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Solar Sail Kinetic Energy Impactor Trajectory Optimization for an Asteroid-Deflection Mission
(2007)
Innovative interplanetary deep space missions, like a main belt asteroid sample
return mission, require ever larger velocity increments (∆V s) and thus ever
more demanding propulsion capabilities. Providing much larger exhaust velocities than chemical high-thrust systems, electric low-thrust space-propulsion
systems can significantly enhance or even enable such high-energy missions. In
1995, a European-Russian Joint Study Group (JSG) presented a study report
on “Advanced Interplanetary Missions Using Nuclear-Electric Propulsion”
(NEP). One of the investigated reference missions was a sample return (SR)
from the main belt asteroid (19) Fortuna. The envisaged nuclear power plant,
Topaz-25, however, could not be realized and also the worldwide developments
in space reactor hardware stalled. In this paper, we investigate, whether such
a mission is also feasible using a solar electric propulsion (SEP) system and
compare our SEP results to corresponding NEP results.
Near-Earth asteroid (NEA) 99942 Apophis provides a typical example for the evolution of asteroid orbits that lead to Earth-impacts after a close Earth-encounter that results in a resonant return. Apophis will have a close Earth-encounter in 2029 with potential very close subsequent Earth-encounters (or even an impact) in 2036 or later, depending on whether it passes through one of several less than 1 km-sized gravitational keyholes during its 2029-encounter. A pre-2029 kinetic impact is a very favorable option to nudge the asteroid out of a keyhole. The highest impact velocity and thus deflection can be achieved from a trajectory that is retrograde to Apophis orbit. With a chemical or electric propulsion system, however, many gravity assists and thus a long time is required to achieve this. We show in this paper that the solar sail might be the better propulsion system for such a mission: a solar sail Kinetic Energy Impactor (KEI) spacecraft could impact Apophis from a retrograde trajectory with a very high relative velocity (75-80 km/s) during one of its perihelion passages. The spacecraft consists of a 160 m × 160 m, 168 kg solar sail assembly and a 150 kg impactor. Although conventional spacecraft can also achieve the required minimum deflection of 1 km for this approx. 320 m-sized object from a prograde trajectory, our solar sail KEI concept also allows the deflection of larger objects. For a launch in 2020, we also show that, even after Apophis has flown through one of the gravitational keyholes in 2029, the solar sail KEI concept is still feasible to prevent Apophis from impacting the Earth, but many KEIs would be required for consecutive impacts to increase the total Earth-miss distance to a safe value
Interplanetary trajectories for low-thrust spacecraft are often characterized by multiple revolutions around the sun. Unfortunately, the convergence of traditional trajectory optimizers that are based on numerical optimal control methods depends strongly on an adequate initial guess for the control function (if a direct method is used) or for the starting values of the adjoint vector (if an indirect method is used). Especially when many revolutions around the sun are re-
quired, trajectory optimization becomes a very difficult and time-consuming task that involves a lot of experience and expert knowledge in astrodynamics and optimal control theory, because an adequate initial guess is extremely hard to find. Evolutionary neurocontrol (ENC) was proposed as a smart method for low-thrust trajectory optimization that fuses artificial neural networks and evolutionary algorithms to so-called evolutionary neurocontrollers (ENCs) [1]. Inspired by natural archetypes, ENC attacks the trajectoryoptimization problem from the perspective of artificial intelligence and machine learning, a perspective that is quite different from that of optimal control theory. Within the context of ENC, a trajectory is regarded as the result of a spacecraft steering strategy that maps permanently the actual spacecraft state and the actual target state onto the actual spacecraft control vector. This way, the problem of searching the optimal spacecraft trajectory is equivalent to the problem of searching (or "learning") the optimal spacecraft steering strategy. An artificial neural network is used to implement such a spacecraft steering strategy. It can be regarded as a parameterized function (the network function) that is defined by the internal network parameters. Therefore, each distinct set of network parameters defines a different network function and thus a different steering strategy. The problem of searching the optimal steering strategy is now equivalent to the problem of searching the optimal set of network parameters. Evolutionary algorithms that work on a population of (artificial) chromosomes are used to find the optimal network parameters, because the parameters can be easily mapped onto a chromosome. The trajectory optimization problem is solved when the optimal chromosome is found. A comparison of solar sail trajectories that have been published by others [2, 3, 4, 5] with ENC-trajectories has shown that ENCs can be successfully applied for near-globally optimal spacecraft control [1, 6] and that they are able to find trajectories that are closer to the (unknown) global optimum, because they explore the trajectory search space more exhaustively than a human expert can do. The obtained trajectories are fairly accurate with respect to the terminal constraint. If a more accurate trajectory is required, the ENC-solution can be used as an initial guess for a local trajectory optimization method. Using ENC, low-thrust trajectories can be optimized without an initial guess and without expert attendance.
Here, new results for nuclear electric spacecraft and for solar sail spacecraft are presented and it will be shown that ENCs find very good trajectories even for very difficult problems. Trajectory optimization results are presented for 1. NASA's Solar Polar Imager Mission, a mission to attain a highly inclined close solar orbit with a solar sail [7] 2. a mission to de ect asteroid Apophis with a solar sail from a retrograde orbit with a very-high velocity impact [8, 9] 3. JPL's \2nd Global Trajectory Optimization Competition", a grand tour to visit four asteroids from different classes with a NEP spacecraft
Limit loads of circumferentially flawed pipes and cylindrical vessels under internal pressure
(2006)
Near-Earth asteroid 99942 Apophis provides a typical example for the evolution of asteroid orbits that lead to Earth-impacts after a close Earth-encounter that results in a resonant return. Apophis will have a close Earth-encounter in 2029 with potential very close subsequent Earth-encounters (or even an impact) in 2036 or later, depending on whether it passes through one of several so-called gravitational keyholes during its 2029-encounter. Several pre-2029-deflection scenarios to prevent Apophis from doing this have been investigated so far. Because the keyholes are less than 1 km in size, a pre-2029 kinetic impact is clearly the best option because it requires only a small change in Apophis' orbit to nudge it out of a keyhole. A single solar sail Kinetic Energy Impactor (KEI) spacecraft that impacts Apophis from a retrograde trajectory with a very high relative velocity (75-80 km/s) during one of its perihelion passages at about 0.75 AU would be a feasible option to do this. The spacecraft consists of a 160 m x 160 m, 168 kg solar sail assembly and a 150 kg impactor. Although conventional spacecraft can also achieve the required minimum deflection of 1 km for this approx. 320 m-sized object from a prograde trajectory, our solar sail KEI concept also allows the deflection of larger objects. In this paper, we also show that, even after Apophis has flown through one of the gravitational keyholes in 2029, solar sail Kinetic Energy Impactor (KEI) spacecraft are still a feasible option to prevent Apophis from impacting the Earth, but many KEIs would be required for consecutive impacts to increase the total Earth-miss distance to a safe value. In this paper, we elaborate potential pre- and post-2029 KEI impact scenarios for a launch in 2020, and investigate tradeoffs between different mission parameters.
Under DLR-contract, Giessen University and DLR Cologne are studying solar-electric propulsion missions (SEP) to the outer regions of the solar system. The most challenging reference mission concerns the transport of a 1.35-tons chemical lander spacecraft into an 80-RJ circular orbit around Jupiter, which would enable to place a 375 kg lander with 50 kg of scientific instruments on the surface of the icy moon "Europa". Thorough analyses show that the best solution in terms of SEP launch mass times thrusting time would be a two-stage EP module and a triple-junction solar array with concentrators which would be deployed step by step. Mission performance optimizations suggest to propel the spacecraft in the first EP stage by 6 gridded ion thrusters, running at 4.0 kV of beam voltage, which would save launch mass, and in the second stage by 4 thrusters with 1.25 to 1.5 kV of positive high voltage saving thrusting time. In this way, the launch mass of the spacecraft would be kept within 5.3 tons. Without a launcher's C3 and interplanetary gravity assists, Jupiter might be reached within about 4 yrs. The spiraling-down into the parking orbit would need another 1.8 yrs. This "large mission" can be scaled down to a smaller one, e.g., by halving all masses, the solar array power, and the number of thrusters. Due to their reliability, long lifetime and easy control, RIT-22 engines have been chosen for mission analysis. Based on precise tests, the thruster performance has been modeled.
Multiple Near-Earth Asteroid Rendezvous and Sample Return Using First Generation Solar Sailcraft
(2005)
Searching optimal interplanetary trajectories for low-thrust spacecraft is usually a difficult and time-consuming task that involves much experience and expert knowledge in astrodynamics and optimal control theory. This is because the convergence behavior of traditional local optimizers, which are based on numerical optimal control methods, depends on an adequate initial guess, which is often hard to find, especially for very-low-thrust trajectories that necessitate many revolutions around the sun. The obtained solutions are typically close to the initial guess that is rarely close to the (unknown) global optimum. Within this paper, trajectory optimization problems are attacked from the perspective of artificial intelligence and machine learning. Inspired by natural archetypes, a smart global method for low-thrust trajectory optimization is proposed that fuses artificial neural networks and evolutionary algorithms into so-called evolutionary neurocontrollers. This novel method runs without an initial guess and does not require the attendance of an expert in astrodynamics and optimal control theory. This paper details how evolutionary neurocontrol works and how it could be implemented. The performance of the method is assessed for three different interplanetary missions with a thrust to mass ratio <0.15mN/kg (solar sail and nuclear electric).
Solar Sails for Near- and Medium-Term Scientific Deep Space Missions / W. Sebolt ; B. Dachwald
(2005)
Low-thrust space propulsion systems enable flexible high-energy deep space missions, but the design and optimization of the interplanetary transfer trajectory is usually difficult. It involves much experience and expert knowledge because the convergence behavior of traditional local trajectory optimization methods depends strongly on an adequate initial guess. Within this extended abstract, evolutionary neurocontrol, a method that fuses artificial neural networks and evolutionary algorithms, is proposed as a smart global method for low-thrust trajectory optimization. It does not require an initial guess. The implementation of evolutionary neurocontrol is detailed and its performance is shown for an exemplary mission.