer optimal control problems (MIOCPs) in aerospace applications, emphasizing the enhancement of convergence robustness, computational efficiency, and accuracy. The research develops a broad spectrum of optimization methodologies, including multi-phase approaches, parallel computing, reinforcement learning (RL), and distributed algorithms, to tackle complex MIOCPs characterized by highly nonlinear dynamics, intricate constraints, and discrete control variables.</p><p dir="ltr">Through discretization and reformulation, MIOCPs are transformed into general quadratically constrained quadratic programming (QCQP) problems, which are then equivalently converted into rank-one constrained semidefinite programs problems. To address these, iterative algorithms are developed specifically for solving such problems. Initially, two iterative search methods are introduced to achieve convergence: one is a hybrid alternating direction method of multipliers (ADMM) designed for large-scale QCQP problems, and the other is an iterative second-order cone programming (SOCP) algorithm developed to achieve global convergence. Moreover, to facilitate the convergence of these iterative algorithms and to enhance their solution quality, a multi-phase strategy is proposed. This strategy integrates with both the iterative ADMM and SOCP algorithms to optimize the solving of QCQP problems, improving both the convergence rate and the optimality of the solutions. To validate the effectiveness and improved computational performance of the proposed multi-phase iterative algorithms, the proposed algorithms were applied to several aerospace optimization problems, including six-degree-of-freedom (6-DoF) entry trajectory optimization, fuel-optimal powered descent, and multi-point precision landing challenges in a human-Mars mission. Theoretical analyses of convergence properties along with simulation results have been conducted, demonstrating the efficiency, robustness, and enhanced convergence rate of the optimization framework.</p><p dir="ltr">However, the iteration based multi-phase algorithms primarily guarantee only local optima for QCQP problems. This research introduces a novel approach that integrates a distributed framework with stochastic search techniques to overcome this limitation. By leveraging multiple initial guesses for collaborative communication among computation nodes, this method not only accelerates convergence but also enhances the exploration of the solution space in QCQP problems. Additionally, this strategy extends to tackle general nonlinear programming (NLP) problems, effectively steering optimization toward more globally promising directions. Numerical simulations and theoretical proofs validate these improvements, marking significant advancements in solving complex optimization challenges.</p><p dir="ltr">Following the use of multiple agents in QCQP problems, this research expand this advantage to address more general rank-constrained semidefinite programs (RCSPs). This research developed a method that decomposes matrices into smaller submatrices for parallel processing by multiple agents within a distributed framework. This approach significantly enhances computational efficiency and has been validated in applications such as image denoising, showcasing substantial improvements in both efficiency and effectiveness.</p><p dir="ltr">Moreover, to address uncertainties in applications, a learning-based algorithm for QCQPs with dynamic parameters is developed. This method creates high-performing initial guesses to enhance iterative algorithms, specifically applied to the iterative rank minimization (IRM) algorithm. Empirical evaluations show that the RL-guided IRM algorithm outperforms the original, delivering faster convergence and improved optimality, effectively managing the challenges of dynamic parameters.</p><p dir="ltr">In summary, this thesis introduces advanced optimization strategies that significantly enhance the resolution of MIOCPs and extends these methodologies to more general issues like NLP and RCSP. By integrating multi-phase approaches, parallel computing, distributed techniques, and learning methods, it improves computational efficiency, convergence, and solution quality. The effectiveness of these methods has been empirically validated and theoretically confirmed, representing substantial progress in the field of optimization.</p>

International Telemetering Conference Proceedings / October 28-31, 1985 / Riviera Hotel, Las Vegas, Nevada / Digital processing techniques and related algorithms for receiving and processing space vehicle downlink signals are discussed. The combination of low minimum signal to noise density (C/No), large signal dynamic range, unknown time of arrival, and high space vehicle dynamics that is characteristic of some of these downlink signals results in a difficult acquisition problem. A method for rapid acquisition is described which employs a Fast Fourier Transform (FFT). Also discussed are digital techniques for precise measurement of space vehicle range and range rate using a digitally synthesized number controlled oscillator (NCO).

<div>In order to answer the most pressing scientific questions about the two Martian moons, Phobos and Deimos, new remote sensing observations are required. The best way to obtain global high resolution observations of Phobos and Deimos is through dedicated missions to each body that utilize close-proximity orbits, however much of the orbital tradespace is too unstable to realistically or safely operate a mission.</div><div><br></div><div>This thesis explores the dynamics and stability characteristics of trajectories near Deimos. The family of distant retrograde orbits that are inclined out of the Deimos equatorial plane, known as quasi-satellite orbits, are explored extensively. To inform future mission design and CONOPS, the sensitivities and stability of distant retrograde and quasi-satellite orbits are examined in the vicinity of Deimos, and strategies for transferring between DROs are demonstrated. Finally, a method for designing quasi-satellite science orbits is demonstrated for a set of notional instruments and science requirements for a Deimos remote sensing mission.<br></div>

<p>  </p> <p>High altitude test facilities are needed for ground testing of upper stage rocket engines or small satellite thrusters with high expansion ratio nozzles to ensure full-flowing nozzle conditions. Rocket exhaust diffusers and ejector systems are essential components of these facilities and are frequently used to set desired simulated altitude/low pressure conditions and pump out rocket exhaust products. </p> <p>This dissertation combined experimental and numerical efforts on diffuser-ejector systems. The experimental efforts included the development of a Second Throat Exhaust Diffuser (STED) to aid with the qualification of space thrusters in the Purdue Altitude Chamber Facility. While performing these experiments, we characterized the single and two-stage ejector systems operating in conjunction with the diffuser to obtain and maintain specific simulated altitudes. </p> <p>The concurrent numerical effort focused on validating a Computational Fluid Dynamics (CFD) approach based on Reynolds-averaged Navier–Stokes equations flow simulations. After validating the ejector CFD, we used it to derive a corrective coefficient of a lumped parameter ejector model (LPM) developed previously for the ejectors used in the Purdue Altitude Facility. We created variable coefficient maps for the stages of the two-stage ejector system using the same LPM and the test data from one of our experiments. </p> <p>We designed, manufactured, and then validated a STED for altitude testing of a ~50 lbf hypergolic hybrid motor as a part of a NASA JPL project. The designed STED enabled the operation of the hybrid motor for the full duration of the test firing (about 2 seconds) at a simulated altitude of 102,000 feet, slightly above the targeted altitude of 100,000 feet. We also validated our diffuser CFD approach by creating a simulation using the measured diffuser back pressure and the average motor chamber pressure. </p> <p>We then devised an experiment to investigate several diffuser–ejector system configurations using cold gas thrusters with conical and bell nozzles. The main aim of that experiment was to explore the effects of different thruster nozzle geometries, diffuser geometries, and thruster/ejector operational parameters on the performance of a diffuser–ejector system. For all the configurations tested, we reported on the minimum starting and operating pressure ratios and corresponding correction factors on the normal shock method. The large hysteresis regions obtained mostly with bell nozzles having a high initial expansion angle provided an opportunity to economize the facility resources. In some cases which were later found to violate STED second throat contraction limits, we experienced a choking flow at the second throat. Then, we studied the second throat contraction limits in detail using CFD in addition to the experimental data and explored minimum diffuser second throats enabling diffuser starting and improving aerodynamic efficiency. </p> <p>Finally, we machined a larger scale cold gas thruster with different nozzle geometries (having throat diameters in the range of 0.367 – 0.52 inches) from acrylic rods to study possible flow separation and gas condensation events that could occur during tests in the altitude chamber. The main difference here with the previous experiment was that the diffuser (JPL STED) was fixed, and the two-stage ejector system was used to create the necessary back pressure. With the experiments performed at varying axial gaps between the nozzle exit and diffuser inlet, we were able to investigate the effect of that on the diffuser performance. The experimental data collected in this work and the complementary numerical efforts served to generate the operating envelope of the Purdue Altitude Chamber Facility.  </p>

<p> The abort mission refers to the mission where the landing vehicle needs to terminate the landing mission when an anomaly happens and be safely guided to the desired orbit. Missions involving crew on board demands for a robust and efficient abort strategy. This thesis focuses on solving the time-optimal abort guidance (TOAG) problem in real-time via the feature-based learning method. First, according to the optimal control theory, the features are identified to represent the optimal solutions of TOAG using a few parameters. After that, a sufficiently large dataset of time-optimal abort trajectories is generated offline by solving the TOAG problems with different initial conditions. Then the features are extracted for all generated cases. To find the implicit relationships between the initial conditions and identified features, neural networks are constructed to map the relationships based on the generated dataset. A successfully trained neural network can generate solution in real time for a reasonable initial condition. Finally, experimental flight tests are conducted to demonstrate the onboard computation capability and effectiveness of the proposed method. </p>

<p dir="ltr">The research presented in this thesis presents methods to solve multi-agent task allocation and path planning problems in the application of on-orbit servicing.</p>

Most present day spacecrafts have large interconnected solar panels. The dynamic behavior of the spacecraft in orbit can be modeled as a free rigid mass with flexible elements attached to it. The natural frequencies of such spacecrafts with deployed solar panels are very low. The low values of the natural frequencies pose difficulties for maneuvering the spacecraft. The control torque required to maneuver the spacecraft is influenced by the flexibility of the solar arrays. The control torque sets up transient oscillations in the flexible solar panels which in turn induces disturbances in the rigid satellite body and the payload within. Therefore the payload operations can be carried out only after the disturbances die out. For any reduction of the above disturbances it is necessary to understand the dynamic behavior of such systems to an applied torque. The present work first studies the nature of the disturbances. The influence of structural parameters on these disturbances is then investigated. Finally, the use of passive damping treatment using viscoelastic material is investigated for the reduction of the disturbances. In order to understand the nature of vibrations induced in the flexible appendages of a satellite during maneuvers, we model the maneuver loads in terms of applied angular acceleration as well as varying torque. The transient decay of the disturbance of the rigid element is characterized by the dynamic characteristics of the flexible panels or appendages. It is shown that by changing the stiffness of the panel the response of the rigid element can be modified. A simple model consisting of an Euler-Bernoulli beam attached to a free mass is next considered. The influence of various parameters of the EulerBernoulli beam in mitigating vibration and thereby the disturbance in the rigid mass is investigated. As the response of the rigid system mounted with the large flexible panels are influenced by the dynamics of the flexible panels, reduction of these disturbances can be achieved by reducing the vibration in the flexible panels. Therefore application of viscoelastic materials for passive damping treatment is investigated. The loss factor of a structure is significantly improved by using constrained viscoelastic layer damping treatment. However providing a constrained layer damping treatment on the entire structure is very inefficient in terms of the additional mass involved. Therefore damping material is applied at suitable optimal locations. In previous studies reported in literature, modal strain energy distribution in the viscoelastic material as well as the base structure is used as a tool to arrive at the optimum location for the damping treatment. It is shown in this study that such locations selected are not the optimum. A new approach is proposed in this study by which both the above shortcomings are overcome. It is shown that use of a parameter that is the ratio of the strain in the viscoelastic material to the angle of flexure is a more reliable measure in arriving at optimal locations for the application of constrained viscoelastic layers. The method considers the deformations in the viscoelastic material and it is shown that significant values of loss factors are achieved by providing material in a small region alone. We also show that loss factor can be improved by providing damping material near the interface region. The loss factor can be further improved by incorporating spacers by using spacer material having higher extensional modulus. Also shown is the fact that loss factor is unaffected by the shear modulus of the spacer material. Experiments have been conducted to validate these results. In a related study we consider honeycomb type flexible structures since in most of the spacecraft applications honeycomb sandwich constructions are employed. But loss factors of sandwich panels with constrained layer damping treatment are seldom discussed in the literature. Use of viscoelastic layers to improve the loss factors of the honeycomb sandwich beams is explored. The results show that the loss factors are enhanced by increasing the inplane stiffness of the constraining layer. These conclusions too are validated by experimental results. Finally a typical satellite with flexible solar panels is considered, and the use of the viscoelastic material for improving the damping is demonstrated.

No description available.

A combined experimental and numerical study of multidimensional viscous flows at speeds exceeding 8 km/s is reported. Experiments were performed in the X3 superorbital expansion tube with air and nitrogen test flows at a Mach number and total enthalpy of 10 and 40 MJ/kg, respectively. Laminar skin friction, heat flux and pressure measurements were obtained at regular intervals along one wall of a rectangular duct. The spatial resolution of the transducers was chosen to capture the multidimensional flow phenomena within the duct. Quasi-steady flow periods were established along the entire length of the duct in the test times offered by the expansion tube. Direct skin friction measurements were accomplished through the use of ‘in house’ acceleration compensated transducers. The successful operation of these skin friction transducers in a high performance expansion tube was demonstrated. Furthermore, the systematic uncertainty in measured shear stress was significantly reduced with the development of a new pressure calibration technique. For the conditions tested, Reynolds analogy was shown to be valid to within experimental uncertainty. The experimental data was in excellent agreement with numerical estimates. Three-dimensional numerical simulations of the diverging duct revealed that the flowfield structure in the vicinity of the corners differs from that of an unbounded corner or a constant area duct. Real gas effects other than those present in the residual nonequilibrium levels of freestream dissociation were negligible for the conditions tested. A computational study of two waverider configurations recently tested in the X3 superorbital expansion tube was conducted to assist in the interpretation of past results. The off-design aerodynamic performance was also analyzed and showed that blunting the leading edges dramatically degraded the performance by increasing drag and decreasing lift for the conditions considered.