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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 1,549 records · Page 86
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NASA NTRS2023

Application of Acoustical Holography for Projecting Near-Field Data to the Far Field

In this report, the application of the acoustical holography (AH) technique for projecting near-field acoustic data to the far field is discussed. Test problems will be used to showcase the accuracy and utility of this technique and to demonstrate its superiority over the more common technique of spherical spreading projection. Three versions of the technique will be presented: planar, cylindrical, and spherical. Depending on the nature of the acoustic field, one or more of these versions may be useful and practical to use. Since the cylindrical and spherical versions depend on the accurate numerical computations of certain special functions, such as the Hankel functions and the associated Legendre polynomials, the implementation of the high-precision numerical computation of the required special functions on a computer are included in the appendixes at the end of the report. In some cases, the material presented in these appendixes represents a substantial extension of the results previously published in the open literature. As appropriate, special considerations associated with the use of the AH technique in practical situations are discussed.

Holography↗
NASA NTRSDate not supplied

Designing Non-Pneumatic, Structural Tires for Space: Challenges and Solutions for a Difficult Application

Design and development of Shape Memory Alloy (SMA) Tires is a difficult and challenging problem. A “build and test” approach isn’t practical due to both the expense and time associated with taking such an approach. The multiple iterations that would be required to close requirements space for a space flight hardware program makes this approach infeasible. Hence, details regarding GRC’s SMA modeling approach to solving this challenging problem will be highlighted and used to showcase the power associated with leveraging an SMA modeling framework during design.

Shape Memory Alloys (SMA)↗
NASA NTRSDate not supplied

Introduction to Quantum Computing

Quantum computing offers the potential to revolutionize high-performance computing by providing a means to solve certain computational problems asymptotically faster than any classical computer. Quantum computing has advanced recently from merely a theoretical possibility to engineered reality, including commercial entities offering early prototype quantum processors, both special-purpose quantum annealers and general-purpose gate-model processors. The media have been showcasing each new development and implicitly conveying the message that quantum-computing ubiquity is nigh. Here, we will respond to this hype and provide an overview of the exciting but still early state of the field. In this tutorial, we introduce participants to the computational models that give quantum computing its immense computational power. We examine the thought processes that programmers need to map problems to quantum computers. And we discuss hardware and algorithmic challenges that must be overcome before quantum computing becomes a component of every software developer's repertoire.

Quantum computing↗
NASA NTRS2022

IROSA 3A EVA Robotics

The MAGIK Robotic analysis team provides kinematic feasibility assessments and robotic visualizations for the ISS. This animation was created with configurations provided by the CX Team and showcases the robotics for the IROSA 3A EVA install. The ExtraVehicular Activity (EVA) shown include the extraction of one ISS Roll-Out Solar Array (IROSA) from the ISS Power Augmentation (IPA) carrier by an astronaut on the end of the Space Station Remote Manipulator System (SSRMS) and subsequent install on the ISS starboard side truss. Operations during the EVA not shown will complete the install of the IROSA.

ISS↗
NASA NTRSDate not supplied

Entry Systems Modeling and Ground Testing: Enabling Flight Performance and Risk Reduction

Entry, Descent, and Landing (EDL) comprise a relatively small portion of a mission’s timeline, however, it is typically among the largest risks. Flying through a body’s atmosphere reliably and accurately – from orbit to ground or via aerocapture – is a critical step toward successful in situ exploration. This exhibit will highlight EDL simulation and ground test capabilities, both existing and under development, that could support mission design, risk reduction, and post-flight analysis for Planetary Science mission concepts displayed in the 2023 SMD Planetary Science Technology Showcase.

Entry Systems↗
NASA NTRSDate not supplied

ASCoT 3: Nonlinear Principal Components Analysis and Uncertainty Quantification in Early Concept Spacecraft Flight Software Cost Estimation

For mission planners and evaluators alike, value in cost models comes from a mean or median prediction, an understanding of the uncertainty on that prediction, and an understanding of model performance. Here we apply advanced statistical and machine learning methods to spacecraft flight software cost, effort, and SLOC estimation, and present the results in the latest version of the Analogy Software Cost Tool (ASCoT). We present in- and out-of-sample performance metrics for our models, each of which incorporate some amount of epistemic uncertainty. ASCoT, hosted on the One NASA Cost Engineering (ONCE) database via the Online NASA Space Estimation Tool (ONSET), was first showcased in 2016 as a number of analogy-based models and methods (kNN and Clustering) to support early project formulation. This ASCoT update improves upon the previous analogic methods by incorporating uncertainty in the data transformations. In particular, we use a Nonlinear Principal Components Analysis (NLPCA) to deal with ordinal data.

Robotic Spacecraft↗
NASA NTRSDate not supplied

An Overview of the Artemis I Navigation Performance

The goal of NASA’s Artemis Program is to explore the Moon and beyond. The Artemis I Mission which flew in late 2022 was the uncrewed test flight whose goal was to exercise the entire navigation system in an extended duration flight and evaluate its performance over the entire mission, from pre-launch to post-landing. This paper provides an overview of the Artemis I navigation system architecture, examines the reasoning behind the design, and showcases the navigation performance. In particular, it presents systems-level performance of the navigation filters, sensors, and fault detection/isolation/recovery (FDIR). Also provided are glimpses into the lessons-learned during the flight, the run-up to the mission, and the post-flight analyses. Of particular interest are the four navigation Extended Kalman Filters (EKFs): the Atmospheric EKF (ATMEKF), the Earth Orbit EKF (EOEKF), the Attitude EKF (ATTEKF) and the Cislunar EKF (CLEKF). Whereas only the ATMEKF is a coupled translation/rotation filter, the other three are either translation-only (EOEKF, CLEKF) or rotation-only (ATTEKF). Also presented is an overview of the Optical Navigation system performance.

Greg N Holt↗
NASA NTRS2023

Orbital Debris Shape Effect Investigations for Mitigating Risk

NASA’s Orbital Debris Program Office (ODPO) and Hypervelocity Impact Technology (HVIT) team have coordinated to better understand the risks to upper stages and spacecraft from non-spherical orbital debris. It is well understood that fragmentation (collision or explosion) events in orbit produce fragments of various materials, sizes, and shapes. To further characterize these parameters, the ODPO is developing the next-generation Orbital Debris Engineering Model (ORDEM) version 4.0 to include orbital debris shape distributions. Ground-based assets, such as radar and optical sensors, can provide size estimates and some insight into material based on radar return or optical filter photometry/spectroscopy, respectively. Characterizing an object’s shape requires more laboratory analyses to infer how shape affects these measurements. More importantly, in addition to size and material/density, the shape of fragments in orbit will alter the ballistic limit equations used in orbital debris risk assessments with NASA’s Bumper Code. The ODPO plans to release ORDEM 4.0 in the coming years. Performing ground-based laboratory impact tests on high-fidelity spacecraft mockups provides the means to directly measure size, mass, material/density, and shape of fragments, all key parameters needed to characterize real-world break up events. The DebriSat test, the results of which are provided, showcases the details of this type of experiment. The goal of this collaborative research between the ODPO and the HVIT team is to include a shape parameter in the environmental and breakup models used to assess risk for various space structures. This paper examines ground-based laboratory impact tests and the associated fragment shape categories. Provided these defined shapes, the approach is simplified by assuming a right circular cylinder (RCC) approximation with varying length-to-diameter ratios. Highlights of impact tests conducted by the HVIT team using non-spherical projectiles based on the RCC approximation are presented. Hydrocode simulations have also been performed to expand on the complexity of variations with non-spherical projectiles. Lastly, ray-tracing simulations of various RCCs of known material are provided to support the ongoing research on optical reflectance distributions with known shapes and to highlight how this may modify the current optical size estimation model. The status and plan forward are outlined for NASA's orbital debris shape effect investigation using a multidisciplinary approach by the ODPO and the HVIT team.

Heather Cowardin↗
NASA NTRS2023

A 3D Printable Alloy Designed for Extreme Environments

Multiprincipal-element alloys are an enabling class of materials owing to their impressive mechanical and oxidation-resistant properties, especially in extreme environments. Here we develop a new oxide-dispersion-strengthened NiCoCr-based alloy using a model-driven alloy design approach and laser-based additive manufacturing. This oxide-dispersion-strengthened alloy, called GRX-810, uses laser powder bed fusion to disperse nanoscale Y 2 O 3 particles throughout the microstructure without the use of resource-intensive processing steps such as mechanical or in situ alloying. We show the successful incorporation and dispersion of nanoscale oxides throughout the GRX-810 build volume via high-resolution characterization of its microstructure. The mechanical results of GRX-810 show a twofold improvement in strength, over 1,000-fold better creep performance and twofold improvement in oxidation resistance compared with the traditional polycrystalline wrought Ni-based alloys used extensively in additive manufacturing at 1,093 °C. The success of this alloy highlights how model-driven alloy designs can provide superior compositions using far fewer resources compared with the ‘trial-and-error’ methods of the past. These results showcase how future alloy development that leverages dispersion strengthening combined with additive manufacturing processing can accelerate the discovery of revolutionary materials.

Timothy M. Smith↗
NASA NTRS2022

Precipitation Estimation From the NASA TROPICS Mission: Initial Retrievals and Validation

This paper describes the initial results of precipitation estimates from the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter-wave Sounder (TMS) using the Precipitation Retrieval and Profiling Scheme (PRPS). The TROPICS mission consists of a Pathfinder cubesat and a constellation of six cubesats, providing a low-cost solution to the frequent sampling of precipitation systems across the Tropics. The TMS instrument is a 12-channel cross-track scanning radiometer operating at frequencies from 91.655 to 204.8 GHz, providing similar resolutions to current passive microwave sounding instruments. These retrievals showcases the potential of the TMS instrument for precipitation retrievals. The PRPS has been modified for use with the TMS using a database based upon observations from current sounding sensors. The results shown here represent the initial post-launch version of the retrieval scheme, as analyzed for the Pathfinder cubesat launched on June 30, 2021. In terms of monthly precipitation estimates the results fall within the mission specifications and are similar in performance t

Chris Kidd↗
NASA NTRS2022

Physical and Chemical Conditions in the N113 Star-Forming Region in the Low-Metallicity Large Magellanic Cloud

The Large Magellanic Cloud (LMC) is the nearest (~50 kpc) star-forming galaxy characterized by a low metallicity (Z~0.3-0.5 Z⨀) similar to galaxies during the early phases of their assembly. As a result, star formation studies in the LMC provide a stepping stone to understanding star formation at earlier epochs of the universe where these processes cannot be directly observed. N113 is one of the most prominent star-forming regions in the LMC hosting one of the most massive giant molecular clouds.N113 is small enough to be imaged in its entirety, but large enough to showcase many important phenomena such as multiple generations of stars, stellar feedback, and different environments. We present our findings from an investigation of the early stages of star formation in the N113 region using the Atacama Large Millimeter/submillimeter Array (ALMA)molecular line data probing a wide density range: 12CO, 13CO, and C18O (2-1), 13COand C18O (1-0), HCN (1-0), HCO+ (1-0), H13CN (1-0) and (3-2), H13CO+ (1-0) and (3-2), CS (2-1) and (5-4), as well as 1.3 mm and 3 mm continuum. We used the Python package quick clump to identify molecular clumps. We utilized the multiline non-LTE fitting tool based on models from RADEX developed by Finn et al. (2021, ApJ, 917, 106)to construct the CO, HCN, HCO+, and CS temperature and column density, and the H2density maps of N113. We constructed a catalog of molecular clumps including their physical properties, chemical abundances, sizes, velocities, and velocity dispersions. To establish the evolutionary status of the clumps, their positions were compared with previously identified young stellar objects (YSOs) from the Spitzer/SAGE and Herschel/HERITAGE surveys, as well as water and OH masers. We compared the properties of the clumps in N113 to those in the Galaxy and other regions in the LMC to assess the impact of the environment (e.g., metallicity, stellar feedback) on the star formation process.

Jonathon Noswitz↗
NASA NTRS2023

The First Extragalactic Detection of Higher-Order Hydrogen Recombination Lines

The Large Magellanic Cloud (LMC) is the nearest (~50 kpc) star-forming galaxy characterized by a low metallicity (Z~0.3-0.5 Z⨀) similar to galaxies during the early phases of their assembly. As a result, star formation studies in the LMC provide a stepping stone to understanding star formation at earlier epochs of the universe where these processes cannot be directly observed. N113 is one of the most prominent star-forming regions in the LMC hosting one of the most massive giant molecular clouds. N113 is small enough to be imaged in its entirety, but large enough to showcase many important phenomena such as multiple generations of stars, stellar feedback, and different environments. We present our findings from an investigation of the early stages of star formation in the N113 region using the Atacama Large Millimeter/submillimeter Array (ALMA) molecular line data probing a wide density range: 12CO, 13CO, and C18O (2-1), 13CO and C18O (1-0), HCN (1-0), HCO+ (1-0), H13CN (1-0) and (3-2), H13CO+ (1-0) and (3-2), CS (2-1) and (5-4), as well as 1.3 mm and 3 mm continuum. We used the Python package quickclump to identify molecular clumps. We utilized the multiline non-LTE fitting tool based on models from RADEX developed by Finn et al. (2021, ApJ, 917, 106) to construct the CO, HCN, HCO+, and CS temperature and column density, and the H2 density maps of N113. We constructed a catalog of molecular clumps including their physical properties, chemical abundances, sizes, velocities, and velocity dispersions. To establish the evolutionary status of the clumps, their positions were compared with previously identified young stellar objects (YSOs) from the Spitzer/SAGE and Herschel/HERITAGE surveys, as well as water and OH masers. We compared the properties of the clumps in N113 to those in the Galaxy and other regions in the LMC to assess the impact of the environment (e.g., metallicity, stellar feedback) on the star formation process.

Marta M Sewilo↗
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 NTRS2023

Neural Radiance Fields for Shadow Removal and Relighting of Satellite Imagery

Multi-view stereo photogrammetric techniques have been conventionally utilized to generate Global Digital Elevation Models (GDEM) of planetary and lunar surfaces. However, these methods, relying on conventional feature detectors, are often subject to inaccuracies caused by changes in lighting conditions, including diffuse reflection and harsh shading. This has limited the ability of these methods to accurately reconstruct shadowed regions in orbital imagery, such as highly shaded urban areas and the permanently shadowed regions (PSRs) located in the lunar surface, which are critical targets for NASA's Artemis program. Neural Radiance Fields (NeRFs) offer a novel solution to these limitations by breaking away from traditional photogrammetric assumptions of ridged, opaque surfaces. NeRFs are capable of reconstructing 3D objects with variably transmissive properties, such as fluids, PSRs, and reflective surfaces. In this work, we demonstrate the robustness of NeRFs in generating high-fidelity 3D models of terrain from highly shaded orbital imagery acquired from small satellites in low earth orbit (LEO). Our results showcase the ability of NeRF to overcome the limitations of traditional photogrammetric methods and provide a promising solution for reconstructing complex scenes in challenging lighting conditions.

Caleb Ashmore Adams↗
NASA NTRS2022

MSL MMRTG Power Modeling for Lifetime Performance Predictions

The Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) has been providing power to the Mars Science Laboratory (MSL) rover, Curiosity, for surface operations since 2012. The Jet Propulsion Laboratory (JPL) has employed the Life Performance Prediction Model (LPPM) to generate predictions and outputs based upon flight data from the rover and experimental data from the thermoelectric (TE) couples. In order to make these predictions, LPPM requires various spacecraft inputs relevant to RTG performance such as fin root temperature, load voltage, general purpose heat source (GPHS) inventory, etc., combined with couple data such as thermoelectric properties, interface degradation, and sublimation properties. With tens of thousands of hours of flight data to date, LPPM can not only track performance to date, but also make predictions on the power output of the MMRTG through the 17-year end-of-design-life (EODL). These predictions are useful for mission planners and surface operators who rely on the MMRTG for power in order to perform the critical science necessary during the mission. This paper will showcase the power data extracted from the flight electronics, comparing it to the predictions and outputs generated from LPPM.

Pinkowski, Stanley↗
NASA NTRS2022

Power Converter Design for the Europa Lander Motor Controller

This paper will outline the design and test results for the Europa Lander motor controller’s Power Conversion Slice. Europa Lander is a proposed NASA mission concept to send a stationary spacecraft to Jupiter’s Icy Moon, Europa, to search for subsurface biosignatures. The Power Conversion Card is one of the many technologies designed for this mission. The Power Conversion Card’s primary function is to convert the power supplied by the spacecraft battery to usable power for use within the motor controller. In addition, this card provides power system telemetry to the spacecraft computer. This card tolerates Europa’s harsh radiation environment within a protected vault to enable it to survive the external temperatures which can be as low as -184°C during the three-week mission. This design makes use of multiple commercially available radiation hardened electronics, including Cobham’s UT32M0R500 Arm Microcontroller along with VPT’s DC-DC Converters for power conversion. The microcontroller is used to collect local power system telemetry and assess card health autonomously without intervention from the spacecraft’s main computer. This paper will showcase the design behind the prototype and electrical testing results.

Lias, Malcolm↗
NASA NTRS2022

Robust Controller Synthesis for Vision-based Spacecraft Guidance and Control

This work develops a method for Robust Controller for Vision-based Spacecraft (RCVS) guidance and control, integral to the robust autonomy framework for multi-spacecraft for- mation control and reconfiguration applications. The method is built around the use of a photo-realistic simulator, where a camera is deployed on a tracking spacecraft (ego) in order to observe an uncontrolled spacecraft (target) in a Low Earth Orbit (LEO). In this direction, the proposed approach performs the relative state (attitude and position) estimation of the target spacecraft using Convolutional Neural Network (CNN). The state estimation error is then modeled and the corresponding error-bounds are obtained around a nominal trajectory of the ego and target spacecraft. Next, this work proposes a linear matrix inequalities (LMIs) based approach to controller synthesis, guaranteed to be robust against both model uncertainties and measurement errors, resulting from vision-based estimation. This controller is comprised of two distinct components, one synthesized based on the nominal trajectory, while the “robust” component corrects for deviations from the nominal trajectory. Finally, a tracking scenario that directly utilize the image data for spacecraft guidance and control, is presented to showcase the performance of the proposed robust autonomy framework.

Rahmani, Amir↗
NASA NTRSDate not supplied

Breaking Down Data Silos

Siloed schedule data creates barriers to information sharing and collaboration. In short, siloed data is not healthy data. If schedule data isn't easy to find and use in a timely fashion (or can't be trusted when it is found) it isn’t adding value. Many programs, projects, and initiatives are accustomed to working in their own worlds with their own lingo, processes, and challenges. This culture of separation carries over to schedules. This presentation will showcase SCaN’s efforts to break down the silo mentality.

schedule↗