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Next generation Unmanned Aerial Vehicles (UAVs) must reliably avoid moving obstacles. Existing dynamic collision avoidance methods are effective where obstacle trajectories are linear or known, but such restrictions are not accurate to many…

This paper introduces a novel Monte Carlo (MC) method to simulate the evolution of the low-earth orbit environment, enhancing the MIT Orbital Capacity Analysis Tool (MOCAT). In recent decades, numerous space environment models have been…

Resilient routing in large-scale Low Earth Orbit (LEO) satellite networks remains a key challenge due to frequent and unpredictable link and node failures, potentially in response to cybersecurity breaches. While prior work has explored…

In Epoch 2 of the 2024 PDC25 Hypothetical Asteroid Impact Scenario, an asteroid is confirmed to be on a collision course with the Earth, and its size and surface composition have been well characterized via a flyby mission. A kinetic…

Using transport theory to model central Au + Au collisions in the energy region of 20 - 110 MeV/u, at impact parameters b <= 5 fm, we predict a measurable impact of spinoidal instability as the collective expansion sets in with energy. Two…

The increasing number of Anthropogenic Space Objects (ASOs) in Low Earth Orbit (LEO) poses a threat to the safety and sustainability of the space environment. Multiple companies are planning to launch large constellations of hundreds or…

The increasing volume of space objects in Earth's orbit presents a significant challenge for Space Situational Awareness (SSA). And in particular, accurate orbit prediction is crucial to anticipate the position and velocity of space…

The growing number of space debris in Low Earth Orbit (LEO) jeopardizes long-term orbital sustainability, requiring efficient risk assessment for active debris removal (ADR) missions. This study presents the development and validation of…

This study proposes a dynamic model to reflect the physical image of the droplet breakup process in two-phase detonation flows. This breakup model is implemented in a two-phase detonation solver developed based on an open-source…

Low Earth Orbit (LEO) satellite networks connect millions of devices on Earth and offer various services, such as data communications, remote sensing, and data harvesting. As the number of services increases, LEO satellite networks will…

Regulation, legal liabilities, and societal concerns challenge the adoption of AI in safety and security-critical applications. One of the key concerns is that adversaries can cause harm by manipulating model predictions without being…

Orbital debris is a pressing problem which presents a danger to global space operations and a barrier to continued development of the space economy and space infrastructure. As research continues regarding orbital debris, there is a need…

We investigate reaction mechanisms occurring in heavy ion collisions at low energy (around 20 MeV/u). In particular, we focus on the competition between fusion and break-up processes (Deep-Inelastic and fragmentation) in semi-peripheral…

This work presents a sequential convex program method to compute fuel-optimal collision avoidance maneuvers for long-term encounters. The low-thrust acceleration model is used to account for the control, but the method can compute…

This paper presents a phenomenological study on the angle between the Standard and the Winner-Take-All (WTA) jet axes ($\Delta R_{{\rm axis}}^{{\rm WTA-Std}}$) in high-energy nuclear collisions. The $p$+$p$ baseline is provided by the…

A possible mean to stabilize the LEO debris population is to remove each year 5 heavy debris like spent satellites or launchers stages from that space region. This paper investigates the DeltaV requirement for such a Space Debris Collecting…

A load sharing system has several components and the failure of one component can affect the lifetime of the surviving components. Since component failure does not equate to system failure for different system designs, the analysis of the…

The escalating accumulation of orbital debris threatens the sustainability of space operations, necessitating active removal solutions that overcome the limitations of current fuel-dependent methods. To address this, this study introduces a…

This study develops an AI-based implementation of autonomous On-Orbit Servicing (OOS) mission to assist with spacecraft collision avoidance maneuvers (CAMs). We propose an autonomous `servicer' trained with Reinforcement Learning (RL) to…

Characterizing the risk of operations is a fundamental requirement in robotics, and a crucial ingredient of safe planning. The problem is multifaceted, with multiple definitions arising in the vast recent literature fitting different…