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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Optimization of the Lucy Interplanetary Trajectory via Two-Point Direct Shooting

Lucy is NASA’s next Discovery-class mission and will explore the Trojan asteroids in the Sun-Jupiter L4 and L5 regions. This paper details the design of Lucy’s interplanetary trajectory using a two-point direct shooting transcription, nonlinear programming, and monotonic basin hopping. These techniques are implemented in the Evolutionary Mission Trajectory Generator (EMTG), a trajectory optimization tool developed at NASA Goddard Space Flight Center. We present applications to the baseline trajectory design, Monte Carlo analysis, and operations.

Lucy↗

Missions to Triton and Pluto using a Hopper Vehicle with In-Situ Refueling

The Triton Hopper is a NASA Innovative Advanced Concepts (NIAC) project to design a mission to not merely land, but repeatedly fly across the surface of Triton, utilizing the volatile surface ices (primarily nitrogen) as propellant for a radioisotope-heated thermal rocket engine to launch across the surface and explore all the moon's varied terrain. An engineering design study of the vehicle and mission was done. With a calculated range of 20 km per hop, equator-to-pole mobility can be achieved over a primary mission duration of 2 years. Using Nuclear Electric Propulsion for the transfer vehicle, the same concept can be applied for a mission to the surface of Pluto.

Landis, Geoffrey A.↗

Global Search and Trajectory Optimization in Interplanetary and Cislunar Space

This presentation describes active research and development in interplanetary and cislunar trajectory optimization and global search at NASA Goddard Space Flight Center. Two point and parallel direct shooting transcriptions are described, along with monotonic basin hopping and batch seed sharing. Applications to the Lucy mission are presented, as well as a variety of other interplanetary and cislunar examples.

Englander, Jacob↗

Optimization of the Lunar Icecube Trajectory Using Stochastic Global Search and Multi-Point Shooting

Lunar IceCube is a 6U cubesat that will launch on NASA’s Artemis 1 mission in 2021. Lunar IceCube will separate from Artemis 1 shortly after trans-lunar injection (TLI) and travel to its science orbit about the moon using its Busek Ion Thruster 3 (BIT-3) propulsion system. This paper describes a technique to rapidly design Lunar IceCube trajectories using the monotonic basin hopping (MBH) stochastic global search algorithm, along with low- and high-fidelity multi-point shooting transcriptions. This technique allows the Lunar IceCube team to rapidly adapt to changing initial conditions, spacecraft properties, and operational constraints.

optimization↗

Terrestrial Unmanned Roving Vertical Take-off and Landing (TURVTOL)

As the uses for autonomous rovers and drones has increased with their variability and utility,a fundamental gap has emerged - one which melds multi-modal capabilities into a singular unit. This project aims to fill that gap with the introduction of a multi-modal unmanned vehicle concept that can traverse ground quickly, hop or fly over obstacles and hazardous areas, and operate without the use of GPS or a human in the loop. The 2020 NASA Academy at Langley has developed a first iteration conceptual design of such a vehicle. This design has proven to be feasible through analyses confined to simulated environments.

VTOL↗

Lunar Relay Coverage Analysis for RF and Optical Links

This paper describes our effort in searching different lunar relay architectures and assessing their coverage performance and other pros and cons for RF and optical links. Regarding RF links, we considered three notional lunar relay architectures, all communicating with the three sites of the Deep Space Network (DSN): Goldstone, California; Canberra, Australia; and Madrid, Spain: 1) A constellation of three relay orbiters: two at the Polar frozen elliptical orbits, and one at an equatorial circular orbit. 2) One relay orbiter in a 74-day Lissajous orbit at Earth-Moon Lagrange Point L2. 3) One relay orbiter in a 14-day Lunar distance retrograde orbit. Regarding optical link, we considered a notional multi-hop relay architecture that consists of one relay orbiter in a 74-day Lissajous orbit at Earth-Moon L2 (as in architecture #2 in the RF case), three Near-Earth relay satellites in geosynchronous orbit at longitudes 187° E, 110° E, and 347° E, and three ground stations at White Sands (US), Guam (US), and Tenerife (Spain). We introduce the additional constraints of Sun-“Earth”Probe (SEP) angle for return links, and Sun-Probe-“Earth” (SPE) angle for forward links. SPE and SPE angles determine the amount of sunlight (noise) that goes into the detector of the telescope, thus affecting the capacity of an optical link.

Lee, Charles↗

Applying the Cognitive Space Gateway to Swarm Topologies

NASA's future vision for interplanetary networking includes a lunar network, Cube Satellite (CubeSat) constellations, and deep space robotic missions, comprising what could be viewed as a network of networks. Delay-tolerant networking (DTN) architecture and protocols provide a standard network layer among these varying scenarios and mitigate many challenges of the space environment, such as long delays, unplanned service interruptions, and asymmetric links. The Cognitive Space Gateway (CSG) is a routing method in a DTN architecture that uses spiking neural networks as the learning element to optimize routing decisions in a complex environment. This work aims to further develop cognitive networking technologies in several critical areas, including DTN, the CSG algorithm, CubeSat swarm topologies, and cloud services. To test the algorithm in a realistic scenario, the emulated network topology is based on a CubeSat swarm. The swarm may function as a mesh of nodes or as a hub-and-spoke network. An emulation environment will be built upon a commercial cloud service, such as Amazon Web Services (AWS) Elastic Compute Cloud. The cloud environment may enable a flexible, lower maintenance approach versus a multi-hop network based in a physical laboratory. The cloud platform will provide a secure environment allowing for collaboration among government and academic entities.

Ricardo Lent↗

Numerical Modeling and Design of Gaseous Propellant Acquisition System for the Triton Hopper

Triton, the largest moon around Neptune, is a captured Kuiper Belt Object with a dynamic rarified atmosphere, active geysers, and unique “cantaloupe” like terrain. Little is known about Kuiper Belt Objects in the scientific community with most of the information coming from Pluto. Currently, NASA is designing an unmanned probe to explore the atmosphere and surface of Triton. This vehicle is unique in that it repeatedly takes off and lands (hops) using nitrogen propellant collected from its surroundings on Triton. This paper presents preliminary conceptual system design and numerical modeling of the atmospheric collection process. Four concepts are presented: a cryocooler-based system, a pump-based system, a sublimation and pump-based system, and a cryocooler and sublimation system. Numerical modeling takes into account the mass and energy transfer between all the relevant nodes in the system and is able to calculate the amount of nitrogen ice collected and ice accumulation rate as a function of time for each concept. The models are ultimately used to assess the feasibility of traversing from equator to pole in under two years using a gaseous propellant acquisition system for the Hopper.

Hopper↗

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.

Zhe Wang↗

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.

Zhe Wang↗

Propulsive trajectory optimization to minimize surface contamination

MOTIVATION: We present an optimization technique for propulsive vehicles that autonomously minimizes contamination during surface approach and landing. In addition to short-range hoppers, the optimization technique is also fully applicable to traditional orbit-to-surface landers. This study addresses scenarios where surface alterations from propulsion events are counterproductive or hazardous to the mission objectives. This is of immediate interest for landers (whether human or robotic), that may rely on pristine soils collected in the immediate vicinity of landing sites to accomplish science investigations, mining, or ISRU surface operations. Such missions are averse to various surface-plume interactions such as thermal scoring, physical agitation, and contamination. The capability can be applied with minimal impact to the baseline mission concept. METHODS: Optimization algorithms have been developed to calculate descent trajectories and maneuvers, thrust magnitude, and attitude for various mission cases. These parameters are determined as an optimal solution when minimizing either fuel consumption, contamination deposited at the landing site, or some weighted combination of both. Among constraints imposed on the solution, we examined pitch rate, vertical takeoff and vertical landing (VTVL) requirements, size of the contamination zone, and minimum ground clearance during flight. This tool provides unique, non-intuitive solutions and can be a valuable resource for mission planners. RESULTS: A variety of agile trajectory solutions were obtained, each yielding different reductions in landing site contamination and corresponding to only modest increases in fuel consumption. Several optimal trajectories were obtained by varying the contamination weight in the fitness function. As expected, when the contamination weight is zero, the trajectory appears close to parabolic since the optimization scheme only attempts to minimize for fuel utilization, yielding essentially, the expected ballistic trajectory. Notably for contamination weights greater than zero, trajectory inflections are observed in the descent phase, which manifests as hovering or additional, mini “pseudo hops” before the final touchdown. A trajectory inflection is characterized by arresting the majority of the spacecraft vertical velocity component at a coordinate outside of the landing target, and without violating ground clearance constraints. FUTURE WORK: Our optimization technique is ready for laboratory or field demonstrations to validate the sophisticated maneuvering solutions obtained for fuel optimization and surface preservation. An appropriate testbed would validate the optimal guidance algorithms, the navigation system, and sensor suite by emulating vehicle flight in closed loop robotic tests. Critically, these algorithms could then be ported to flight software for implementation.

surface contamination↗

Spectral Single and Double Power-law Formation by Sequential Particle Acceleration in Flare Magnetic Islands

Spectral single and double power laws are common in high-energy phenomena, such as solar flares and solar energetic particles, including ground level enhancement events. It is not clear what determines the energy breaks and spectral indexes of these power laws. Here, we will describe a first-principles model of pitch-angle and energy distribution function evolution, which produces power laws and provides physical interpretation for such spectral features (Guidoni et al. 2022, ApJ). In this model, a prescribed fraction of particles sequentially “hops” between shrinking magnetic islands (accelerators) formed by flare reconnection. Each accelerator increases particles’ energies by a modest amount, but particles must visit only a few accelerators to increase their energies by orders of magnitude. Data from global magnetohydrodynamic simulations of an eruptive flare/coronal mass ejection provide ambient conditions for the evolving particle distributions. We will also describe the fully analytic method for forming and interpreting power laws, which requires only a few constrained physical parameters of the acceleration region and is independent of the acceleration model, as well as preliminary results extending the analytical model to the formation of double power laws.

S E Guidoni↗

Broadband Continuous Single-mode Tuning of a Short-cavity Quantum-cascade VECSEL

Changing the length of a laser cavity is a simple technique for continuously tuning the wavelength of a laserbutis rarelyused for broad fractional tuning, with a notable exception of the diode laser VCSEL1,2. This is because, to avoid mode hopping, the cavity must be keptopticallyshort to ensure a large free-spectral-range (FSR) compared to the gain bandwidth of the amplifying material. Terahertz quantum-cascade (QC) lasers are ideal candidates for such a short cavity scheme as they demonstrate exceptional gain bandwidths (up to octave spanning) and can be integrated with broadband amplifying metasurfaces. We present such a QC-metasurface based vertical-external-cavity surface-emitting-laser (VECSEL) that exhibits over 20% continuous fractional tuning of a single laser mode. Such tuning is possible because the metasurface has sub-wavelength thickness which allows lasing on low-order Fabry-Pérot cavity modes. Good beam quality and high output power are simultaneously obtained.

Christopher A Curwen↗

Spectral Power-law Formation by Sequential Particle Acceleration in Multiple Flare Magnetic Islands

We present a first-principles model of pitch-angle and energy distribution function evolution as particles are sequentially accelerated by multiple flare magnetic islands. Data from magnetohydrodynamic (MHD) simulations of an eruptive flare/coronal mass ejection provide ambient conditions for the evolving particle distributions. Magnetic islands, which are created by sporadic reconnection at the self-consistently formed flare current sheet, contract and accelerate the particles. The particle distributions are evolved using rules derived in our previous work. In this investigation, we assume that a prescribed fraction of particles sequentially "hops" to another accelerator and receives an additional boost in energy and anisotropy. This sequential process generates particle number spectra that obey an approximate power law at mid-range energies and presents low- and high-energy breaks. We analyze these spectral regions as functions of the model parameters. We also present a fully analytic method for forming and interpreting such spectra, independent of the sequential acceleration model. The method requires only a few constrained physical parameters, such as the percentage of particles transferred between accelerators, the energy gain in each accelerator, and the number of accelerators visited. Our investigation seeks to bridge the gap between MHD and kinetic regimes by combining global simulations and analytic kinetic theory. The model reproduces and explains key characteristics of observed flare hard X-ray spectra as well as the underlying properties of the accelerated particles. Our analytic model provides tools to interpret high-energy observations for missions and telescopes, such as RHESSI, FOXSI, NuSTAR, Solar Orbiter, EOVSA, and future high-energy missions.

magnetic reconnection↗

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗

Deep Reinforcement Learning based Routing in an Air-to-Air Ad-hoc Network

This paper studies the Multiple Sources and Multiple Destinations (MSMD) routing problem in a dynamic Air-to-Air Ad-hoc Network (AAAN). We consider a spectrum limited scenario where multiple links have to share the same frequency channel so that co-channel interference becomes inevitable. As a result, routing decisions and spectrum access are coupled and must be jointly considered. This paper proposes a deep Q-learning based algorithm to find an optimal routing and channel selection strategy that minimizes the end-to-end communication delay. Specifically, under the assumption that only local information is available to every node, the Deep Q-Network (DQN) is trained offline to learn the optimal routing and channel selection strategy. After the trained DQN is implemented in every node, multiple relay nodes can simultaneously determine their next-hop relay and channel selections in real-time. Simulation results demonstrate the efficacy of our proposed algorithm.

AAAN↗

Reducing Landing Site Contamination Using 3-D Trajectory Optimization for Surface Hoppers

Rocket-powered vehicles utilizing Vertical Take-off Vertical Landing (VTVL) are a compelling alternative to surface rovers for exploring planetary and lunar bodies. These so called “hoppers” provide enhanced mobility for accessing locations difficult to reach, and over a wider region of the surface. However, contamination and plume interactions from rocket exhaust deposited at landing sites is anticipated since landing approaches are typically along a vertical direction during the final descent. Consequently, exhaust products may alter the surface chemistry, potentially confounding compositional analysis for samples collected in the vicinity of the landing site or jeopardize mining efforts. There has been no rigorous study on flight maneuvers that can mitigate plume-to-surface interactions. A multi-objective optimization tool has been developed to simulate propulsive hops on a planetary body and minimize both fuel consumption and site alterations. Trajectories are derived by multi-objective optimization and include solutions with significant reduction in contamination for a modest increase in fuel consumption. For these solutions, surface-to-surface propulsive transfer is demonstrated, but the method can also be modified for orbit-to-surface transfers (e.g., landers).

guidance↗