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Pertica, A J

Publications and source records attributed to Pertica, A J.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the 'point-cloud' of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

97 MATHEMATICS AND COMPUTING↗

Satellite Collision Modeling with Physics-Based Hydrocodes: Debris Generation Predictions of the Iridium-Cosmos Collision Event and Other Impact Events

Satellite collision debris poses risks to existing space assets and future space missions. Predictive models of debris generated from these hypervelocity collisions are critical for developing accurate space situational awareness tools and effective mitigation strategies. Hypervelocity collisions involve complex phenomenon that spans several time- and length-scales. We have developed a satellite collision debris modeling approach consisting of a Lagrangian hydrocode enriched with smooth particle hydrodynamics (SPH), advanced material failure models, detailed satellite mesh models, and massively parallel computers. These computational studies enable us to investigate the influence of satellite center-of-mass (CM) overlap and orientation, relative velocity, and material composition on the size, velocity, and material type distributions of collision debris. We have applied our debris modeling capability to the recent Iridium 33-Cosmos 2251 collision event. While the relative velocity was well understood in this event, the degree of satellite CM overlap and orientation was ill-defined. In our simulations, we varied the collision CM overlap and orientation of the satellites from nearly maximum overlap to partial overlap on the outermost extents of the satellites (i.e, solar panels and gravity boom). As expected, we found that with increased satellite overlap, the overall debris cloud mass and momentum (transfer) increases, the average debris size decreases, and the debris velocity increases. The largest predicted debris can also provide insight into which satellite components were further removed from the impact location. A significant fraction of the momentum transfer is imparted to the smallest debris (< 1-5mm, dependent on mesh resolution), especially in large CM overlap simulations. While the inclusion of the smallest debris is critical to enforcing mass and momentum conservation in hydrocode simulations, there seems to be relatively little interest in their disposition. Based on comparing our results to observations, it is unlikely that the Iridium 33-Cosmos 2251 collision event was a large mass-overlap collision. We also performed separate simulations studying the debris generated by the collision of 5 and 10 cm spherical projectiles on the Iridium 33 satellite at closing velocities of 5, 10, and 15 km/s. It is important to understand the vulnerability of satellites to small debris threats, given their pervasiveness in orbit. These studies can also be merged with probabilistic conjunction analysis to better understand the risk to space assets. In these computational studies, we found that momentum transfer, kinetic energy losses due to dissipative mechanisms (e.g., fracture), fragment number, and fragment velocity increases with increasing velocity for a fixed projectile size. For a fixed velocity, we found that the smaller projectile size more efficiently transfers momentum to the satellite. This latter point has an important implication: Eight (spaced) 5 cm debris objects can impart more momentum to the satellite, and likely cause more damage, than a single 10 cm debris object at the same velocity. Further studies are required to assess the satellite damage induced by 1-5 cm sized debris objects, as well as multiple debris objects, in this velocity range.

42 ENGINEERING↗

Intelligent Sensor Tasking for Space Collision Mitigation

Orbital collisions pose a hazard to space operations. Using a high performance computer modeling and simulation environment for space situational awareness, we explore a new paradigm for improving satellite conjunction analysis by obtaining more precise orbital information only for those objects that pose a collision risk greater than a defined threshold to a specific set of satellites during a specified time interval. In particular, we assess the improvement in the quality of the conjunction analysis that can be achieved using a distributed network of ground-based telescopes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗