Spacecraft design is inherently difficult due to the nonlinearity of the systems involved as well as the expense of testing hardware in a realistic environment. The number and cost of flight tests can be reduced by performing extensive simulation and analysis work to understand vehicle operating limits and identify circumstances that lead to mission failure. A Monte Carlo simulation approach that varies a wide range of physical parameters is typically used to generate thousands of test cases. Currently, the data analysis process for a fully integrated spacecraft is mostly performed manually on a case-by-case basis, often requiring several analysts to write additional scripts in order to sort through the large data sets. There is no single method that can be used to identify these complex variable interactions in a reliable and timely manner as well as be applied to a wide range of flight dynamics problems. This dissertation investigates the feasibility of a unified, general approach to the process of analyzing flight dynamics Monte Carlo data. The main contribution of this work is the development of a systematic approach to finding and ranking the most influential variables and combinations of variables for a given system failure. Specifically, a practical and interactive analysis tool that uses tractable pattern recognition methods to automate the analysis process has been developed. The analysis tool has two main parts: the analysis of individual influential variables and the analysis of influential combinations of variables. This dissertation describes in detail the two main algorithms used: kernel density estimation and nearest neighbors. Both are non-parametric density estimation methods that are used to analyze hundreds of variables and combinations thereof to provide an analyst with insightful information about the potential cause for a specific system failure. Examples of dynamical systems analysis tasks using the tool are provided.

<div>Optimization of atmospheric flight control has long been performed on the ground, prior to mission flight due to large computational requirements used to solve non-linear programming problems. Onboard trajectory optimization enables the creation of new reference trajectories and updates to guidance coefficients in real time. This thesis summarizes the methods involved in solving optimal control problems in real time using convexification and Sequential Convex Programming (SCP). The following investigation provided insight in assessing the use of state of the art SCP optimization architectures and convexification of the hypersonic equations of motion[ 1 ]–[ 3 ] with different control schemes for the purposes of enabling on-board trajectory optimization capabilities.</div><div>An architecture was constructed to solve convexified optimal control problems using direct population of sparse matrices in triplet form and an embedded conic solver to enable rapid turn around of optimized trajectories. The results of this show that convexified optimal control problems can be solved quickly and efficiently which holds promise in autonomous trajectory design to better overcome unexpected environments and mission parameter changes. It was observed that angle of attack control problems can be successfully convexified and solved using SCP methods. However, the use of multiple coupled controls is not guaranteed to be successful with this method when they act in the same plane as one another. The results of this thesis demonstrate that state of the art SCP methods have the capacity to enable onboard trajectory optimization with both angle of attack control and bank angle control schemes.</div><div><br></div>

Aerocapture offers a near propellantless and quick method of orbit insertion at atmosphere bearing planetary destinations. Compared to conventional propulsive insertion, the primary advantage of using aerocapture is the savings in propellant mass which could be used to accommodate more useful payload. To protect the spacecraft from the aerodynamic heating during the maneuver, the spacecraft must be enclosed in a protective aeroshell or deployable drag device which also provides aerodynamic control authority to target the desired conditions at atmospheric exit. For inner planets such as Mars and Venus, aerocapture offers a very attractive option for inserting small satellites or constellations into very low circular orbits such as those used for imaging or radar observations. The large amount of propellant required for orbit insertion at outer planets such as Uranus and Neptune severely limits the useful payload mass that can delivered to orbit as well as the achievable flight time. For outer planet missions, aerocapture opens up an entirely new class of short time of flight trajectories which are infeasible with propulsive insertion. A systems framework for rapid conceptual design of aerocapture missions considering the interdependencies between various elements such as interplanetary trajectory and vehicle control performance for aerocapture is presented. The framework provides a step-by-step procedure to formulate an aerocapture mission starting from a set of mission objectives. At the core of the framework is the ``aerocapture feasibility chart", a graphical method to visualize the various constraints arising from control authority requirement, peak deceleration, stagnation-point peak heat rate, and total heat load as a function of vehicle aerodynamic performance and interplanetary arrival conditions. Aerocapture feasibility charts have been compiled for all atmosphere-bearing Solar System destinations for both lift and drag modulation control techniques. The framework is illustrated by its application to conceptual design of a Venus small satellite mission and a Flagship-class Neptune mission using heritage blunt-body aeroshells. The framework is implemented in the Aerocapture Mission Analysis Tool (AMAT), a free and open-source Python package, to enable scientists and mission designers perform rapid conceptual design of aerocapture missions. AMAT can also be used for rapid Entry, Descent, and Landing (EDL) studies for atmospheric probes and landers at any atmosphere-bearing destination.

A student-based university environment for engineering design and development is much different from a product development environment within the aerospace industry. Therefore, a different approach to systems engineering should be considered. By its very nature, a university product development laboratory thrives on creativity and rejects bureaucracy. Experience shows that continuity and discipline within a project is crucial for success. The practice of systems engineering enables technical project discipline. Systems engineering is the art and science of developing an operable system that meets requirements within imposed constraints. The purpose of this thesis is to describe the systems engineering processes and techniques necessary for a student-based project, and explicitly show how to implement these processes. Although attempts have been made to utilize a few systems engineering techniques in past projects, many students did not properly and consistently apply those techniques to the technical design work. The goal of the thesis is to tailor the NASA systems engineering processes to a student-based design laboratory environment and to apply the methodologies to the mission design of Paradox. The Picosatellite for Autonomous Rendezvous and Docking on-Orbit eXperiment, or Paradox, is the second of four missions to demonstrate autonomous rendezvous and docking with a picosatellite-class satellite. A strong technical contribution highlighted within the thesis involves developing an open architecture rendezvous targeting algorithm for the Paradox mission in the face of large mission architecture uncertainties. The robust targeting algorithm builds from previous work utilizing an optimizer based on the Clohessey-Wiltshire equations and an iterative Lambert targeter. The contribution extends the rendezvous transfer times by including a multi-revolution Lambert targeter. The rendezvous algorithm will perform successfully given any launch vehicle and target spacecraft vehicle supporting the notion of an open architecture to satisfy the mission. The development of the algorithm is embedded within the context of the systems engineering processes to clearly showcase the intimate connection between systems engineering processes and the technical engineering design of a mission. / text

<div>The orbits of interest for potential missions are stable or nearly stable to maintain long term presence for conducting scientific studies and to reduce the possibility of rapid departure. Near Rectilinear Halo Orbits (NRHOs) offer such stable or nearly stable orbits that are defined as part of the L1 and L2 halo orbit families in the circular restricted three-body problem. Within the Earth-Moon regime, the L1 and L2 NRHOs are proposed as long horizon trajectories for cislunar exploration missions, including NASA's upcoming Gateway mission. These stable or nearly stable orbits do not possess well-distinguished unstable and stable manifold structures. As a consequence, existing tools for stationkeeping and transfer trajectory design that exploit such underlying manifold structures are not reliable for orbits that are linearly stable. The current investigation focuses on leveraging stretching direction as an alternative for visualizing the flow of perturbations in the neighborhood of a reference trajectory. The information supplemented by the stretching directions are utilized to investigate the impact of maneuvers for two contrasting applications; the stationkeeping problem, where the goal is to maintain a spacecraft near a reference trajectory for a long period of time, and the transfer trajectory design application, where rapid departure and/or insertion is of concern.</div><div><br></div><div>Particularly, for the stationkeeping problem, a spacecraft incurs continuous deviations due to unmodeled forces and orbit determination errors in the complex multi-body dynamical regime. The flow dynamics in the region, using stretching directions, are utilized to identify appropriate maneuver and target locations to support a long lasting presence for the spacecraft near the desired path. The investigation reflects the impact of various factors on maneuver cost and boundedness. For orbits that are particularly sensitive to epoch time and possess distinct characteristics in the higher-fidelity ephemeris model compared to their CR3BP counterpart, an additional feedback control is applied for appropriate phasing. The effect of constraining maneuvers in a particular direction is also investigated for the 9:2 synodic resonant southern L2 NRHO, the current baseline for the Gateway mission. The stationkeeping strategy is applied to a range of L1 and L2 NRHOs, and validated in the higher-fidelity ephemeris model.</div><div><br></div><div>For missions with potential human presence, a rapid transfer between orbits of interest is a priority. The magnitude of the state variations along the maximum stretching direction is expected to grow rapidly and, therefore, offers information to depart from the orbit. Similarly, the maximum stretching in reverse time, enables arrival with a minimal maneuver magnitude. The impact of maneuvers in such sensitive directions is investigated. Further, enabling transfer design options to connect between two stable orbits. The transfer design strategy developed in this investigation is not restricted to a particular orbit but applicable to a broad range of stable and nearly stable orbits in the cislunar space, including the Distant Retrograde Orbit (DROs) and the Low Lunar Orbits (LLO) that are considered for potential missions. Examples for transfers linking a southern and a northern NRHO, a southern NRHO to a planar DRO, and a southern NRHO to a planar LLO are demonstrated.</div>