Hybrid rocket propulsion systems, utilizing liquid oxidizers in conjunction with solid hydrocarbon fuels, are recognized for their safety, environmental compatibility, operational simplicity, and capacity for precise control over thrust and impulse profiles. Thus, this emerging technology offers a promising alternative for future space propulsion applications. In the last decade, the Utah State University Propulsion Research Laboratory (PRL) has developed hybrid propulsion technologies for a diverse array of space mission applications. This paper summarizes key progress in the PRL’s green-hybrid propulsion research, offers insights for scalable design future strategies, and presents a road map for future applications.

At the PRL, significant advancements in hybrid rocket technology have addressed both performance and sustainability requirements. Among the key technological advances are a patented low-energy arc-ignition system, which ensures reliable and consistent ignition, and a digital throttle control that enables precise and deep throttling. These advancements significantly enhance flexibility in missions requiring orbital transfer, attitude control, and rendezvous operations. These advances enable hybrid propulsion systems to serve as viable competitors to conventional chemical and electric propulsion methods for space applications.

PRL research also focuses on environmental sustainability alongside ignition and throttling improvements. A key objective is to substitute toxic and hazardous hydrazine-based propellants with safer, environmentally friendly options for in-space propulsion. By leveraging modern additive manufacturing methods, PRL research has enabled fast, affordable solid-fuel production by using recycled and bio-based plastics. These advances have optimized fuels, resulting in lowered production costs, minimized environmental impact, and increased motor efficiency. These advanced fuel blends exhibit advantageous regression rates, consistent mechanical strength, and compatibility with current ignition and oxidizer-feed systems. This research shows that sustainable materials can be used in propulsion without compromising performance, enabling hybrid rocket engines to be competitive in this market space.

Antarctic ice-shelf movements are essential for controlling sea-level rise and global climate patterns. Continuous monitoring of the region poses substantial challenges due to the vast spatial extent, remote location, and harsh environmental conditions of Antarctica. The Antarctic Ice Exploration Experiment (AICE) mission concept is designed to address these challenges by tracking changes in Antarctic ice shelves using a satellite positioned in a highly elliptical orbit. The mission employs a Synthetic Aperture Radar (SAR)- equipped 12U-class small satellite to effectively monitor designated areas of interest (AOI) over a nominal two-year mission period.

The proposed mission utilizes a single-satellite-single-maneuver (SSSM) configuration to reduce the overall mass of the satellite while minimizing the Δv budget, thereby maintaining the possibility of accessing a high-inclination orbit without any plane-change maneuvers, thus maximizing polar region observation capability. Synthetic Aperture Radar (SAR) was selected as the primary scientific payload for the satellite to collect measurements of ice shelves for its ability to deliver high-resolution imagery in all-weather, day-and-night conditions, ensuring reliable coverage of Antarctic ice shelves. The radar payload features a 30° field of view to maximize the swath exceeding 400km during each pass.

To extend the observation time, the spacecraft is placed on a Molniya orbit with an inclination of 63.4°. It provides over 75% of the mission lifetime worth of observation window dedicated to Antarctic observations. The AICE mission demonstrates the feasibility of a single-satellite, single-maneuver spacecraft with SAR-enabled imagery, enabling sustained monitoring of the Antarctic region in highly elliptical orbits. The approach highlights a scalable and efficient solution for earth observation and information-gathering missions in long-term climate modeling, polar science, and the understanding of ice-sheet dynamics.

Introduction: Dust generation during lunar regolith excavation presents a major challenge for sustained surface operations, with implications for mechanical wear, optical degradation, thermal control, and crew safety. Most current excavation approaches address dust through mitigation techniques applied after particle liberation. In this work, we investigate an alternative strategy focused on dust prevention by design, using a staged excavation architecture intended to limit particle release at the source during material interaction.

System Design: We present the design of a dual-stage excavation and containment subsystem developed as the core functional element of a small-scale experimental platform. The architecture integrates material engagement, controlled internal transport, and temporary storage within a single enclosed cylindrical volume. This configuration is intended to minimize exposure of disturbed regolith to the surrounding environment during insertion and excavation, thereby reducing opportunities for particle entrainment and dispersion.

Experimental Methods: Preliminary experimental testing was conducted in open-air conditions using LMS-1E lunar regolith simulant. The excavation subsystem was mounted on a fixed test jig to isolate excavation behavior from vehicle dynamics, vibration, and wheel–terrain interactions. Dust dispersion was evaluated using gravity-collected particles captured on adhesive sampling pads placed at fixed locations around the excavation zone. Following each test, sampling pads were photographed and weighed to estimate relative dust deposition patterns. Ambient humidity was not controlled during testing.

Results and Discussion: Observations indicate reduced visible dust during both insertion and excavation phases, with dust deposition patterns suggesting localized particle release and limited spatial dispersion. Collected particles on sampling pads were concentrated near the excavation interface, consistent with the staged excavation hypothesis. While the results are preliminary and qualitative, they support the potential of staged excavation architecture as a viable approach for reducing dust generation during lunar regolith operations.

Space and rocket-related projects are notoriously expensive, with costs that often exceed initial budgets, especially for government-funded projects. These high costs pose a substantial barrier to expanding the capabilities of space exploration, satellite deployment, and related scientific research. To overcome these challenges, this study presents the optimization of a two-stage rocket for low Earth orbit (LEO) at a maximum altitude of 450 km and a 300 kg payload, focusing on aerodynamic and propulsion optimization to enhance fuel efficiency.

A multidisciplinary framework was applied, incorporating propulsion system analysis, and thermodynamic properties of the rocket nozzles using NASA’s Chemical Equilibrium with Applications (CEA) code. The Computational Fluid Dynamics (CFD) simulations were conducted in SolidWorks to refine the rocket's aerodynamic profile by optimizing fin geometries. The nozzle geometry was refined using Rao’s method, with MATLAB calculations applied to determine the optimal nozzle expansion ratio. NASA’s General Mission Analysis Tool (GMAT) was utilized to perform trajectory optimization and propellant mass calculations. The nozzle performance was validated through benchmarking against comparable-class small-lift launch vehicles.

The optimized launch vehicle achieves a total lift-off mass of 13,000 kg, including 11,200 kg of propellant and a 300 kg payload. The first stage produces 235 kN of thrust with a burn time of 155 s and a specific impulse of 265 s, while the second stage delivers 25 kN of thrust over 350 s with a specific impulse of 340 s. The combined two-stage propulsion system provides a total ΔV of 13.71 km/s, enabling a final orbital altitude of approximately 400 km. These findings contribute to more sustainable two-stage propulsion systems by enhancing fuel efficiency and sustainability in small-lift launch vehicles.

Space-based artificial intelligence (AI) is advancing rapidly with compute efficiency rapidly becoming a critical factor in measuring system capabilities. This abstract analyzes AI compute efficiency—measured in floating-point operations per second per kilogram (FLOPS/kg)—across platforms from 3U CubeSats (~4 kg) to 1000 kg satellites. Historically, larger spacecraft relied on radiation-hardened processors that had very limited compute (a couple hundred MIPs). Recent advances in edge compute have led to the ability of nanosatellites to have gigaflop to teraflop compute capabilities. This comparison of onboard edge AI compute will evaluate the tradeoff with size and compute, demonstrating the closing gap of FLOPS/kg. Space-based missions often evaluate design trade-offs such as form factor power, thermal management, and compute architecture; this work seeks to find the appropriate compute solution for workloads and then compare those to missions capable of running those loads. Early benchmarks show small-satellite GPUs achieving ~14× speedups over legacy processors. Overall, low-mass platforms in LEO are approaching the AI performance per mass of larger systems, enabling new autonomous capabilities and specialized compute workloads. At the end of this work, sample workloads for missions will be explored and will demonstrate how multiple satellites can autonomously carry out larger missions. This work seeks to demonstrate that AI capabilities including increased autonomy and onboard edge computer vision are possible on the smallest space-based platforms.

Decarbonizing aircraft transport, such as aircraft, is becoming a central priority in global efforts to reduce greenhouse gas emissions and meet long-term climate targets. This study evaluates the technical and environmental performance of hydrogen fuel-cell propulsion as an alternative to conventional jet fuel in commercial aviation. The analysis examines key aircraft design requirements, including the integration of liquid hydrogen storage tanks, fuel-cell power systems, cryogenic handling components, and electric propulsion units. It also considers the airport-side needs for hydrogen production, liquefaction, storage, and refueling, highlighting the importance of coordinated infrastructure planning for future deployment.

An environmental assessment indicates that hydrogen fuel-cell aircraft can eliminate in-flight CO₂ emissions and substantially reduce other pollutants, supporting cleaner operations and improved air quality around airports. From a technical standpoint, fuel-cell propulsion provides high energy efficiency, reduced mechanical complexity, and low noise levels, making it particularly suitable for short- and medium-range aircraft segments where electric propulsion architectures are more readily implemented.

Overall, the findings emphasize the strong potential of hydrogen fuel-cell systems to contribute to aviation decarbonization. The study offers practical insights for aircraft manufacturers, airport planners, and policymakers seeking to enable the transition toward zero-emission air transport and guide future development pathways for hydrogen-powered aviation.

The rapid expansion of satellite constellations has fundamentally transformed space operations, resulting in unprecedented volumes of onboard data and increasing dependence on limited downlink capacity and ground-based processing. This traditional ground-centric paradigm introduces latency, scalability challenges, and operational inefficiencies, particularly for time-critical applications such as anomaly detection, Earth observation, and constellation-level coordination. As the number of satellites continues to grow, these limitations pose significant risks to the sustainability and responsiveness of future space systems.

This paper proposes an edge AI-enabled framework for on-orbit intelligence that shifts key decision-making processes from ground stations to the satellites themselves. Lightweight machine learning models are deployed onboard to perform real-time data filtering, prioritization, and anomaly detection, allowing only high-value information to be transmitted to Earth. By reducing unnecessary data transmission, the proposed approach alleviates communication bottlenecks while improving operational agility.

A conceptual system architecture is presented to illustrate how edge AI can be integrated into resource-constrained space environments. Design considerations such as power limitations, radiation exposure, fault tolerance, and model update strategies are discussed to highlight practical deployment challenges. The framework emphasizes scalability and resilience, making it suitable for large and heterogeneous satellite constellations.

This study demonstrates how relocating intelligence from ground control to orbit can enhance system autonomy, reduce downlink dependency, and support more sustainable space operations. By advancing the digitalization and autonomy of space systems, this work contributes to the development of next-generation aerospace architectures and provides actionable insights for AI-enabled satellite constellation design.

This project deals with the numerical analysis of a composite cantilever beam that represents a section of a helicopter propeller blade. The analysis is carried out using ANSYS software, with the beam modeled using Fiber-Reinforced Polymer materials such as Carbon Fiber-Reinforced Polymer (CFRP) and Glass Fiber-Reinforced Polymer (GFRP). Since helicopter blades are usually pre-twisted to improve their aerodynamic performance, this study considers both the pre-twisted geometry and the anisotropic nature of composite materials. Modal analysis is performed to understand the natural frequencies and vibration modes of the beam.

Torsional vibrations are especially important in rotating blade structures, as they can lead to problems such as flutter, stall-induced vibrations, and structural instability. The interaction between axial forces and torsional motion, known as tension–torsion coupling, is examined to understand effects like blade untwisting and torsional stiffening. These phenomena are important in modern rotor blade design, where passive twist control is achieved through proper material tailoring.

The finite element model includes bending, torsion, shear deformation, and material directionality to accurately capture the dynamic behavior. The results show that pre-twist and material anisotropy significantly influence the vibration response. Overall, this study highlights how composite materials and structural tailoring can be effectively used to improve vibration control and performance in helicopter rotor blades.

The rapid increase in satellites and spacecraft has led to a critical rise in orbital debris, posing severe risks to active missions and long-term sustainability in space. Defunct satellites, spent rocket stages, and collision fragments threaten to trigger cascading collisions, making active debris mitigation an urgent priority. This project investigates a space-based laser debris mitigation system as a proactive solution to reduce orbital debris hazards.

The proposed system employs high-powered lasers mounted on space-based platforms equipped with precision pointing, advanced optics, and real-time tracking technologies. Unlike ground-based systems, space deployment eliminates atmospheric interference and enables direct access to debris across multiple orbital regimes, including LEO, MEO, and GEO. The operational principle involves directing focused laser pulses at debris surfaces to induce localized ablation, generating a recoil force that alters the object’s velocity and trajectory. This controlled perturbation enables orbital decay or relocation to less congested regions.

Integrated debris tracking, adaptive control algorithms, and optimized laser parameters ensure effective engagement across a wide range of debris sizes and materials. The system’s versatility allows mitigation of both large trackable objects and smaller high-risk fragments.

Key challenges include high power demand, energy storage, thermal management, system integration, and international regulatory concerns related to the dual-use nature of directed-energy technologies. Future work will focus on improving laser efficiency, compact power systems, advanced tracking algorithms, and simulation-based validation, alongside international collaboration.

Overall, space-based laser debris mitigation offers a scalable and effective approach to enhancing orbital safety and ensuring the long-term sustainability of space operations.

The current research aims to investigate the structural deformation, equivalent von Mises stress, and safety factor outcomes of a simplified jet trainer aircraft wing using a fluid–structure interaction (FSI) approach and optimize the structure for safe flight without lowering the structural safety margin of 1.2. The wing geometry is designed in the Ansys Design Modeler, and Aluminum alloy 2024 T3 and Aluminum alloy 7075 T6 are assigned as the material of the wing. The pressure distribution on the wing is calculated from the commercial software code Ansys Fluent and, later on, coupled with static structural analysis to solve the FSI problem. Experimental pressure coefficient data of the Onera M6 aircraft wing, tested in the NASA laboratory, is validated using Ansys Fluent. Keeping an angle of attack of 3⁰, the Mach number is varied from 0.5 to 0.8, and it was found that increasing the Mach number would increase the equivalent von Mises stress drastically, from 61.946 MPa to 236.52 MPa, passing the safety margin of the yield stress of 315 MPa. In addition, keeping the Mach number constant at 0.8 and changing the angle of attack from 0⁰ to 12⁰ would result in a rise in equivalent stress up to 411.33 MPa in linear analysis, which is higher than the yield stress, suggesting the potential plastic failure of the wing. Considering the maximum Mach number of 0.8 and angle of attack of 8⁰, an optimization is proposed to check how the thickness of the skin, ribs, and spars can be varied to bring down the stress generated on the root of the wing. A response surface optimization was conducted for satisfying the margin of safety for the wing.