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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Building the Next Generation Technology Transfer Information System

The Defense Technology Transfer Information System (DTTIS) is a scalable data system built to grow and adapt to changing conditions. It collects information from each technology transfer offices, patent attorneys, innovators, and more. It automates workflows to standardize and streamline technology transfer business rules. This resulting in improved efficiency, standardized processes and reducing errors. DTTIS is a search and reporting engine built on patented NASA's Technology Transfer System (NTTS) core software platform.

Tran, Peter B.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32060-DND

All previous PSP testing done in the Unitary Plan Wind Tunnel (UPWT) have required a significant amount of manual operation of the system. This has resulted in decreased testing efficiency and precluded the ability to provide near real-time data analysis to the customer. The overall goal of this project is to integrate the PSP data acquisition system into the supersonic UPWT data acquisition system (DAS) and create an adaptive software platform from which PSP data acquisition can be triggered by the tunnel and critical testing conditions can be recorded in real time for rapid analysis of the PSP data. This analysis includes the mapping of up to eight camera views onto a surface grid for analysis and converting to pressure using parameters supplied by the DAS. To fully implement this solution, communication must first be established between the Unitary DAS and the PSP DAS. This will be done by employing multiple scripts written in Python and C++ and implemented on a Linux cluster. These will be demonstrated and refined on an upcoming test (December 2018), and the successful completion will result in the ability to have automatic collection of PSP images and near real-time analysis capabilities.

Juliette Eddins↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗
NASA NTRSDate not supplied

Connecting Mission Profiles and Radiation Vulnerability Assessment

Radiation vulnerability assessment early in spacecraft development is cheaper and faster than in late development phases. RGENTIC and SEAM are two software platforms that can be coupled to provide this type of early assessment. Specifically, RGENTIC is a tool that outputs descriptions of radiation risks based on a selected mission environment and the system’s electronic part portfolio, while SEAM models how radiation-induced faults in electronic parts propagate through a system. In this work, we propose a spacecraft evaluation flow where RGENTIC’s outputs, which are radiation vulnerabilities of electronic parts for a given mission, become inputs to SEAM, resulting in an automatic part-type template palette presented to users so that they can easily begin modeling the occurrence and propagation of radiation-induced faults in their spacecraft. In this context, fault propagation modeling shows how radiation effects impact the spacecraft’s electronics.

Richard H. Nederlande↗
NASA NTRSDate not supplied

A Decision Support System for Extravehicular Operations Under Significant Communication Latency

Within the next few decades, humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant two-way communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) performing an EVA and an Earth-based mission control. Next-generation operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the on-planet extravehicular crewmember(s), and intermediate mission support from intravehicular crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. For this purpose, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automating the tracking and projection of consumables usage over an EVA timeline, providing real-time probabilistic safety assessments of an EVA timeline given consumables constraints, and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the intravehicular crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g. training bias.

Mars↗
NASA NTRSDate not supplied

A Thinking System and Thinking Autonomy

There are many definitions of what a “Thinking System” (TS) is. The literature primarily addresses what is called “Systems Thinking.” Dr. Marie Morganelli from Southern New Hampshire University states that “Systems thinking is a holistic way to investigate factors and interactions that could contribute to a possible outcome. A mindset more than a prescribed practice, systems thinking provides an understanding of how individuals can work together in different types of teams and through that understanding, create the best possible processes to accomplish just about anything.” So, a TS is a system that is capable of “systems thinking,” as it should be able to “ … create [utilize] the best possible processes [and intelligence] to accomplish just about anything.” To achieve this capability, human-like thinking is required. A truly autonomous system must be one that is capable of human-like thinking. This paper will address “Thinking Autonomy” (TA) enabled by a “Thinking System.” It will describe an architecture with the elements required to achieve the “thinking” behavior: understanding, intellect, reason, decision, will. The paper will further describe the contents and functionality of these elements and how to implement them, including software capabilities needed. Finally, the paper will provide details of a software platform that enables TA, the NASA Platform for Autonomous Systems (NPAS), and describe implementations of thinking systems. Thinking systems will enable a fundamental change how AI and autonomy are implemented. It will change from a “brute force” approach that results in one-time implementations that are minimally intelligent or autonomous to a “thinking” approach where implementations evolve continuously and enable powerful intelligence and autonomy on systems of high complexity as well as on systems-of-systems.

Thinking systems↗
NASA NTRSDate not supplied

A Decision Support System for Extravehicular Operations Under Significant Communication Latency

Humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) and Earth-based mission control. Nextgeneration operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the onplanet extravehicular crewmember(s), and intermediate mission support from intravehicular (IV) crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. Thus, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automatically tracking and projecting consumables usage over an EVA timeline, providing real-time probabilistic safety assessments and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the IV crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g., training bias.

Mars↗
NASA NTRSDate not supplied

PersEIDS: A Biomedical Decision Support System for Extravehicular Operations Under Significant Communication Latency

Humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) and Earth-based mission control. Nextgeneration operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the onplanet extravehicular crewmember(s), and intermediate mission support from intravehicular (IV) crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. Thus, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automatically tracking and projecting consumables usage over an EVA timeline, providing real-time probabilistic safety assessments and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the IV crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g., training bias.

Mars↗
NASA NTRSDate not supplied

Modeling of Multicomponent Trace Contaminant Adsorption on Activated Carbon

Modeling of multicomponent trace contaminant adsorption on activated carbon for spacecraft life support applications presents challenges due to the very low contaminant concentrations in cabin air coupled with very strong adsorption of heavier components such as cyclic polydimethylsiloxanes. Both gas-phase and solid-phase micropore mass transfer resistances can be important, and competitive interactions between adsorbed components can result in behavior such as roll-up where lighter components displaced by heavier components have a higher concentration at the outlet than at the inlet. This paper describes the further development of a dynamic trace contaminant adsorption model based on Ideal Adsorbed Solution Theory (IAST). Alternative 1-dimensional and 2-dimensional versions of the model are described with different mass transfer resistance and driving force assumptions. Optimization of solution methods for speed and stability is also described. Mass balance equations are scaled to provide sensitivity over the wide range of component concentrations in cabin air. Model parameters are estimated from isotherm and breakthrough test data on single adsorbate and binary adsorbate systems. Multicomponent results are compared against predictions of a heritage model used extensively by NASA for trace contaminant control system (TCCS) carbon bed sizing. Finally, efforts to implement the model in a second software platform for wider access are described.

Kevin E Lange↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Low SWaP Onboard Satellite Navigation, Guidance, and Control Technology

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The first build of autoNGC, providing autonomous navigation for lunar orbiting spacecraft, is targeted for completion by Fall 2024. It provides sensor fusion of multiple measurement types including pseudo-range from a weak signal Global Navigation Satellite Service (GNSS) receiver, 1-way and 2-way direct to Earth (DTE) range and Doppler, bearing and range from optical camera sensed images, and an accelerometer. AutoNGC is also being targeted for future missions that involve small body proximity operations, Sun Earth Libration point orbits, and distributed systems missions (DSMs) including those at outer planets. AutoNGC flight software is being built upon the plug-and-play architecture of the core Flight System (cFS) [Ref. 1]. Figure (Slide 7) shows the message-based software bus layout of various software applications (“apps”) consisting of the standard cFS apps and autoNGC interface apps and libraries. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library [Ref. 2], which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are provided by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app [Ref. 3]. This app processes optical images to extract the bearing angles of the centroid of the imaged body (near or far), the range to the imaged body, and/or of the features on the surface of a body to perform terrain relative navigation (TRN). Measurement of range to the body’s center of mass can also be derived from the detection of the limb. The first build of autoNGC for a lunar orbiting spacecraft is a minimal size, weight, and power (SWaP) hardware design allowing for inclusion into CubeSats and SmallSat-size class buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z [Ref. 4] are utilized for low SWaP while maintaining a high level of performance. Figure (Slide 11) shows the composition of the first autoNGC build. The current enclosure design has dimensions 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. The hardware interfaces are designed for flexibility with a variety of sensor inputs. The achievable navigation performance depends on the sensors utilized, including the onboard clock for 1-way pseudo-range measurements. Analysis using a configuration that consists of weak signal GPS, TRN, and 1-way DTE has shown position and velocity accuracies of 10 meters and 2 cm/s (3-σ ) RSS, respectively, with onboard time knowledge estimated to better than 13 ns (3-σ ), for a spacecraft in a representative 12-hour eccentric lunar orbit. Other measurement types such as x-rays from known pulsars (called XNAV) and cross-links can also be processed in GEONS. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced, even after launch. Goddard is actively seeking partners to collaborate in the development of additional capabilities for autoNGC, including industry, academia, and others across the US Government. Plans are being formulated to make the autoNGC software platform available for use by any US government organization to leverage the non-recurring engineering associated with the development of onboard autonomous NGC 3 capabilities. As advancements in space qualified sensors, microprocessors, and algorithms are made, the autoNGC platform provides a ready starting point for inclusion of these technologies.

C. J. Gramling↗
NASA NTRS2024

Celestial Mapping System Videos

The Celestial Mapping System (CMS) is a software platform to generate virtual 3D globes for celestial bodies within our solar system. Multiple planetary data layers can be added to the virtual globe to provide visualization of high-resolution imagery and elevation data, which enables precise measurements, tools for analytical capabilities and a broad range of other functionalities to assist planetary scientists and mission planners. Third-party planetary data can be ingested into CMS with minimal effort. The present focus of CMS is on developing lunar mapping tools to provide features such as: 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo, CLPS and international mission landing site annotations, 3D Models, stereoscopic view, terrain profiling, line of sight analysis, sunlight shading and many more. The application has been developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placement and traverse path optimization.

Mapping↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRS2008

REVEAL: Software Documentation and Platform Migration

The Research Environment for Vehicle Embedded Analysis on Linux (REVEAL) is reconfigurable data acquisition software designed for network-distributed test and measurement applications. In development since 2001, it has been successfully demonstrated in support of a number of actual missions within NASA s Suborbital Science Program. Improvements to software configuration control were needed to properly support both an ongoing transition to operational status and continued evolution of REVEAL capabilities. For this reason the project described in this report targets REVEAL software source documentation and deployment of the software on a small set of hardware platforms different from what is currently used in the baseline system implementation. This report specifically describes the actions taken over a ten week period by two undergraduate student interns and serves as a final report for that internship. The topics discussed include: the documentation of REVEAL source code; the migration of REVEAL to other platforms; and an end-to-end field test that successfully validates the efforts.

Wilson, Michael A.↗
NASA NTRS2011

REVEAL: Software Documentation and Platform Migration

The Research Environment for Vehicle Embedded Analysis on Linux (REVEAL) is reconfigurable data acquisition software designed for network-distributed test and measurement applications. In development since 2001, it has been successfully demonstrated in support of a number of actual missions within NASA's Suborbital Science Program. Improvements to software configuration control were needed to properly support both an ongoing transition to operational status and continued evolution of REVEAL capabilities. For this reason the project described in this report targets REVEAL software source documentation and deployment of the software on a small set of hardware platforms different from what is currently used in the baseline system implementation. This presentation specifically describes the actions taken over a ten week period by two undergraduate student interns and serves as an overview of the content of the final report for that internship.

Wilson, Michael A.↗
NASA NTRS2013

Upgrades to the Probabilistic NAS Platform Air Traffic Simulation Software

This document is the final report for the project entitled "Upgrades to the Probabilistic NAS Platform Air Traffic Simulation Software." This report consists of 17 sections which document the results of the several subtasks of this effort. The Probabilistic NAS Platform (PNP) is an air operations simulation platform developed and maintained by the Saab Sensis Corporation. The improvements made to the PNP simulation include the following: an airborne distributed separation assurance capability, a required time of arrival assignment and conformance capability, and a tactical and strategic weather avoidance capability.

Hunter, George↗
NASA NTRS1989

Methodology for automating software systems. Task 1 of the foundations for automating software systems

The early stages of a research program designed to establish an experimental research platform for software engineering are described. Major emphasis is placed on Computer Assisted Software Engineering (CASE). The Poor Man's CASE Tool is based on the Apple Macintosh system, employing available software including Focal Point II, Hypercard, XRefText, and Macproject. These programs are functional in themselves, but through advanced linking are available for operation from within the tool being developed. The research platform is intended to merge software engineering technology with artificial intelligence (AI). In the first prototype of the PMCT, however, the sections of AI are not included. CASE tools assist the software engineer in planning goals, routes to those goals, and ways to measure progress. The method described allows software to be synthesized instead of being written or built.

Moseley, Warren↗