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Articles 1 - 8 of 8
Full-Text Articles in Commercial Space Operations
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Publications
As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …
Terra Lunaris: Assessment Of A Lunar Habitat For Scientific Astronauts, Space Miners, Or Space Tourists, Dirk Schumann, Robert A. Goehlich
Terra Lunaris: Assessment Of A Lunar Habitat For Scientific Astronauts, Space Miners, Or Space Tourists, Dirk Schumann, Robert A. Goehlich
Publications
This conceptual paper explores ground- based habitable space modules for various applications. The Terra Lunaris concept serves as the baseline and is evaluated in comparison to existing and theoretical studies in this field. Terra Lunaris is a compact hybrid habitat that expands to offer nearly four times its transport volume by combining rigid modules with an inflatable shell. With most interior elements pre-installed and foldable, setup time and complexity are minimized. The design integrates technical zones, living quarters, and shared spaces, while also supporting psychological well-being under extreme conditions. The paper provides both qualitative and quantitative analyses of lunar habitation …
The Space Rescue Professional: Operationalizing Guardians For The Future, Benjamin Johnis, Robert Bettinger, James Dean
The Space Rescue Professional: Operationalizing Guardians For The Future, Benjamin Johnis, Robert Bettinger, James Dean
Faculty Publications
The escalating competition in space exploration demands a dedicated space rescue capability. This article argues for the establishment of a space rescue professional (SRP) career field within the Department of Defense and the US Space Force. By harnessing existing US Air Force combat rescue expertise and partnering with the National Aeronautics and Space Administration, the Space Force can rapidly develop a robust SRP program with the warrant officer corps as its backbone. This article addresses a critical gap in national space policy to outline a cost-effective dual-service training pipeline and SRP operational roles. Such an investment safeguards astronauts, bolsters US …
Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Student Works
Machine learning regression techniques have shown success at feedback control to perform near-optimal pinpoint landings for low fidelity formulations (e.g. 3 degree-of-freedom). Trajectories from these low-fidelity landing formulations have been used in imitation learning techniques to train deep neural network policies to replicate these optimal landings in closed loop. This study details the development of a near-optimal, neural network feedback controller for a 6 degree-of-freedom pinpoint landing system. To model disturbances, the problem is cast as either a multi-phase optimal control problem or a triple single-phase optimal control problem to generate examples of optimal control through the presence of disturbances. …
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua
Student Works
The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …
Predicting Dynamic Fragmentation Characteristics From High-Impact Energy Events Utilizing Terrestrial Static Arena Test Data And Machine Learning, Katharine Larsen, Riccardo Bevilacqua, Omkar S. Mulekar, Elisabetta L. Jerome, Thomas J. Hatch-Aguilar
Predicting Dynamic Fragmentation Characteristics From High-Impact Energy Events Utilizing Terrestrial Static Arena Test Data And Machine Learning, Katharine Larsen, Riccardo Bevilacqua, Omkar S. Mulekar, Elisabetta L. Jerome, Thomas J. Hatch-Aguilar
Student Works
To continue space operations with the increasing space debris, accurate characterization of fragment fly-out properties from hypervelocity impacts is essential. However, with limited realistic experimentation and the need for data, available static arena test data, collected utilizing a novel stereoscopic imaging technique, is the primary dataset for this paper. This research leverages machine learning methodologies to predict fragmentation characteristics using combined data from this imaging technique and simulations, produced considering dynamic impact conditions. Gaussian mixture models (GMMs), fit via expectation maximization (EM), are used to model fragment track intersections on a defined surface of intersection. After modeling the fragment distributions, …
Self-Acquisition Of Liquid Propellant Versatile Arsenal Of Resources Endeavour (S.A.L.V.A.R.E.), Vittorio Baraldi, Nikki Smith-Cielo, Sotirios Zormpas
Self-Acquisition Of Liquid Propellant Versatile Arsenal Of Resources Endeavour (S.A.L.V.A.R.E.), Vittorio Baraldi, Nikki Smith-Cielo, Sotirios Zormpas
Student Works
Unlocking the mysteries of Mars’s past and future habitability is just within humanity’s grasp. With a multitude of inherent similarities to Earth, Mars is one of the most promising locations to extend humankind’s reach in manned space exploration. As humanity is at the summit of taking the next leap for mankind by preparing the first crewed missions to Mars, a need that must be met is to significantly reduce the mass necessary to deliver to the surface.
The Self-Acquisition of Liquid propellant Versatile Arsenal of Resources Endeavour (SALVARE) project details a mission for creating the first Mars water-based In-Situ Resources …
Space Tourism: Hurdles And Hopes, Robert A. Goehlich
Space Tourism: Hurdles And Hopes, Robert A. Goehlich
Publications
According to the Space Policy Institute (2002, Bib. section), “Space tourism is the term broadly applied to the concept of paying customers traveling beyond Earth’s atmosphere.” Operating reusable launch vehicles (RLVs) might be a first step toward achieving mass space tourism. Thus, the aim of this article is to investigate the potential hurdles and other aspects of importance that must be overcome in order to use RLVs for space tourism flights. The primary ones are social issues (e.g., “Is space tourism ethically acceptable?”), institutional issues (e.g., “Is environmental pollution caused by space tourism more harmful than other emission sources?”), and …