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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 NTRS2002

Tools and Techniques for Evaluating the Effects of Maintenance Resource Management (MRM) in Air Safety

This research project was designed as part of a larger effort to help Human Factors (HF) implementers, and others in the aviation maintenance community, understand, evaluate, and validate the impact of Maintenance Resource Management (MRM) training programs, and other MRM interventions; on participant attitudes, opinions, behaviors, and ultimately on enhanced safety performance. It includes research and development of evaluation methodology as well as examination of psychological constructs and correlates of maintainer performance. In particular, during 2001, three issues were addressed. First a prototype process for measuring performance was developed and used. Second an automated calculator was developed to aid the HF implementer user in analyzing and evaluating local survey data. These results include being automatically compared with the experience from all MRM programs studied since 1991. Third the core survey (the Maintenance Resource Management Technical Operations Questionnaire, or 'MRM/TOQ') was further developed and tested to include topics of added relevance to the industry.

Taylor, James C.↗
NASA NTRS1988

Graphical representation of three-dimensional vortical flows by means of helicity density and normalized helicity

The helicity density and normalized helicity are introduced as important tools for the graphical representation of three-dimensional flowfields that contain concentrated vortices. The use of these two quantities filters out the graphical representation of the flowfield regions of low vorticity, as well as regions of high vorticity but low speed where the angle between the velocity and vorticity vectors is large (such as in the boundary layer). Their use permits the researcher to identify and accentuate the concentrated vortices, differentiate between primary and secondary vortices and mark their separation and reattachment lines. The method allows locating the singular points in type I primary separations and tracing the vortex-core streamlines that emanate from them. It also allows locating the vortex-core axes in flows of other types.

Seginer, Arnan↗
NASA NTRS2002

Propulsion System Modeling and Simulation

The Aerospace Systems Design Laboratory at the School of Aerospace Engineering in Georgia Institute of Technology has developed a core competency that enables propulsion technology managers to make technology investment decisions substantiated by propulsion and airframe technology system studies. This method assists the designer/manager in selecting appropriate technology concepts while accounting for the presence of risk and uncertainty as well as interactions between disciplines. This capability is incorporated into a single design simulation system that is described in this paper. This propulsion system design environment is created with a commercially available software called iSIGHT, which is a generic computational framework, and with analysis programs for engine cycle, engine flowpath, mission, and economic analyses. iSIGHT is used to integrate these analysis tools within a single computer platform and facilitate information transfer amongst the various codes. The resulting modeling and simulation (M&S) environment in conjunction with the response surface method provides the designer/decision-maker an analytical means to examine the entire design space from either a subsystem and/or system perspective. The results of this paper will enable managers to analytically play what-if games to gain insight in to the benefits (and/or degradation) of changing engine cycle design parameters. Furthermore, the propulsion design space will be explored probabilistically to show the feasibility and viability of the propulsion system integrated with a vehicle.

Tai, Jimmy C. M.↗
NASA NTRS2004

Distributive On-line Processing, Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time- consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions, for example, when preparing data for input into modeling systems. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Time plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. In the future, we will add correlation plots, GIS-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. In our case, we use this approach to read pre-processed binary files and/or to read and extract the needed parts from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS processing and analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, G.↗
NASA NTRS2008

Framework for the Parametric System Modeling of Space Exploration Architectures

This paper presents a methodology for performing architecture definition and assessment prior to, or during, program formulation that utilizes a centralized, integrated architecture modeling framework operated by a small, core team of general space architects. This framework, known as the Exploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), enables: 1) a significantly larger fraction of an architecture trade space to be assessed in a given study timeframe; and 2) the complex element-to-element and element-to-system relationships to be quantitatively explored earlier in the design process. Discussion of the methodology advantages and disadvantages with respect to the distributed study team approach typically used within NASA to perform architecture studies is presented along with an overview of EXAMINE s functional components and tools. An example Mars transportation system architecture model is used to demonstrate EXAMINE s capabilities in this paper. However, the framework is generally applicable for exploration architecture modeling with destinations to any celestial body in the solar system.

Komar, David R.↗
NASA NTRS2011

The Application of Lean Thinking Principles and Kaizen Practices for the Successful Development and Implementation of the Ares I-X Flight Test Rocket and Mission

On October 28, 2009 the Ares I-X flight test rocket launched from Kennedy Space Center and flew its suborbital trajectory as designed. The mission was successfully completed as data from the test, and associated development activities were analyzed, transferred to stakeholders, and well documented. Positive lessons learned from Ares I-X were that the application of lean thinking principles and kaizen practices are effective in streamlining development activities. Ares I-X, like other historical rocket development projects, was hampered by technical, cost, and schedule challenges and if not addressed boldly could have resulted in cancellation of the test. The mission management team conducted nine major meetings, referred to as lean events, across its elements to assess plans, procedures, processes, requirements, controls, culture, organization, use of resources, and anything that could be changed to optimize schedule or reduce risk. The preeminent aspect of the lean events was the focus on value added activities and the removal or at least reduction in non-value activities. Trained Lean Six Sigma facilitators assisted the Ares I-X developers in conducting the lean events. They indirectly helped formulate the mission s own unique methodology for assessing schedule. A core team was selected to lead the events and report to the mission manager. Each activity leveraged specialized participants to analyze the subject matter and its related processes and then recommended alternatives and solutions. Stakeholders were the event champions. They empowered and encouraged the team to succeed. The keys to success were thorough preparation, honest dialog, small groups, adherence to the Ares I-X ground rules, and accountability through disciplined reporting and tracking of actions. This lean event formula was game-changing as demonstrated by the success of Ares I-X. It is highly recommended as a management tool to help develop other complex systems efficiently. The key benefits for Ares I-X were obtaining unambiguous schedule margin, defining enabling options for risk reduction, and most importantly a stronger more unified team.

Askins, B. R.↗
NASA NTRS1995

New far infrared images of bright, nearby, star-forming regions

Broadband imaging in the far infrared is a vital tool for understanding how young stars form, evolve, and interact with their environment. As the sensitivity and size of detector arrays has increased, a richer and more detailed picture has emerged of the nearest and brightest regions of active star formation. We present data on M 17, M 42, and S 106 taken recently on the Kuiper Airborne Observatory with the Yerkes Observatory 60-channel far infrared camera, which has pixel sizes of 17 in. at 60 microns, 27 in. at 100 microns, and 45 in. at 160 and 200 microns. In addition to providing a clearer view of the complex central cores of the regions, the images reveal new details of the structure and heating of ionization fronts and photodissociation zones where radiation form luminous stars interacts with adjacent molecular clouds.

Harper, D. AL, Jr.↗
NASA NTRS1996

Aeroacoustic Codes For Rotor Harmonic and BVI Noise--CAMRAD.Mod1/HIRES

This paper presents a status of non-CFD aeroacoustic codes at NASA Langley Research Center for the prediction of helicopter harmonic and Blade-Vortex Interaction (BVI) noise. The prediction approach incorporates three primary components: CAMRAD.Mod1 - a substantially modified version of the performance/trim/wake code CAMRAD; HIRES - a high resolution blade loads post-processor; and WOPWOP - an acoustic code. The functional capabilities and physical modeling in CAMRAD.Mod1/HIRES will be summarized and illustrated. A new multi-core roll-up wake modeling approach is introduced and validated. Predictions of rotor wake and radiated noise are compared with to the results of the HART program, a model BO-105 windtunnel test at the DNW in Europe. Additional comparisons are made to results from a DNW test of a contemporary design four-bladed rotor, as well as from a Langley test of a single proprotor (tiltrotor) three-bladed model configuration. Because the method is shown to help eliminate the necessity of guesswork in setting code parameters between different rotor configurations, it should prove useful as a rotor noise design tool.

Brooks, Thomas F.↗
NASA NTRS2011

Launch Vehicle Demonstrator Using Shuttle Assets

The Advanced Concepts Office at NASA's George C. Marshall Space Flight Center undertook a study to define candidate early heavy lift demonstration launch vehicle concepts derived from existing space shuttle assets. The objective was to determine the performance capabilities of these vehicles and characterize potential early demonstration test flights. Given the anticipated budgetary constraints that may affect America's civil space program, and a lapse in U.S. heavy launch capability with the retirement of the space shuttle, an early heavy lift launch vehicle demonstration flight would not only demonstrate capabilities that could be utilized for future space exploration missions, but also serve as a building block for the development of our nation s next heavy lift launch system. An early heavy lift demonstration could be utilized as a test platform, demonstrating capabilities of future space exploration systems such as the Multi Purpose Crew Vehicle. By using existing shuttle assets, including the RS-25D engine inventory, the shuttle equipment manufacturing and tooling base, and the segmented solid rocket booster industry, a demonstrator concept could expedite the design-to-flight schedule while retaining critical human skills and capital. In this study two types of vehicle designs are examined. The first utilizes a high margin/safety factor battleship structural design in order to minimize development time as well as monetary investment. Structural design optimization is performed on the second, as if an operational vehicle. Results indicate low earth orbit payload capability is more than sufficient to support various vehicle and vehicle systems test programs including Multi-Purpose Crew Vehicle articles. Furthermore, a shuttle-derived, hydrogen core vehicle configuration offers performance benefits when trading evolutionary paths to maximum capability.

Creech, Dennis M.↗
NASA NTRS2011

NASA Tech Briefs, November 2011

The topics include: 1) Flight Test Results from the Rake Airflow Gage Experiment on the F-15B; 2) Telemetry and Science Data Software System; 3) CropEx Web-Based Agricultural Monitoring and Decision Support; 4) High-Performance Data Analysis Tools for Sun-Earth Connection Missions; 5) Experiment in Onboard Synthetic Aperture Radar Data Processing; 6) Microfabrication of a High-Throughput Nanochannel Delivery/Filtration System; 7) Improved Design and Fabrication of Hydrated-Salt Pills; 8) Monolithic Flexure Pre-Stressed Ultrasonic Horns; 9) Cryogenic Quenching Process for Electronic Part Screening; 10) Broadband Via-Less Microwave Crossover Using Microstrip-CPW Transitions; 11) Wheel-Based Ice Sensors for Road Vehicles; 12) G-DYN Multibody Dynamics Engine; 13) Multibody Simulation Software Testbed for Small-Body Exploration and Sampling; 14) Propulsive Reaction Control System Model; 15) Licklider Transmission Protocol Implementation; 16) Core Recursive Hierarchical Image Segmentation; 17) Two-Stage Centrifugal Fan; 18) Combined Structural and Trajectory Control of Variable-Geometry Planetary Entry Systems; 19) Pressure Regulator With Internal Ejector Circulation Pump, Flow and Pressure Measurement Porting, and Fuel Cell System Integration Options; 20) Temperature-Sensitive Coating Sensor Based on Hematite; 21) Standardization of a Volumetric Displacement Measurement for Two-Body Abrasion Scratch Test Data Analysis; 22) Detection of Carbon Monoxide Using Polymer-Carbon Composite Films; 23) Substituted Quaternary Ammonium Salts Improve Low-Temperature Performance of Double-Layer Capacitors; 24) Sustainably Sourced, Thermally Resistant, Radiation Hard Biopolymer; 25) Integrated Lens Antennas for Multi-Pixel Receivers; 26) 180-GHz Interferometric Imager; 27) Maturation of Structural Health Management Systems for Solid Rocket Motors; 28) Validating Phasing and Geometry of Large Focal Plane Arrays; 29) Transverse Pupil Shifts for Adaptive Optics Non-Common Path Calibration; 30) Qualification of Fiber Optic Cables for Martian Extreme Temperature Environments; 31) Solid-State Spectral Light Source System; 32) Multiple-Event, Single-Photon Counting Imaging Sensor; 33) Surface Modeling to Support Small-Body Spacecraft Exploration and Proximity Operations; and 34) Achieving Exact and Constant Turnaround Ratio in a DDS-Based Coherent Transponder.

Source record↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗
NASA NTRS2019

Continuous Electrode Inertial Electrostatic Confinement Fusion

The NIAC Phase I project on Inertial Electrostatic Confinement was a continuation of early stage research that was funded by an NSTRF. The student on the project, Andrew Chap, was funded by the NSTRF from Fall 2013 through the Summer of 2017, and then was funded on the NIAC through the completion of his PhD. A significant amount of work targeting the plasma confinement physics was the focus of his NSTRF, and over the course of that effort he developed a number of analyses and computational tools that leveraged GPU parallelization. A detailed discussion of these models can be found in his dissertation, which has been included as Appendix D in this report. As a requirement for the NSTRF, Andrew's full dissertation was submitted at the end of the program.Having developed the computational tools, a substantial amount of simulation and analyses leveraging those tools were conducted during the Fall of 2017, under the auspices of the NIAC funded research. Much of this work targeted optimization of the confinement fields, investigating their structure and the possible advantages of having them be time-varying. The results of these simulations can also be found in Appendix D.One of the main results from this research is that the density of ions electrostatically confined within the system can indeed be increased by several orders of magnitude by optimizing the radial potential distribution, and by dynamically varying these fields to maintain compressed ion bunches. An electron population can also be confined within the core by a static radial cusped magnetic field,which helps to support a greater ion density within the core. The issue with the confinement mechanism is that as the ion densities are increased toward fusion-relevant levels, the electrostatic forces generated by the confined electron population become so great that the ions are no longer energetic enough to leave the device core. As their excursions into the outer channels are diminished, the mechanism that is used to maintain their non-thermal velocity distributions becomes ineffective, and eventually the ions become fully confined within the core, where they thermalize. A possible fix to the problem comes by discarding the active ion control (a main pillar of the concept)but retaining the structure of the permanent magnet confinement of the electron population. Such cusped field confinement has been the focus of other IEC approaches (e.g. Polywell), but the high transparency of the permanent magnet structure lends itself to better ion extraction and power conversion (a second pillar of the concept). The question then becomes whether any influence on the ion evolution within the core can be achieved to slow the thermalization of the ions. Such approaches have been studied in highly idealized analytic models, but face major criticisms within the literature. While this is a possible path forward, the uncertainty in the approach did not warrant committing NIAC Phase II resources to investigating the concept at this time.

Sedwick, Raymond↗
NASA NTRSDate not supplied

Feasibility Study to Interactive Workshop: Building End-user Capacity to Integrate Earth Observation Data into Federally Endangered Atlantic Salmon (Salmo salar) Habitat Monitoring in Main

Changes in temperature and precipitation patterns, along with alterations in land cover threaten ongoing conservation efforts for Federally Endangered Atlantic salmon (Salmo salar) in Maine. Earth observation data offers a unique perspective for habitat monitoring that can complement habitat restoration and conservation activity on the ground. As a dual capacity building program, the NASA DEVELOP National Program strives to build the capacity of program participants by leveraging Earth observation data to address environmental concerns across the globe, while also building capacity in partner organizations to integrate Earth observation data into their decision making practices. Between September 2021 and August 2022, three NASA DEVELOP teams demonstrated the feasibility of utilizing NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), and Shuttle Radar Topography Mission (SRTM) in conjunction with Sentinel-2 MultiSpectral Instrument (MSI) to assess temperature, precipitation, and land use land cover (LULC) over time throughout salmon habitat in Maine. While the first two teams completed projects that were categorized as NASA DEVELOP’s traditional feasibility projects, the third and final project team generated resources and planned an interactive workshop to transfer project methods to end-user organizations. Ultimately, the goal of this work was to not only inform the partner’s ongoing salmon population recovery and habitat restoration initiatives but provide tools that allow partner organizations to continue integrating Earth observation data into their work beyond their partnership with the program. This project serves as a case study within the NASA DEVELOP Program and provides lessons learned for moving beyond traditional feasibility studies to more interactive partner engagement and knowledge transfer practices.

Nicole Ramberg-Pihl↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
NASA NTRS2023

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of machine-learning (ML) models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a user-friendly app that has been created to deploy trained machine-learning (ML) models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of ML application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). The app gets user input for a turbofan design, preprocesses the input data, and deploys trained ML models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The ML predictive models were built by employing supervised deep-learning and K-nearest neighbor regression algorithms to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these ML models using the app shows that Aero-Engines AI is an easy-touse and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage. Current version of the app focuses on the performance prediction of conventional turbofans. However, the scope of the app can easily be easily expanded to include other engine types (such as turboshaft and hybrid-electric systems) after their ML models are developed. Overall, the use of a machine-learning app for aircraft engine concept assessment represents a promising area of development in aircraft engine conceptual design.

machine learning↗
NASA NTRS2002

Preliminary Design and Evaluation of Portable Electronic Flight Progress Strips

There has been growing interest in using electronic alternatives to the paper Flight Progress Strip (FPS) for air traffic control. However, most research has been centered on radar-based control environments, and has not considered the unique operational needs of the airport air traffic control tower. Based on an analysis of the human factors issues for control tower Decision Support Tool (DST) interfaces, a requirement has been identified for an interaction mechanism which replicates the advantages of the paper FPS (e.g., head-up operation, portability) but also enables input and output with DSTs. An approach has been developed which uses a Portable Electronic FPS that has attributes of both a paper strip and an electronic strip. The prototype flight strip system uses Personal Digital Assistants (PDAs) to replace individual paper strips in addition to a central management interface which is displayed on a desktop computer. Each PDA is connected to the management interface via a wireless local area network. The Portable Electronic FPSs replicate the core functionality of paper flight strips and have additional features which provide a heads-up interface to a DST. A departure DST is used as a motivating example. The central management interface is used for aircraft scheduling and sequencing and provides an overview of airport departure operations. This paper will present the design of the Portable Electronic FPS system as well as preliminary evaluation results.

Doble, Nathan A.↗
NASA NTRS2019

Psyche Early Project Verification & Validation Planning Development

The Psyche mission to the asteroid (16) Psyche was selected as the fourteenth mission in the Discovery program in January 2017. The Psyche mission will determine if (16) Psyche is the core of a larger differentiated body. As part of the development of this mission a Verification and Validation (V&V) engineer was assigned early in the project’s design Phase B. This paper will discuss some of the strategies that the Psyche team is using to take full advantage of the early planning for V&V on flight projects and specifically how the Psyche mission is approaching these tasks. This paper will discuss the effects of having a V&V mindset on: 1) The Psyche requirements development process, and how focusing not only on how the team will verify these requirements but also on developing the tools necessary to track and monitor that verification feeds back into the requirement development process. 2) The Psyche testbed development, and how using a verification mindset is useful for identifying holes in the testbed development process, including the required testbed speed and how to think about testbed certification early in the process while encouraging trades and developing relationships with the testbed team. 3) Developing new V&V Tools for Psyche, and how developing tools early in the project development process means that they can influence the development of other requirement and scheduling tools. 4) Verification Activity Planning, which is typically done to a preliminary level during Phase B of the project, and is important for understanding the major testing that is needed to ensure that the system as built represents the design. On Psyche we are not only focused on bringing this planning to a preliminary level, we are also developing a V&V focused schedule to help us de-conflict V&V activities that may require similar resources early on in the program’s development. 5) Validation Planning, for which we are working with the testbed and model development teams to ensure that their models can be effectively validated and that the plans to do so are in place. In this paper we will describe how the Psyche mission is approaching each of these V&V areas and identify lessons that can be taken by other space missions trying to decide how much effort should be put into V&V early in the project lifecycle.

Solish, Benjamin↗
NASA NTRS2016

The Core Flight System (cFS) Community: Providing Low Cost Solutions for Small Spacecraft

In February 2015 the NASA Goddard Space Flight Center (GSFC) completed the open source release of the entire Core Flight Software (cFS) suite. After the open source release a multi-NASA center Configuration Control Board (CCB) was established that has managed multiple cFS product releases. The cFS was developed and is being maintained in compliance with the NASA Class B software development process requirements and the open source release includes all Class B artifacts. The cFS is currently running on three operational science spacecraft and is being used on multiple spacecraft and instrument development efforts. While the cFS itself is a viable flight software (FSW) solution, we have discovered that the cFS community is a continuous source of innovation and growth that provides products and tools that serve the entire FSW lifecycle and future mission needs. This paper summarizes the current state of the cFS community, the key FSW technologies being pursued, the development/verification tools and opportunities for the small satellite community to become engaged. The cFS is a proven high quality and cost-effective solution for small satellites with constrained budgets.

System↗