Speaker
Description
The expansion of human activity in space has resulted in a substantial increase in the number of objects traveling at high velocities in low Earth orbit. These objects are susceptible to mutual collisions, necessitating continuous and precise monitoring. The resulting cascade of debris from successive collisions, commonly referred to as the
Kessler syndrome, poses a significant long-term threat to the sustainability of orbital operations. To mitigate this risk, space agencies have established debris-mitigation guidelines, including passivation requirements and active debris-removal initiatives. At the level of ground-based Space Situational Awareness (SSA) operations, a critical objective is the development of comprehensive hazard knowledge for all monitored objects. Evaluating probabilities of fragmentation and associated risks is essential for enabling observers to prioritize and optimize observation campaigns in accordance with the threat levels posed by individual objects.
For similar purposes, indices such as the Environmental Consequences of Orbital Break-Ups (ECOB) or Criticality of Spacecraft Index (CSI) have already been created by different organizations. However, they mostly prioritize active debris removal based primarily on intrinsic object properties or collision rather than on explosion behavior. Few of them rely on private databases, long-term space environmental projections, or
parameters that are infrequently updated or not publicly accessible, making their use unpractical. These limitations underscore the need for a more practical index whose computation incorporates a broader assessment of fragmentation risk using regularly updated, publicly available data.
The Fragmentation, Loss-of-control, and other Acute Space-based Hazards (FLASH) Score was therefore developed as a hazard rating system for all tracked objects, intended to support day-to-day observation prioritization within SSA operations by identifying the most hazardous objects in orbit. In this framework, risk is defined as the product of event probability and the associated consequences for the space environment. Building on this premise, a central focus of the work is the characterization of self-fragmentation risk (i.e., explosions rather than collisions).
FLASH can be broadly decomposed into four components: 1) self-explosion
probability, estimated through statistical reliability methods; 2) collision probability, derived from formulations based on the kinetic theory of gases applied to orbital dynamics; 3) fragmentation consequences, quantified using the NASA Standard Breakup Model to estimate the number of generated fragments and their potential to induce catastrophic events; 4) an object-centric component that captures intrinsic properties independently of any fragmentation scenario.
The proposed solution exhibited 28-40% object-level similarity with existing indices in the top 50 rankings. However, the correspondence lies primarily in object categories rather than specific objects, as rankings within categories vary with orbital activity and location. The explosion component proved effective, with many top 200 objects belonging to categories documented in Database and Information System Characterizing Objects in Space (DISCOS) fragmentation. FLASH rankings show strong spatial agreement with Massive Collision Monitoring Activity (MCMA) cluster. While most indices prioritize rocket bodies (60-89% of 50 rankings), FLASH allocates only 49% of its top 200 to rocket bodies, thereby allowing greater diversity in object types.
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