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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 253 records · Page 14

Flight Path Control Error Analysis for the Helioswarm Observatory

The HelioSwarm Observatory requires specific geometries be formed by the nine satellites in the swarm to resolve different scales of solar wind turbulence. Maneuver execution and state estimation drive flight path control errors that could disrupt the swarm geometry. Using a Monte-Carlo analysis, flight path control errors for dispersed trajectories were generated and the impact to science performance and other mission constraints evaluated. The results highlight the unique aspects of swarm-type multi-satellite missions in terms of maneuver planning and error tolerance.

Swarm↗

Optimization Algorithm for Criticality Experiment Design Using Whisper

Many criticality experiments performed to aid in nuclear data evaluation are designed to maximize the sensitivity of the system’s effective neutron multiplication factor to a certain nuclide reaction pair over an energy region of interest. This is typically done by evaluating possible designs in a transport code such as MCNP and selecting the one with the highest desired sensitivity. A designer has many tools to try to maximize this sensitivity such as different moderators, reflectors, fuels, and geometries. This balancing act of identifying a critical and maximally sensitive system become very computationally expensive as more variables are added and higher precisions are desired. In order to identify these optimal configurations more efficiently a Particle Swarm Optimization (PSO) algorithm coupled with MCNP has been developed by Los Alamos National Laboratory (LANL). This algorithm has been used to design two upcoming criticality experiments that will be performed at the National Criticality Experiments Research Center (NCERC), located at the Nevada National Security Site, and operated by LANL, the only general-purpose critical experiments laboratory in the United States. PSO uses a population (swarm) of candidate solutions (particles) on a search space of dimensions such as moderator and reflector thicknesses or enrichments and concentrations. These particles move around the search space from generation to generation according to simple rules. Eventually, the swarm converges on the configuration that is both critical and maximally sensitive to a piece of nuclear data. PSO is well suited for criticality experiments as the algorithm is agnostic to the underlying physics, meaning it is effective on many different experimental setups. This algorithm has been modified to maximize the nuclear data similarity coefficient between an application case and an experiment aimed at replicating the application case using WHISPER, a nuclear criticality safety analysis tool. This allows for the efficient design of critical experiments informed by nuclear data sensitives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Collective behavior of “flexicles”

In recent years the functionality of synthetic active microparticles has edged even closer to that of their biological counterparts. However, we still lack the understanding needed to recreate at the microscale key features of autonomous behavior exhibited by microorganisms or swarms of macroscopic robots. In this study, we propose a model for a three-dimensional deformable cellular composite particle consisting of self-propelled rod-shaped colloids confined within a flexible vesicle—representing a superstructure we call a “flexicle” that couples particle deformation to the internal dynamics of the internal active components. Using molecular dynamics simulations, we investigate the collective behavior of dense systems composed of many flexicles. We show that individual flexicles exhibit shape changes upon collisions with other flexicles that lead to rearrangements of the internal active rods, which slows flexicle motion. This shape deformability gives rise to a diverse set of motility-induced phase separation phenomena and the spontaneous flow of flexicles reminiscent of the migration of cells in dense tissues. Our findings establish a foundation for designing responsive, cell-like active particles and developing strategies for controlling swarm migration and other autonomous swarm behaviors at cellular and colloidal scales.

Science & Technology - Other Topics↗

Planet formation - Mechanism of early growth

Experiments in vacuum (approx. 0.5 to 1 mbar) and in air quantify mechanics of collisions, rebound, and fragmentation at low velocities (1-50 m/sec), under the conditions usually postulated for the preplanetary environment in the primitive solar nebula. Such collisions have been little studied experimentally. Contrary to widespread assumptions, accretionary growth of the largest meteoroid- and asteroid-sized bodies in a given swarm results spontaneously from the simple mechanics of these collisions, without other ad hoc sticking mechanisms. The smaller bodies in the swarm are less likely to grow. Granular surfaces form, either by gravitational collapse of dust swarms or by rapid formation of regolith surfaces on solid planetesimals; these surfaces strongly promote further growth by retarding rebound. Growth of large bodies increases modal collision velocities, causing fragmentation of smaller bodies and eventual production of interstellar dust as a by-product of planetesimal interactions.

Hartmann, W. K.↗

Formation of the terrestrial planets

Two growth mechanisms are identified for the development of the terrestrial planets: (1) gravitational instability leading to a collapse, and (2) gravitational accumulation caused by two-body collisions and coherence. The presence of a dynamically-significant gas phase would not affect either mechanism. Theoretical expressions are presented for the production of giant gaseous protoplanets by gravitational instability within a central dust layer. Gravitational accumulation is discussed with reference to the accumulation of planetesimals from a gas-free circumsolar swarm of bodies. Numerical simulations are given for the early stages of accumulation. The Safronov steady-state velocity is considered, noting that the competition between mutual collisional damping and gravitational acceleration by the members of a solar swarm yields a steady-state velocity distribution where the mean velocity is comparable to the escape velocity of the largest body. A time scale for accumulation is postulated on the basis of the radial distribution of a swarm of non-accreting bodies of equal size. The simultaneous gas-free accumulation of several terrestrial planets is noted. Attention is also given to growth mechanisms in gas-rich interplanetary media.

Wetherill, G. W.↗

A circumterrestrial compositional filter

A major question about the Moon is its under abundance of iron. The proposal of whether a metal-silicate fractionation of heliocentric bodies could be achieved through collisional interactions with a circumterrestrial swarm is examined. The whole scenario works only if there is a way to maintain the hypothesized circumterrestrial swarm, which otherwise would collisionally diffuse on a time scale of 100 yr (much of it collapsing on the Earth); the source of angular momentum to maintain the swarm remains a mystery.

Chapman, C. R.↗

Accretion and evolution of solar system bodies

We use a combination of analytical and numerical methods to study dynamical processes involved in the formation of planets and smaller bodies in the solar system. Our goal was to identify and understand critical processes and to link them in a numerical model of planetesimal accretion. We study effects of these processes by applying them in the context of the standard model of solar system formation, which involves accretion of the terrestrial planets and cores of the giant planet from small planetesimals. The principal focus of our research effort is the numerical simulation of accretion of a swarm of planetesimals into bodies of planetary size. Our computer code uses a Monte Carlo method to determine collisional interactions within the swarm. These interactions are not determined simply by a relative velocity, but rather by explicit distributions of keplerian orbital elements. The planetesimal swarm is divided into a number of zones in semimajor axis, which are allowed to interact. The present version of our code has the capability of following detailed distributions of size, eccentricity, and inclination in each zone.

Weidenschilling, S. J.↗

NanoSat constellation mission design

The NanoSat constellation concept mission proposes simultaneous operation of multiple swarms of as many as 22 identical 10 kg spacecraft per swarm. The various orbits in a NanoSat swarm vary from 3x5 to 3x42 R(sub e) in geometry. In this report the unique flight dynamics issues of this constellation satellite mission design are addressed. Studies include orbit design, orbit determination, and error analysis. A preliminary survey determined the orbital parameters that would yield a 100 minute shadow condition maximum while providing adequate ground station access for three ground stations.

Concha, Marco↗

NanoSat Constellation Mission Design

The NanoSat constellation concept mission proposes simultaneous operation of multiple swarms of as many as 22 identical 10 kg spacecraft per swarm. The various orbits in a NanoSat swarm vary from 3x12 to 3x42 R(sub e) in geometry. In this report the unique flight dynamics issues of this constellation satellite mission design are addressed. Studies include orbit design, orbit determination, and error analysis. A preliminary survey determined the orbital parameters that would limit the maximum shadow condition while providing adequate ground station access for three ground stations.

Concha, Marco↗

A Collisional Algorithm for Modeling Circumstellar Debris Disks

Many planetary systems harbor circumstellar disks of dust and planetesimals thought to be debris left over from planet formation. These debris disks exhibit a range of morphological features which can arise from the gravitational perturbations of planets. Accurate models of these features, accounting for the interactions of the particles in a disk with each other and with whatever planets they contain, can act as signposts for planets in debris disks that otherwise could not be detected. Such models can also constrain the planet's mass and orbital parameters. Current models for many disks consider the gravitational and radiative effects of the star and planets on the disk, but neglect the morphological consequences of collisional interactions between the planetesimals. Many observed disk features are not satisfactorily explained by the current generation of models. I am developing a new kind of debris disk model that considers both the gravitational shaping of the disk by planets and the inelastic collisions between particles. I will use a hybrid N-body integrator to numerically solve the equations of motion for the particles and planets in the disk. To include the collisional effects, I begin with an algorithm that tests for collisions at each step of the orbit integration and readjusts the velocities of colliding particles. I am adapting this algorithm to the problem at hand by allowing each particle to represent a "swarm" of planetesimals with a range of masses. When the algorithm detects an encounter between swarms, two or three swarms are produced to approximate the range of possible trajectories of the daughter planetesimals. Here I present preliminary results from my collisional algorithm.

Nesvold, Erika↗

Thermal Modeling in Support of the Edison Demonstration of Smallsat Networks Project

NASA's Edison program is intending to launch a swarm of at least 8 small satellites in 2013. This swarm of 1.5U Cubesats, the Edison Demonstration of Smallsat Networks (EDSN) project, will demonstrate intra-swarm communications and multi-point in-situ space physics data acquisition. In support of the design and testing of the EDSN satellites, a geometrically accurate thermal model has been constructed. Due to the low duty cycle of most components, no significant overheating issues were found. The predicted mininum temperatures of the external antennas are low enough, however, that some mitigation may be in order. The development and application of the model will be discussed in detail.

Coker, Robert F.↗

Thermal Modeling in Support of the Edison Demonstration of Smallsat Networks Project

NASA's Edison program is intending to launch a swarm of at least 8 small satellites in 2013. This swarm of 1.5U Cubesats, the Edison Demonstration of Smallsat Networks (EDSN) project, will demonstrate intra-swarm communications and multi-point in-situ space physics data acquisition. In support of the design and testing of the EDSN satellites, a geometrically accurate thermal model has been constructed. Due to the low duty cycle of most components, no significant overheating issues were found. The predicted mininum temperatures of the external antennas are low enough, however, that some mitigation may be in order. The development and application of the model will be discussed in detail.

Coker, Robert↗

Introducing The Lunar Autonomous PNT System(LAPS) Simulator

In this paper we introduce a software simulator that has been used to develop an architecture for a low-cost Lunar Autonomous Position, Navigation and Time (PNT) System, LAPS. LAPS is a conceptual architecture for providing autonomous PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities.

Benjamin Hagenau↗

Starling Animation

NASA’s Starling mission is advancing the readiness of various technologies for cooperative groups of spacecraft – also known as distributed missions, clusters, or swarms. Starling will demonstrate technologies to enable multipoint science data collection by several small spacecraft flying in swarms. The six-month mission will use four CubeSats in low-Earth orbit to test four technologies that let spacecraft operate in a synchronized manner without resources from the ground. The technologies will advance the following capabilities. • Network Communication • Cluster Flight Control • Relative navigation • Distributed Spacecraft Autonomy The Starling mission will test whether the technologies work as expected, what their limitations are, and what developments are still needed for CubeSat swarms to be successful. This animation illustrates Starling mission operations, offering an overview of each technology being demonstrated.

Howard N Cannon↗

Flight Path Control Error Analysis for the Helioswarm Observatory

The HelioSwarm Observatory requires specific geometries be formed by the nine satellites in the swarm to resolve different scales of solar wind turbulence. Maneuver execution and state estimation drive flight path control errors that could disrupt the swarm geometry. Using a Monte-Carlo analysis, flight path control errors for dispersed trajectories were generated and the impact to science performance and other mission constraints evaluated. The results highlight the unique aspects of swarm-type multi-satellite missions in terms of maneuver planning and error tolerance.

Stephen West↗

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As lunar missions increase in complexity inspired by NASA’s Artemis Program, they will require reliable and sufficient capability of the Position, Navigation, and Timing (PNT) system to support their scientific objectives. In addition, NASA's Commercial Lunar Payload Services (CLPS) program initiates the proliferation of public and private exploration partnerships using small satellites from commercial and private organizations, expanding traditionally confined low Earth orbit to be used for missions beyond geosynchronous orbit (Zucherman et al., 2022). Therefore, the Lunar PNT system is also required to provide navigation services compatible with the smaller platforms being sent by the public and private sectors, like CubeSats. However, traditional approaches to deep space missions’ navigation based on ground radio facilities have difficulties in providing sufficient support for the increasing number of users and communication at a distance from the Earth (Kaplev et al., 2022). In particular, the existing Lunar navigation technologies such as weak signal global positioning system (GPS) and deep space network (DSN) are not able to ensure operations of the upcoming small-scale Lunar missions due to their limitations in localization performance as well as capacity aspects. Another way to provide Lunar PNT service is to create a dedicated Lunar global navigation satellite system (GNSS) constellation, like GNSS systems on Earth. Space agencies like NASA, ESA, and JAXA are now developing the lunar communications relay and navigation systems (LCRNS) and Lunar navigation satellite systems (LNSS). In their systems, satellites will be deployed in moon orbits to provide the communication, positioning, navigation, and timing (CPNT) service at the lunar south pole region where the Artemis base camp will be expected (Murata et al., 2022). Meanwhile, common challenges considered in lunar PNT research arise from poor geometry of the terrestrial GNSS satellites when seen from the lunar user, highly perturbed lunar orbits, and limitations in power, size, and cost of the equipment on lunar satellites (Iiyama et al., 2023). It is also not clear if there will be enough Lunar users to support the cost and resources this would require as the Low-cost surface missions may not be able to support the large power, mass, and weight requirements that these navigation solutions entail (Niemoeller et al., 2022). As an alternative, existing Lunar science and exploration assets could be used to create a low-cost, autonomous, ad-hoc, and on-demand mission-centric Lunar PNT swarm capable of providing PNT services to these low-cost lunar missions (Hagenau et al., 2021). Introducing the non-dedicated and ad-hoc Lunar navigation constellation gives a way to provide PNT services on-demand. The non-dedicated swarm assets of Lunar constellations are designed to localize themselves with minimal interaction with Earth by adding cooperative autonomous localization to lunar missions, freeing up valuable bandwidth and ground segment resources. An autonomous localization of Lunar constellations is based on the concept of the decentralized PNT system with a distributed extended Kalman filter (DEKF) approach to state estimation for minimal onboard operating costs. In the distributed data processing algorithm, computation is broken down and assigned to each satellite, resulting in a considerably decreased computational amount while maintaining the accuracy of the orbit ephemeris and clock offsets as the result of centralized data processing (Wen et al., 2019). The DEKF requires spacecraft to perform two-way ranging operations with each other to communicate simultaneously, leveraging neighbor two-way intersatellite link (ISL) measurements such as pseudoranges to, and relative velocities between, visible satellites as sensor values (Frank et al., 2021). The Lunar autonomous PNT simulation (LAPS) demonstrated the feasibility of orbital asset localization among ad-hoc Lunar small-sat constellations based on the DEKF in Hagenau et al. (2021) and evaluated the matching algorithm proposed by Frank et al. (2021) in scheduling position estimation updates. In previous papers, all assets and measurements are assumed to be always available without consideration of the impact of intermittent and permanent communication failure. This study presents localization performance with increasing levels of network degradation for swarm assets and users to demonstrate the robustness of the decentralized Lunar PNT service in more realistic scenarios. Main issues arising from communication failure include spacecraft permanent or transient loss, antenna failures, message delays, etc. We tested four possible reasons for network degradation for 7 days in 21 satellites frozen with an altitude of 5500 km, evenly spaced around 3 circular, 40 inclination orbital planes where each spacecraft has two directional antennas. As anchor nodes with an independent estimate of their position are required in the DEKF approach, two ground nodes in each pole and one node in the gateway were implemented in the simulation. First, the most probable failure scenario involves the loss of a single spacecraft due to solar interference and technical malfunctions of the assets. Losing the availability of a single spacecraft means losing the two-way ISL measurement of the asset in the DEKF update. In order to provide the best possible quality of PNT service with limited time and resources, the distributed Lunar constellations must schedule the communication activities. The scheduler leverages mixed-integer linear programming (MILP) for the coordination and scheduling of the desired “as-needed” localization service (Niemoeller et al., 2022). We assume the scheduler has completely excluded the spacecraft information before the DEKF update in the failure scenario. When a random spacecraft has been turned off at a specific time, the robustness of the autonomous Lunar PNT system is evaluated. The simulation results give an 11.5% degradation in median position accuracy compared to the idealized performance excluding the asset loss. Second, a large number of assets may vanish due to major hardware problems or meteor strikes around the moon. A multiple spacecraft loss can degrade the localization performance very fast by losing the communication ability to do cross-plane measurements and in-plane measurements in a 3-plane constellation. When the matching-based scheduler is aware of ISL availability, we investigate a large number of in-plane and cross-plane asset vanishments both in close proximity and equally spaced throughout the orbital plane. According to the simulations, the loss of in-plane measurements gives 40.2% degradation while cross-plane measurements degrade 50.5% of asset localization performance among available assets. Therefore, it is concluded that cross-plane measurements are more important in improving the position estimation accuracy. Third, spacecraft failure information can be lost due to the internal message delay, resulting in the DEKF update scheduler to solve the matching problem with unavailable assets. The DEKF update cycle is comprised of network setup, communication, and computations where a global broadcast network and a 2-way ISL network setup take 6 minutes in total (Frank et al., 2021). Once the broadcast network successfully transmits and receives information, a random spacecraft may lose its availability right before solving the matching problem. This means the matching solution is no longer optimal, resulting in degradation in the localization performance. A numerical assessment shows the matching-based scheduler with knowing failure holds 11.5% of position accuracy degradation, whereas the scheduler without knowing failure gives 34% degraded localization performance without asset loss. Fourth, a transient loss of a single or multiple spacecraft may occur due to their antenna outages. After losing the two-way ISL availability for a few DEKF update cycles, the availability of spacecraft can easily be recovered as their states have been independently updated using measurements from anchor nodes. It is likely that the longer failure will result in worse localization performance. We have tested the transient failure of a random single asset for 30 min in the simulation, which is losing 3 update cycles in the DEKF system. From the simulation results, the position accuracy has been degraded to 4.84% which is better than the degraded localization performance of 11.5% from the permanent loss scenario among available assets. In conclusion, the autonomous Lunar PNT system based on the DEKF approach shows the ability to maintain resilience and robustness in the possible communication failure scenarios, ensuring that localization accuracy is preserved across various network degradation and outages. Future studies on investigating user localization performance near the South Pole and the broadcast network system will be continued in the following months.

Yeji Kim↗

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.

Yeji Kim↗

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗