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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A wall interference assessment/correction system

A Wall Signature method originally developed by Hackett has been selected to be adapted for the Ames 12-ft Wind Tunnel WIAC system in the project. This method uses limited measurements of the static pressure at the wall, in conjunction with the solid wall boundary condition, to determine the strength and distribution of singularities representing the test article. The singularities are used in turn for estimating wall interference at the model location. The development and implementation of a working prototype will be completed, delivered and documented with a software manual. The WIAC code will be validated by conducting numerically simulated experiments rather than actual wind tunnel experiments. The simulations will be used to generate both free-air and confined wind-tunnel flow fields for each of the test articles over a range of test configurations. Specifically, the pressure signature at the test section wall will be computed for the tunnel case to provide the simulated 'measured' data. These data will serve as the input for the WIAC method--Wall Signature method. The performance of the WIAC method then may be evaluated by comparing the corrected parameters with those for the free-air simulation. The following two additional tasks are included: (1) On-line wall interference calculation: The developed wall signature method (modified Hackett's method) for Ames 12-ft Tunnel will be the pre-computed coefficients which facilitate the on-line calculation of wall interference, and (2) Support system effects estimation: The effects on the wall pressure measurements due to the presence of the model support systems will be evaluated.

Lo, C. F.↗
NASA NTRS2004

Jet Noise Reduction

The Acoustics Branch is responsible for reducing noise levels for jet and fan components on aircraft engines. To do this, data must be measured and calibrated accurately to ensure validity of test results. This noise reduction is accomplished by modifications to hardware such as jet nozzles, and by the use of other experimental hardware such as fluidic chevrons, elliptic cores, and fluidic shields. To insure validity of data calibration, a variety of software is used. This software adjusts the sound amplitude and frequency to be consistent with data taken on another day. Both the software and the hardware help make noise reduction possible. work properly. These software programs were designed to make corrections for atmosphere, shear, attenuation, electronic, and background noise. All data can be converted to a one-foot lossless condition, using the proper software corrections, making a reading independent of weather and distance. Also, data can be transformed from model scale to full scale for noise predictions of a real flight. Other programs included calculations of Over All Sound Pressure Level (OASPL), Effective Perceived Noise Level (EPNL). OASPL is the integration of sound with respect to frequency, and EPNL is weighted for a human s response to different sound frequencies and integrated with respect to time. With the proper software correction, data taken in the NATR are useful in determining ways to reduce noise. display any difference between two or more data files. Using this program and graphs of the data, the actual and predicted data can be compared. This software was tested on data collected at the Aero Acoustic Propulsion Laboratory (AAPL) using a variety of window types and overlaps. Similarly, short scripts were written to test each individual program in the software suite for verification. Each graph displays both the original points and the adjusted points connected with lines. During this summer, data points were taken during a live experiment at the AAPL to measure Nozzle Acoustic Test Rig (NATR) background noise levels. Six condenser microphones were placed in strategic locations around the dome and the inlet tunnel to measure different noise sources. From the control room the jet was monitored with the help of video cameras and other sensors. The data points were recorded, reduced, and plotted, and will be used to plan future modifications to the NATR. The primary goal to create data reduction test programs and provide verification was completed. As a result of the internship, I learned C/C++, UNIX/LINUX, Excel, and acoustic data processing methods. I also recorded data at the AAPL, then processed and plotted it. These data would be useful to compare against existing data. In addition, I adjusted software to work on the Mac OSX platform. And I used the available training resources.

Kenny, Patrick↗
NASA NTRS2006

A survey of ground operations tools developed to simulate the pointing of space telescopes and the design for WISE

WISE, the Wide Field Infrared Survey Explorer, is scheduled for launch in June 2010. The mission operations system for WISE requires a software modeling tool to help plan, integrate and simulate all spacecraft pointing and verify that no attitude constraints are violated. In the course of developing the requirements for this tool, an investigation was conducted into the design of similar tools for other space-based telescopes. This paper summarizes the ground software and processes used to plan and validate pointing for a selection of space telescopes; with this information as background, the design for WISE is presented.

ground system↗
NASA NTRS2009

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

Burken, John J.↗
NASA NTRS2009

Applying Formal Methods to NASA Projects: Transition from Research to Practice

NASA project managers attempt to manage risk by relying on mature, well-understood process and technology when designing spacecraft. In the case of crewed systems, the margin for error is even tighter and leads to risk aversion. But as we look to future missions to the Moon and Mars, the complexity of the systems will increase as the spacecraft and crew work together with less reliance on Earth-based support. NASA will be forced to look for new ways to do business. Formal methods technologies can help NASA develop complex but cost effective spacecraft in many domains, including requirements and design, software development and inspection, and verification and validation of vehicle subsystems. To realize these gains, the technologies must be matured and field-tested so that they are proven when needed. During this discussion, current activities used to evaluate FM technologies for Orion spacecraft design will be reviewed. Also, suggestions will be made to demonstrate value to current designers, and mature the technology for eventual use in safety-critical NASA missions.

Othon, Bill↗
NASA NTRS2001

Adjustable Autonomy Testbed

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Malin, Jane T.↗
NASA NTRS2007

System Engineering Strategy for Distributed Multi-Purpose Simulation Architectures

This paper describes the system engineering approach used to develop distributed multi-purpose simulations. The multi-purpose simulation architecture focuses on user needs, operations, flexibility, cost and maintenance. This approach was used to develop an International Space Station (ISS) simulator, which is called the International Space Station Integrated Simulation (ISIS)1. The ISIS runs unmodified ISS flight software, system models, and the astronaut command and control interface in an open system design that allows for rapid integration of multiple ISS models. The initial intent of ISIS was to provide a distributed system that allows access to ISS flight software and models for the creation, test, and validation of crew and ground controller procedures. This capability reduces the cost and scheduling issues associated with utilizing standalone simulators in fixed locations, and facilitates discovering unknowns and errors earlier in the development lifecycle. Since its inception, the flexible architecture of the ISIS has allowed its purpose to evolve to include ground operator system and display training, flight software modification testing, and as a realistic test bed for Exploration automation technology research and development.

Bhula, Dlilpkumar↗
NASA NTRS1991

Validating system-level error recovery for spacecraft

The system-level software onboard a spacecraft is responsible for recovery from communication, thermal, power, and computer-health anomalies that may occur. The recovery must occur without disrupting any critical scientific or engineering activity that is executing at the time of the error. Thus, the error-recovery software may have to execute concurrently with the ongoing acquisition of scientific data or with spacecraft maneuvers. This paper provides a technique by which the rules that constrain the concurrent execution of these processes can be modeled in a graph. An algorithm is described that uses this model to validate that the constraints hold for all concurrent executions of the error-recovery softwave with the softwave that controls the science and engineering events on the spacecraft.

Lutz, Robyn R.↗
NASA NTRS2019

Simulation and Flight Test Environments for the TASAR Traffic Aware Planner

The Traffic Aware Planner (TAP) software is a flight deck decision support tool that enhances the flight crew’s ability to make flight-optimizing route change requests while airborne. The software provides conflict-free, optimized trajectory suggestions during en route flight to produce time- and fuel-savings compared to the current trajectory. The TAP software requires evaluation in an operational environment with real pilot users to validate projected benefits. To this end, a set of developmental test environments have been developed to mature the software and mitigate technical risk prior to entering operational evaluation. The unique attributes of each test environment were leveraged to provide a range of purpose- and case-dependent TAP software tests. This paper describes the elements of a testing environment, discusses several environments of varying fidelity used to test the TAP software, and provides a review of two case studies highlighting the vital role testing played in the TAP software development process.

Barney, Terique L.↗
NASA NTRS2013

Development and Validation of a Computational Model for Predicting the Behavior of Plumes from Large Solid Rocket Motors

Exhaust plumes from large solid rocket motors fired at ATK's Promontory test site carry particulates to high altitudes and typically produce deposits that fall on regions downwind of the test area. As populations and communities near the test facility grow, ATK has become increasingly concerned about the impact of motor testing on those surrounding communities. To assess the potential impact of motor testing on the community and to identify feasible mitigation strategies, it is essential to have a tool capable of predicting plume behavior downrange of the test stand. A software package, called PlumeTracker, has been developed and validated at ATK for this purpose. The code is a point model that offers a time-dependent, physics-based description of plume transport and precipitation. The code can utilize either measured or forecasted weather data to generate plume predictions. Next-Generation Radar (NEXRAD) data and field observations from twenty-three historical motor test fires at Promontory were collected to test the predictive capability of PlumeTracker. Model predictions for plume trajectories and deposition fields were found to correlate well with the collected dataset.

Wells, Jason E.↗
NASA NTRS2012

Simulation Tools Model Icing for Aircraft Design

Here s a simple science experiment to try: Place an unopened bottle of distilled water in your freezer. After 2-3 hours, if the water is pure enough, you will notice that it has not frozen. Carefully pour the water into a bowl with a piece of ice in it. When it strikes the ice, the water will instantly freeze. One of the most basic and commonly known scientific facts is that water freezes at around 32 F. But this is not always the case. Water lacking any impurities for ice crystals to form around can be supercooled to even lower temperatures without freezing. High in the atmosphere, water droplets can achieve this delicate, supercooled state. When a plane flies through clouds containing these droplets, the water can strike the airframe and, like the supercooled water hitting the ice in the experiment above, freeze instantly. The ice buildup alters the aerodynamics of the plane - reducing lift and increasing drag - affecting its performance and presenting a safety issue if the plane can no longer fly effectively. In certain circumstances, ice can form inside aircraft engines, another potential hazard. NASA has long studied ways of detecting and countering atmospheric icing conditions as part of the Agency s efforts to enhance aviation safety. To do this, the Icing Branch at Glenn Research Center utilizes a number of world-class tools, including the Center s Icing Research Tunnel and the NASA 607 icing research aircraft, a "flying laboratory" for studying icing conditions. The branch has also developed a suite of software programs to help aircraft and icing protection system designers understand the behavior of ice accumulation on various surfaces and in various conditions. One of these innovations is the LEWICE ice accretion simulation software. Initially developed in the 1980s (when Glenn was known as Lewis Research Center), LEWICE has become one of the most widely used tools in icing research and aircraft design and certification. LEWICE has been transformed over the years from strictly a research tool to one used routinely by industry and other government agencies. Glenn contractor William Wright has been the architect of this development, supported by a team of researchers investigating icing physics, creating validation data, and ensuring development according to standard software engineering practices. The program provides a virtual simulation environment for determining where water droplets strike an airfoil in flight, what kind of ice would result, and what shape that ice would take. Users can enter geometries for specific, two-dimensional cross sections of an airfoil or other airframe surface and then apply a range of inputs - different droplet sizes, temperatures, airspeeds, and more - to model how ice would build up on the surface in various conditions. The program s versatility, ease of use, and speed - LEWICE can run through complex icing simulations in only a few minutes - have contributed to it becoming a popular resource in the aviation industry.

Source record↗
NASA NTRSDate not supplied

New Tools for Automating Arcjet Sample Recession Tracking and Analysis

Arcjet Computer Vision (arcjetCV) has been significantly upgraded to enhance accuracy and performance in tracking material recession and shock-material standoff in test videos. These improvements include integrating new machine learning models, developing a specialized edge detection class, and incorporating a more comprehensive training dataset. These upgrades have refined the software’s ability to automate time-resolved recession tracking, making it more precise and reliable for analyzing complex physical processes. In parallel, a new tool called STARscan (Spatial Targeting and Alignment Rig for Scanning) is being developed to capture detailed 3D surface data before and after testing. By comparing these pre- and post-test scans with arcjetCV’s automated video analysis results, users can achieve a more comprehensive assessment of material recession. This method enables cross-validation of results, improving confidence in the analysis of tested materials. The expanded capabilities of arcjetCV have been successfully demonstrated on videos from various facilities, including the NASA Ames arcjets, UIUC’s PlasmatronX, and the VKI Plasmatron. It has been adopted as a new standard for in-situ recession tracking by the Mars Sample Return Project and Orion. ArcjetCV’s improved efficiency and accuracy are critical for reducing testing uncertainties and validating heatshield material performance under extreme conditions. The software’s user-friendly graphical interface ensures ease of use, enabling seamless processing and precise analysis of arcjet videos, providing deeper insights into material behavior in hypersonic environments. ArcjetCV is now available on both PyPI and Conda, allowing easy installation via "pip install arcjetCV" or through the Conda package manager, ensuring broad accessibility and streamlined deployment for users across various platforms.

Ablation↗
NASA NTRSDate not supplied

Simulated Ice Shapes on the High Lift Common Research Model Using LEWICE3D

Computational icing tools consist of predicting two distinct problems, the dry air aerodynamics around the iced or uniced vehicle and the accretion of ice due to inclement weather. A desire exists to advance these tools such that they can be reliably used earlier in the design process to limit the need for more costly flight and wind tunnel testing. To achieve these goals the computational tools need to be benchmarked and validated against high quality experimental data sets to raise the software’s Technology Readiness Level. An ongoing collaborative effort between NASA and Boeing Commercial Airplanes is focused on obtaining this required experimental data and subsequently benchmarking and/or validating the tools that predict the aerodynamics around the iced and uniced vehicle. Currently the scope of this effort is focused on the usage of simulated ice shapes to be representative of the iced vehicle. This presentation discusses the generation of those simulated ice shapes.

Icing↗
NASA NTRS2002

LEWICE 2.2 Capabilities and Thermal Validation

A computational model of bleed air anti-icing and electrothermal de-icing have been added to the LEWICE 2.0 software by integrating the capabilities of two previous programs, ANTICE and LEWICE/ Thermal. This combined model has been released as LEWICE version 2.2. Several advancements have also been added to the previous capabilities of each module. This report will present the capabilities of the software package and provide results for both bleed air and electrothermal cases. A comprehensive validation effort has also been performed to compare the predictions to an existing electrothermal database. A quantitative comparison shows that for deicing cases, the average difference is 9.4 F (26%) compared to 3 F for the experimental data while for evaporative cases the average difference is 2 F (32%) compared to an experimental error of 4 F.

Wright, William B.↗
NASA NTRS2013

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.↗
NASA NTRS2012

Spacecraft Avionics Software Development Then and Now: Different but the Same

NASA has always been in the business of balancing new technologies and techniques to achieve human space travel objectives. NASA s historic Software Production Facility (SPF) was developed to serve complex avionics software solutions during an era dominated by mainframes, tape drives, and lower level programming languages. These systems have proven themselves resilient enough to serve the Shuttle Orbiter Avionics life cycle for decades. The SPF and its predecessor the Software Development Lab (SDL) at NASA s Johnson Space Center (JSC) hosted flight software (FSW) engineering, development, simulation, and test. It was active from the beginning of Shuttle Orbiter development in 1972 through the end of the shuttle program in the summer of 2011 almost 40 years. NASA s Kedalion engineering analysis lab is on the forefront of validating and using many contemporary avionics HW/SW development and integration techniques, which represent new paradigms to NASA s heritage culture in avionics software engineering. Kedalion has validated many of the Orion project s HW/SW engineering techniques borrowed from the adjacent commercial aircraft avionics environment, inserting new techniques and skills into the Multi-Purpose Crew Vehicle (MPCV) Orion program. Using contemporary agile techniques, COTS products, early rapid prototyping, in-house expertise and tools, and customer collaboration, NASA has adopted a cost effective paradigm that is currently serving Orion effectively. This paper will explore and contrast differences in technology employed over the years of NASA s space program, due largely to technological advances in hardware and software systems, while acknowledging that the basic software engineering and integration paradigms share many similarities.

Mangieri, Mark L.↗
DOE OSTI2025

Fragme∩t: An Open‐Source Framework for Multiscale Quantum Chemistry Based on Fragmentation

Fragment-based quantum chemistry offers a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations, by partitioning a large calculation into smaller subsystems then considering the many-body interactions between them. Variants of this approach have been used to parameterize classical force fields and machine learning potentials, applications that benefit from interoperability between quantum chemistry codes. However, there is a dearth of software that provides interoperability yet is purpose-built to handle the combinatorial complexity of fragment-based calculations. To fill this void we introduce “Fragme∩t”, an open-source software application that provides a tool for community validation of fragment-based methods, a platform for developing new approximations, and a framework for analyzing many-body interactions. Fragme∩t includes algorithms for automatic fragment generation and structure modification, and for distance- and energy-based screening of the requisite subsystems. Checkpointing, database management, and parallelization are handled internally and results are archived in a portable database. Interfaces to various quantum chemistry engines are easy to write and exist already for Q-Chem, PySCF, xTB, Orca, CP2K, MRCC, Psi4, NWChem, GAMESS, and MOPAC. Applications reported here demonstrate parallel efficiencies around 96% on more than 1000 processors but also showcase that the code can handle large-scale protein fragmentation using only workstation hardware, all with a codebase that is designed to be usable by non-experts. Fragme∩t conforms to modern software engineering best practices and is built upon well established technologies including Python, SQLite, and Ray. The source code is available under the Apache 2.0 license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗