Engineering topics
Petropoulos, Anastassios
Publications and source records attributed to Petropoulos, Anastassios.
Uranus and Neptune Missions: A Study in Advance of the Next Planetary Science Decadal Survey
The ice giant planets, Uranus and Neptune, represent an important and relatively unexplored class of planet. Most of our detailed information about them comes from fleeting looks by the Voyager 2 spacecraft in the 1980s. Voyager, and ground-based work since then, found that these planets, their satellites, rings, and magnetospheres, challenge our understanding of the formation and evolution of planetary systems. We also now know that Uranus- Neptune size planets are common around other stars. These are some of the reasons ice giant exploration was a high priority in NASA's most recent Planetary Science Decadal Survey. In preparation for the next Decadal Survey, NASA, with ESA participation, conducted a broad study of possible ice giant missions in the 2024–2037 timeframe. This paper summarizes the key results of the study, and addresses questions that have been raised by the science community and in a recent NASA review. Foremost amongst these are questions about the science objectives, the science payload, and the importance of an atmospheric probe. The conclusions of the NASA/ESA study remain valid. In particular, it is a high priority to send an orbiter and atmospheric probe to at least one of the ice giants, with instrumentation to study all components of an ice giant system. Uranus and Neptune are found to be equally compelling as science targets. The two planets are not equivalent, however, and each system has things to teach us the other cannot. An additional mission study is needed to refine plans for future exploration of these worlds.
Mission Design Analysis for the Martian Moon Phobos: Close Flybys, Missed Thrusts, and Other In-Flight Entertainment
A robotic mission to the Martian moons Phobos and Deimos would offer a wealth of scientific information and serve as a useful precursor to potential human missions. In this paper, we investigate a prospective mission enabled by solar electric propulsion that would explore Phobos via a series of flybys followed by capture into orbit around the moon. Of particular interest are low-cost options for capture and walkdown to the target science orbits aided by multi-body effects due to the mutual gravitational interaction of Phobos and Mars. We also consider contingency operations in the event of missed thrust or maneuver execution errors.
Mission Design Analysis for the Martian Moon Phobos: Close Flybys, Missed Thrusts, and Other In-Flight Entertainment
No abstract available
Experiments with Julia for Astrodynamics Applications
Julia's potential for solving complex astrodynamics problems is studied. Julia is a high-level, new, dynamic programming language with performance approaching C/Fortran and has features like inbuilt parallelism, variable accuracy, integrated numerical libraries and direct C and Fortran interfaces. Two astrodynamics problems are solved in Julia: 1) Lambert's problem, using the vercosine formulation and 2) trajectory integration. Implemented algorithms are compared with C and Fortran based counterparts on key performance parameters (speed, development effort, etc). Using Julia for fast and reliable astrodynamics software development is also discussed.
Deflection Missions for Asteroid 2011 AG5
The recently discovered asteroid 2011 AG5 currently has a 1-in-500 chance of impacting Earth in 2040. In this paper, we discuss the potential of future observations of the asteroid and their effects on the asteroid's orbital uncertainty. Various kinetic impactor mission scenarios, relying on both conventional chemical as well as solar-electric propulsion, are presented for deflecting the course of the asteroid safely away from Earth. The times for the missions range from pre-keyhole passage (pre-2023), and up to five years prior to the 2040 Earth close approach. We also include a brief discussion on terminal guidance, and contingency options for mission planning.
EUROPA Multiple-Flyby Trajectory Design
As reinforced by the 2011 NRC Decadal Survey, Europa remains one of the most scientifically intriguing targets in planetary science due to its potential suitability for life. However, based on JEO cost estimates and current budgetary constraints, the Decadal Survey recommended-and later directed by NASA Headquarters-a more affordable pathway to Europa exploration be derived. In response, a flyby-only proof-of-concept trajectory has been developed to investigate Europa. The trajectory, enabled by employing a novel combination of new mission design techniques, successfully fulfills a set of Science Definition Team derived scientific objectives carried out by a notional payload including ice penetrating radar, topographic imaging, and short wavelength infrared observations, and ion neutral mass spectrometry in-situ measurements. The current baseline trajectory, referred to as 11-F5, consists of 34 Europa and 9 Ganymede flybys executed over the course of 2.4 years, reached a maximum inclination of 15 degrees, has a deterministic delta v of 157 m/s (post-PJR), and has a total ionizing dose of 2.06 Mrad (Si behind 100 mil Al, spherical shell). The 11-F5 trajectory and more generally speaking, flyby-only trajectories-exhibit a number of potential advantages over an Europa orbiter mission.
Genetic Algorithm Optimizes Q-LAW Control Parameters
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Efficient Optimization of Low-Thrust Spacecraft Trajectories
A paper describes a computationally efficient method of optimizing trajectories of spacecraft driven by propulsion systems that generate low thrusts and, hence, must be operated for long times. A common goal in trajectory-optimization problems is to find minimum-time, minimum-fuel, or Pareto-optimal trajectories (here, Pareto-optimality signifies that no other solutions are superior with respect to both flight time and fuel consumption). The present method utilizes genetic and simulated-annealing algorithms to search for globally Pareto-optimal solutions. These algorithms are implemented in parallel form to reduce computation time. These algorithms are coupled with either of two traditional trajectory- design approaches called "direct" and "indirect." In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. The indirect approach involves the primer-vector theory (introduced in 1963), in which the thrust control problem is transformed into a co-state control problem and the initial values of the co-state vector are optimized. In application to two example orbit-transfer problems, this method was found to generate solutions comparable to those of other state-of-the-art trajectory-optimization methods while requiring much less computation time.
Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms
Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.