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At least 1,297 records · Page 72

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗

NASA NTRS1997

Mechanical Design of the Mars Pathfinder Mission

The Mars Pathfinder Mission was a great engineering achievement for the National Aeronautics and Space Administration (NASA) and the Jet Propulsion Laboratory (JPL) which built the Pathfinder Spacecraft and the Sojourner Rover. The mechanical design of the mission hardware was critical to the success of the complex entry sequence and landed operations.

Mars↗

NASA NTRSDate not supplied

Preliminary Design of a Downstream Processing System for Protein Production in Space

Biomanufacturing is a promising technology to convert in situ resources into essential products including enzymes, therapeutics, biopolymers and other chemicals required to support deep-space missions that may not be easily supplied or produced by alternative means. In addition to the biomass production operations, vital down-stream steps including biomass harvesting/concentration, cell lysis, protein capture and purification are needed to produce an application-ready product. Commercially available terrestrial processes commonly require complex, heavy equipment and highly trained operators, which are not practical in deep space environments. In this work, we aim to identify approaches required to produce an intracellular, His-tagged recombinant enzyme using E. coli at 1 L production scales within the constraints of a deep-space mission as a model use-case scenario. Based on extensive literature review and commercially available products, we identified candidate technologies and products that could be integrated for deep space biomanufacturing. Different preliminary designs were then compared in terms of total system impacts on up-mass, processing time, and consumables required. Our analysis indicated that a biomass concentrator would significantly reduce the processing time and consumables required for the overall system without a large increase in the total mass. We also identified viable technologies for other steps such as cell lysis and protein purification. Predictions from our trade study will be validated in the laboratory by testing the most promising products with the results used to optimize the design. This research will help transfer technology that is well developed on Earth to a space-ready format to produce biological products from a wide variety of microorganisms that can support deep-space missions.

Biomanufacturing↗

NASA NTRSDate not supplied

The Ring Current ENA Instrument on the NASA STORIE Mission

NASA has recently selected the Storm Time O+ Ring current Imaging Evolution (STORIE) mission to study the evolution of Earth’s ring current and the role of composition and dynamics during geomagnetic storms. STORIE addresses this inner magnetospheric science through the use of a Ring current Energetic Neutral Atom (RENA) instrument hosted on the International Space Station (ISS). This novel vantage point for ENA imaging has a number of scientific and implementation advantages. RENA is a high sensitivity remote sensing ENA imager and composition instrument with a field of view of 90 x 2 degrees, and an angular resolution of 2 x 2 degrees. The instrument aperture points zenith and its long dimension is oriented perpendicular to the ISS ram direction. As a result, RENA acts as a “push broom” imager building up a complete sky scan of the ring current in a single 90-minute ISS orbit. The instrument employs electrostatic optics along with a foil-MCP TOF x PHA x Delay-Line position measurement technique to resolve H and O energy spectra in the energy range 10-500 KeV for each look direction. Furthermore, it employs triple+ time and position coincidence to effectively reduce background noise from geocoronal and black sky UV as well as penetrating radiation. The abundant mass, power, and telemetry, resources of the ISS allow for large instrument aperture, very high sensitivity, complex data product and simplified operations, altogether contributing towards a high signal to noise (S/N) measurement.

Space Science↗

NASA NTRSDate not supplied

End-to-End Mission Design & Trajectory Optimization

The ability to compute end-to-end mission optimized trajectories is a critical component needed for the next generation of complex human spaceflight design and operations (Orion, HLS, Gateway, Mars). This project created a new interface for two of NASA’s trajectory tools: Copernicus and Genesis, enabling them to be used together for end-to-end mission design and optimization of all flight phases, including Earth ascent, lunar ascent, rendezvous, and lunar descent. This capability can also serve as a pathfinder for developing a future autonomous, onboard trajectory optimizer.

Software↗

NASA NTRS2023

Executive Summary for CIF22 Project: End-to-End Mission Design & Trajectory Optimization

The goal of this project was the integration of NASA's Copernicus and Genesis trajectory design tools to create a new capability for end-to-end mission design and optimization of all flight phases, including Earth ascent, lunar ascent, rendezvous, and lunar descent. This capability is a critical component needed for the next generation of complex human spaceflight design and operations (Orion, HLS, Gateway, Mars) and can serve as a pathfinder for developing a future autonomous, onboard trajectory optimizer. The result was the creation of a new Copernicus/Genesis plugin, which allows a Genesis trajectory (e.g., ascent or descent) to be incorporated into a Copernicus mission, enabling an end-to-end optimization. Inputs from Copernicus are sent to Genesis, which runs and produces output sent back to Copernicus. Thus, the full power of the Genesis tool is available in Copernicus and can be used for a wide variety of applications.

Jacob Williams↗

NASA NTRS2023

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA's Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA's primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA's Starling 1.0 satellites.

Caleb Ashmore Adams↗

NASA NTRSDate not supplied

End-to-End Mission Design & Trajectory Optimization

Software↗

NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST to reduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗

NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST toreduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗

NASA NTRSDate not supplied

Science Target Prioritization Framework for Remote Sensing

Behind the scenes of a remote sensing mission there are complex decision making and planning operations. Streamlining these operations, with a quantitative scientific value framework, aids efficient and optimized science data collection.While there have been previous efforts to quantify the science value for specific science scenarios, our work aims to develop a general framework which can be applied across different scenarios. We describe a pipeline of processes which combines model forecast and observation data, in computational forms, as dictated by the mission objectives set forth by subject matter experts. The framework is described with use cases involving the monitoring of nitrogen dioxide (NO2) concentrations over the Gulf of Mexico and methane concentrations over interior Alaska.

Remote Sensing↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk Presentation for EnCyCriS

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk

42 - ENGINEERING↗

DOE OSTI2026

Design of a GammaT-Jump System for Fermilab Booster

A $\gamma_{T}$ scheme may be required for the PIP-II era performance or ACE-MIRT era performance of the Booster. PIP-II era operations of the Fermilab proton complex will require the Fermilab Booster to increase beam intensity from 4.5e12 to 6.7e12 protons, while also increasing its ramp from 15 Hz to 20 Hz. These changes pose particular challenges for transition-crossing in the Booster, where longitudinal beam quality must be controlled in order to facilitate slip-stacking in the Recycler Ring later in the Main Injector cycle. Two novel $\gamma_{T}$-jump schemes are proposed, termed Double $\gamma_{T}$ jump and Partial $\gamma_{T}$-jump , which optimize the magnitude of the $\gamma_{T}$-jump within optics and power supply constraints.

Eldred, J. [Fermilab] (ORCID:000000034432072X)↗

DOE OSTI2025

Toward the Development of Molten Salt Reactor Diagnostics based on Resonantly Enhanced Laser Spectroscopy

One emerging concern within the safeguards community is how to best ensure compliance with nuclear security regulations within molten salt reactor (MSR) facilities. This problem is nontrivial as molten salts used for fuel or coolant are highly corrosive, chemically complex, and inherently require high operational temperatures. Laser spectroscopy methods such as laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF) have previously been suggested for molten salt diagnostics due to their compatibility with liquid phase samples and potential for in-situ measurements [1]. In the former, the laser is used to ionize the sample, allowing for the characteristic light from electronic de-excitation as the resultant plasma cools to be used for material characterization. In the latter, a tunable light source is set be resonant with a specific transition, resulting in element specific excitation and the emission of fluorescence light. In our previous work [2], we demonstrated that LIF could be used for the detection of fission fragments such as Nd in solution through the separation of laser scatter and fluorescence within the time domain. Here, we present progress towards two alternate measurement schemes: LIF measurements based on spectroscopic discrimination of fluorescence emissions and resonant LIBS measurements that induce plasma using a light source set to the resonant frequency of a specific electronic transition. Both methods aim to exploit resonant excitation methods to enhance the emitted signal. The studies may provide routes for element-specific detection of constituents within complicated matrices and a means to better understand the chemical behavior of lanthanides and actinides relevant to MSRs.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

NASA NTRS1993

Systems engineering and integration processes involved with manned mission operations

This paper will discuss three mission operations functions that are illustrative of the key principles of operations SE&I and of the processes and products involved. The flight systems process was selected to illustrate the role of the systems product line in developing the depth and cross disciplinary skills needed for SE&I and providing the foundation for dialogue between participating elements. FDDD was selected to illustrate the need for a structured process to assure that SE&I provides complete and accurate results that consistently support program needs. The flight director's role in mission operations was selected to illustrate the complexity of the risk/gain tradeoffs involved in the development of the flight techniques and flight rules process as well as the absolute importance of the leadership role in developing the technical, operational, and political trades.

Kranz, Eugene F.↗

NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗