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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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NASA NTRS2023

NASA's Center Innovation Fund (CIF) Internal Research and Development (IRAD) Handling Qualities Study on the Mikrolar Motion Platform Test Report

In order to support the National Aeronautics and Space Administration’s (NASA) Extravehicular Activity and Surface Mobility Program (EHP), system engineers, designers, and researchers embarked on a yearlong challenge to develop a new lunar rover-based motion table simulator to study handling qualities of lunar rovers in the lunar South Pole region, support development research for any lunar rover vendor, and provide a lunar training capability for future lunar/planetary astronauts. In 1989, the United Kingdom’s Royal Air Force Institute of Aviation Medicine (RAF-IAM) stated that motion platforms are the only simulation devices capable of fully stimulating the body motion sensors. They confirmed that motion platforms can impart accelerations to the whole body and therefore exercise the automatic motion feedback-loop that operators are used to. With both visual and motion cues handling the vehicle becomes more realistic. Strachan (2019) con-firms motion cueing from a well set-up motion platform has been found to be important especially in conditions such as night or reduced visibility where motion cues may be more relied upon

Motion Table↗
NASA NTRS1988

Crew activities, science, and hazards of manned missions to Mars

The crew scientific and nonscientific activities that will occur at each stage of a mission to Mars are examined. Crew activities during the interplanetary flight phase will include simulations, maintenance and monitoring, communications, upgrading procedures and operations, solar activity monitoring, cross-training and sharpening of skills, physical conditioning, and free-time activities. Scientific activities will address human physiology, human psychology, sociology, astronomy, space environment effects, manufacturing, and space agriculture. Crew activities on the Martian surface will include exploration, construction, manufacturing, food production, maintenance and training, and free time. Studies of Martian geology and atmosphere, of the life forms that may exist there, and of the Martian moons will occur on the planet's surface. Crew activities and scientific studies that will occur in Mars orbit, and the hazards relevant to each stage of the mission, are also addressed.

Clark, Benton C.↗
NASA NTRS1990

Reach performance while wearing the Space Shuttle launch and entry suit during exposure to launch accelerations

A crew of four veteran astronaut/pilots were subjected to sustained linear accelerations of up to 3G(x) in order to quantify crew reach performance while wearing the currently used Launch and Entry Suit (LES). Photogrammetric techniques were used to quantify magnitudes of reach in any direction while subjects rode a centrifuge. Subjects exhibited small changes of reach capability in the +x (forward) direction which ranged from an improvement of 2.04 cm to a decrease of 14.4 cm while reach performance in the +z (overhead) direction was improved in three of four subjects, indicating that any task which could be accomplished under exposure to 1G(x) could definitely be done at 3G(x). The data from this experiment demonstrated that Shuttle crews in training can expect to maintain all of the overhead reach capability evident in good simulator runs and suffer only moderate degradation in the forward reach performance during the launch phase of an actual Shuttle mission.

Bagian, James P.↗
NASA NTRS1994

Neural net controller for inlet pressure control of rocket engine testing

Many dynamic systems operate in select operating regions, each exhibiting characteristic modes of behavior. It is traditional to employ standard adjustable gain proportional-integral-derivative (PID) loops in such systems where no apriori model information is available. However, for controlling inlet pressure for rocket engine testing, problems in fine tuning, disturbance accommodation, and control gains for new profile operating regions (for research and development) are typically encountered. Because of the capability of capturing I/O peculiarities, using NETS, a back propagation trained neural network is specified. For select operating regions, the neural network controller is simulated to be as robust as the PID controller. For a comparative analysis, the higher order moment neural array (HOMNA) method is used to specify a second neural controller by extracting critical exemplars from the I/O data set. Furthermore, using the critical exemplars from the HOMNA method, a third neural controller is developed using NETS back propagation algorithm. All controllers are benchmarked against each other.

Trevino, Luis C.↗
NASA NTRS2002

Prediction of Aerodynamic Coefficients using Neural Networks for Sparse Data

Basic aerodynamic coefficients are modeled as functions of angles of attack and sideslip with vehicle lateral symmetry and compressibility effects. Most of the aerodynamic parameters can be well-fitted using polynomial functions. In this paper a fast, reliable way of predicting aerodynamic coefficients is produced using a neural network. The training data for the neural network is derived from wind tunnel test and numerical simulations. The coefficients of lift, drag, pitching moment are expressed as a function of alpha (angle of attack) and Mach number. The results produced from preliminary neural network analysis are very good.

Rajkumar, T.↗
NASA NTRS2002

Prediction of Aerodynamic Coefficients for Wind Tunnel Data using a Genetic Algorithm Optimized Neural Network

A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.

Rajkumar, T.↗
NASA NTRS2004

Carbon Dioxide Dispersion in the Combustion Integrated Rack Simulated Numerically

When discharged into an International Space Station (ISS) payload rack, a carbon dioxide (CO2) portable fire extinguisher (PFE) must extinguish a fire by decreasing the oxygen in the rack by 50 percent within 60 sec. The length of time needed for this oxygen reduction throughout the rack and the length of time that the CO2 concentration remains high enough to prevent the fire from reigniting is important when determining the effectiveness of the response and postfire procedures. Furthermore, in the absence of gravity, the local flow velocity can make the difference between a fire that spreads rapidly and one that self-extinguishes after ignition. A numerical simulation of the discharge of CO2 from PFE into the Combustion Integrated Rack (CIR) in microgravity was performed to obtain the local velocity and CO2 concentration. The complicated flow field around the PFE nozzle exits was modeled by sources of equivalent mass and momentum flux at a location downstream of the nozzle. The time for the concentration of CO2 to reach a level that would extinguish a fire anywhere in the rack was determined using the Fire Dynamics Simulator (FDS), a computational fluid dynamics code developed by the National Institute of Standards and Technology specifically to evaluate the development of a fire and smoke transport. The simulation shows that CO2, as well as any smoke and combustion gases produced by a fire, would be discharged into the ISS cabin through the resource utility panel at the bottom of the rack. These simulations will be validated by comparing the results with velocity and CO2 concentration measurements obtained during the fire suppression system verification tests conducted on the CIR in March 2003. Once these numerical simulations are validated, portions of the ISS labs and living areas will be modeled to determine the local flow conditions before, during, and after a fire event. These simulations can yield specific information about how long it takes for smoke and combustion gases produced by a fire to reach a detector location, how large the fire would be when the detector alarms, and the behavior of the fire until it has been extinguished. This new capability could then be used to optimize the location of fire detectors and fire-suppression ports as well as to evaluate the effectiveness of fire suppressants and response strategies. Numerical data collected from these simulations could also be used to develop a virtual reality fire event for crew training and fire safety awareness. This work is funded by NASA's Bioastronautics Initiative, which has the objective of ensuring and enhancing the health, safety, and performance of humans in space. As part of this initiative, the Microgravity Combustion Science Branch at the NASA Glenn Research Center is conducting spacecraft fire safety research to significantly improve fire safety on inhabited spacecraft.

Wu, Ming-Shin↗
NASA NTRS2006

Progress Toward a Format Standard for Flight Dynamics Models

In the beginning, there was FORTRAN, and it was... not so good. But it was universal, and all flight simulator equations of motion were coded with it. Then came ACSL, C, Ada, C++, C#, Java, FORTRAN-90, Matlab/Simulink, and a number of other programming languages. Since the halcyon punch card days of 1968, models of aircraft flight dynamics have proliferated in training devices, desktop engineering and development computers, and control design textbooks. With the rise of industry teaming and increased reliance on simulation for procurement decisions, aircraft and missile simulation models are created, updated, and exchanged with increasing frequency. However, there is no real lingua franca to facilitate the exchange of models from one simulation user to another. The current state-of-the-art is such that several staff-months if not staff-years are required to 'rehost' each release of a flight dynamics model from one simulation environment to another one. If a standard data package or exchange format were to be universally adopted, the cost and time of sharing and updating aerodynamics, control laws, mass and inertia, and other flight dynamic components of the equations of motion of an aircraft or spacecraft simulation could be drastically reduced. A 2002 paper estimated over $ 6 million in savings could be realized for one military aircraft type alone. This paper describes the efforts of the American Institute of Aeronautics and Astronautics (AIAA) to develop a standard flight dynamic model exchange standard based on XML and HDF-5 data formats.

Jackson, E. Bruce↗
NASA NTRS2005

Human Factors Assessment of Respiratory Support Pack (RSP) Cue Card

The Respiratory Support Pack (RSP) is a medical pack onboard the International Space Station (ISS) that contains much of the necessary equipment for providing aid to a conscious or unconscious crewmember in respiratory distress. Inside the RSP lid pocket is a 5.5 by 11 inch paper cue card, which is used by a Crew Medical Officer as the procedure to set up the equipment and deliver oxygen to a crewmember. In training, crewmembers expressed concerns about the readability and usability of the cue card; consequently, updating the cue card was prioritized as an activity to be completed prior to Space Shuttle return-to-flight. The Usability Testing and Analysis Facility at the Johnson Space Center evaluated the current layout of the cue card, and proposed several new cue card designs based on human factors principals. A series of three studies were performed in order to experimentally compare performance with each of the cue card designs. Nonmedically trained personnel used either a redesigned RSP cue card, or the original card to simulate resuscitation (using a mannequin along with the hardware). Time to completion, errors and subjective ratings were recorded. The addition of pictures, colors, borders, and simplification of the flow of information (making minimal changes to the actual procedure content) elicited great benefits during testing. Time to complete RSP procedures was reduced by as much as three minutes with the final cue card design. Detailed results from these studies, as well as general guidelines for cue card design will be discussed.

Whitmore, Mihriban↗
NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.

Jaehyun Cho↗
NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.

Jaehyun Cho↗
NASA NTRSDate not supplied

NASA Commercial Crew Program and Medical Operational Challenges

This abstract is submitted as part of the USSPACECOM Command Surgeon’s panel demonstrating the medical capabilities and challenges involved in human space flight support operations. BACKGROUND: NASA embarked on the Commercial Crew Program to launch astronauts into low-earth orbit from US soil and dock with the International Space Station (ISS). The eventual industry providers selected were SpaceX (SpX) and Boeing. These commercial transportation systems are vital to ensure crew availability on ISS for research and discovery. OVERVIEW: NASA/SpaceX Demo-2 (DM2) mission launched from the Kennedy Space Center in 2020 as the historic first crewed test-flight of the Crew Dragon spacecraft with two NASA Astronauts onboard. DM2 represented the first flight in 9-years from US soil since STS-135 in 2011. The 63-day mission ended with splashdown in the Gulf of Mexico, the first US water recovery in 45-years since Apollo-Soyuz. Validation of system hardware and operations allowed four-person crews to launch on subsequently missions (Crew-1, Crew-2, Crew-3, Crew-4, Crew-5 to date), which included International Partner crewmembers. DISCUSSION: A multitude of operational, training, medical, and technical issues needed to be addressed between NASA Medical Operations, the commercial provider SpaceX, and the Department of Defense. These included Flight rule development, occupant protection, pressurized suit testing, communication plans during mission phases, and emergency simulations for supporting Flight Surgeons and Biomedical Engineers. In providing crew experience with expected launch and entry G-force profile, Centrifuge training was established. Preventive health measures via the Health Stabilization Program were especially vital during the global COVID-19 pandemic. Unique aspects arise for SpX Dragon parachute splashdown and shipboard recovery operations in the Atlantic Ocean and Gulf of Mexico. The new Commercial Crew Program is indeed a wonderfully challenging and exciting era for human spaceflight.

Joseph Dervay↗
NASA NTRSDate not supplied

NASA Commercial Crew Program and Medical Operational Challenges

BACKGROUND: NASA embarked on the Commercial Crew Program to launch astronauts into low-earth orbit from US soil and dock with the International Space Station (ISS). The eventual industry providers selected were SpaceX (SpX) and Boeing. These commercial transportation systems are vital to ensure crew availability on ISS for research and discovery. OVERVIEW: NASA/SpaceX Demo-2 (DM2) mission launched from the Kennedy Space Center in 2020 as the historic first crewed test-flight of the Crew Dragon spacecraft with two NASA Astronauts onboard. DM2 represented the first flight in 9-years from US soil since STS-135 in 2011. The 63-day mission ended with splashdown in the Gulf of Mexico, the first US water recovery in 45-years since Apollo-Soyuz. Validation of system hardware and operations allowed four-person crews to launch on subsequently missions (Crew-1, Crew-2, Crew-3, Crew-4, Crew-5 to date), which included International Partner crewmembers. DISCUSSION: A multitude of operational, training, medical, and technical issues needed to be addressed between NASA Medical Operations, the commercial provider SpaceX, and the Department of Defense. These included Flight rule development, occupant protection, pressurized suit testing, communication plans during mission phases, and emergency simulations for supporting Flight Surgeons and Biomedical Engineers. In providing crew experience with expected launch and entry G-force profile, Centrifuge training was established. Preventive health measures via the Health Stabilization Program were especially vital during the global COVID-19 pandemic. Unique aspects arise for SpX Dragon parachute splashdown and shipboard recovery operations in the Atlantic Ocean and Gulf of Mexico. The new Commercial Crew Program is indeed a wonderfully challenging and exciting era for human spaceflight.

Joseph P Dervay↗
NASA NTRS2017

Medical Support for ISS Crewmember Training in Star City, Russia

Medical support of spaceflight training operations across international lines is a unique circumstance with potential applications to other aerospace medicine support scenarios. KBRwyle's Star City Medical Support Group (SCMSG) has fulfilled this role since the Mir-Shuttle era, with extensive experience and updates to share with the greater AsMA community. OVERVIEW: The current Soyuz training flow for assigned ISS crewmembers takes place in Star City, Russia. Soyuz training flow involves numerous activities that pose potential physical and occupational risks to crewmembers, including centrifuge runs and pressurized suit simulations at ambient and hypobaric pressures. In addition, Star City is a relatively remote location in a host nation with variable access to reliable, Western-standard medical care. For these reasons, NASA's Human Health & Performance contract allocates full-time physician support to assigned ISS crewmembers training in Star City. The Star City physician also treats minor injuries and illnesses as needed for both long- and short-term NASA support personnel traveling in the area, while working to develop and maintain relationships with local health care resources in the event of more serious medical issues that cannot be treated on-site. The specifics of this unique scope of practice will be discussed. SIGNIFICANCE: ISS crewmembers training in Star City are at potential physical and occupational risk of trauma or dysbarism during nominal Soyuz training flow, requiring medical support from an on-duty aerospace medicine specialist. This support maintains human health and performance by preserving crewmember safety and well-being for mission success; sharing information regarding this operational model may contribute to advances in other areas of international, military, and civilian operational aerospace medicine.

Chough, Natacha↗
NASA NTRS2017

Medical Support for ISS Crewmember Training in Star City, Russia

Medical support of spaceflight training operations across international lines is a unique circumstance with potential applications to other aerospace medicine support scenarios. KBRwyle's Star City Medical Support Group (SCMSG) has fulfilled this role since the Mir-Shuttle era, with extensive experience and updates to share with the greater AsMA community. OVERVIEW: The current Soyuz training flow for assigned ISS crewmembers takes place in Star City, Russia. Soyuz training flow involves numerous activities that pose potential physical and occupational risks to crewmembers, including centrifuge runs and pressurized suit simulations at ambient and hypobaric pressures. In addition, Star City is a relatively remote location in a host nation with variable access to reliable, Western-standard medical care. For these reasons, NASA's Human Health & Performance contract allocates full-time physician support to assigned ISS crewmembers training in Star City. The Star City physician also treats minor injuries and illnesses as needed for both long- and short-term NASA support personnel traveling in the area, while working to develop and maintain relationships with local health care resources in the event of more serious medical issues that cannot be treated on-site. The specifics of this unique scope of practice will be discussed. SIGNIFICANCE: ISS crewmembers training in Star City are at potential physical and occupational risk of trauma or dysbarism during nominal Soyuz training flow, requiring medical support from an on-duty aerospace medicine specialist. This support maintains human health and performance by preserving crewmember safety and well-being for mission success; sharing information regarding this operational model may contribute to advances in other areas of international, military, and civilian operational aerospace medicine.

Chough, Natacha↗
NASA NTRSDate not supplied

Isolator Shock Train Response to Dual-Mode Scramjet Throttling-Like Forcing

Typical dual-mode scramjet designs employ an isolator component situated between the inlet and combustor. The isolator fluidically buffers the inlet from the combustor via the formation of a shock train, an interconnected series of shock-boundary layer interactions. The isolator is required during ramjet-engine operation and at the lower edges of the scramjet operational envelope. In an operational engine, transient behavior imposes fluidic dynamics due to attitude adjustments, combustor throttling, aberrant resonances within the combustor, etc. To accommodate these transients, the shock train adjusts on both temporal and spatial scales. Sufficiently large downstream pressure increases in the combustor play a critical role during unstart, whereby strong compression waves propagate upstream in the isolator to ultimately force the shock train out the inlet, if it cannot stabilize to the pressure increase. This critically reduces the engine mass flow rate, potentially causing a catastrophic reduction in thrust and loss of the vehicle. A nearly instantaneous unstart can, in principle, be predicted by a ratio of the normal shock pressure jump in an inviscid isolator. However, lower-magnitude perturbations, below this bound, also induce unstarts. Understanding the transient behavior inherent in unsteady isolator operation is critical to reducing safety margin in isolator length and refining engine control algorithms to improve engine performance. The Isolator Dynamics Research Lab (IDRL) is a cold-flow, direct-connect isolator facility ideal for assessing the fundamental fluid dynamics of shock trains. The internal flow of a scramjet isolator is modeled using a 2D, symmetric Mach 2.5 nozzle followed by a 695 mm long, 25.4x50.8 mm rectangular isolator test section. A blockage cone on a high-speed ball screw actuator downstream of the isolator is pulsed to simulate the throttling behavior in an operational combustor. Wall flush high-speed static pressure transducers detect the streamwise shock train within the isolator. Time delays between the onset of the throttling and the response motion of the shock train are analyzed to assess the controlling scales and parameters. From this analysis, the response time of the isolator shock train system is found to depend primarily on the isolator back pressure time-rate-of-change but quickly saturates to a maximum propagation speed along the isolator. These results inform dual-mode scramjet engine designers of the critical parameters and limits of an unstart resistant engine.

scramjet↗
NASA NTRS2001

Investigation of the Effectiveness of Dynamic Seat in a Black Hawk Flight Simulation

Low cost alternatives have been sought to provide motion cues in ground-based flight simulators to meet mission objectives. The ability to provide high frequency vibrations makes the dynamic seat attractive to helicopter training applications. Previous studies have found that dynamic seat does enhance the realism of the cockpit and affect pilots' workload. This investigation, conducted under the auspices of the Joint Shipboard Helicopter Integration Process (JSHIP), is using a three degree-of-freedom dynamic seat, i.e., heave, surge, and sway, with limited travels in a research simulator configured as a UH-60 Black Hawk at NASA Ames Research Center. The seat's effectiveness is studied using hover, landing, pirouette, bob-up/bob-down, sidestep, and acceleration/deceleration maneuvers. Seat commands consist of constant vibrations in heave and sway which provide the fundamental vibratory cues. Pilot station accelerations and collective controls provide onset and sustained commands. In addition, transient effects due to translational-lift, collective; and normal acceleration are produced by regulating the magnitude and frequency that depend on the rotor rpm. Results are compared to flight test data and two other ground-based motion systems configurations, i.e., a motion condition with very large motion travels and a motion condition that is comparable with commercial simulator travels. Both subjective and objective data will be analyzed to determine the significance of the motion cueing effect in each system for selected maneuvers.

Chung, William W. Y.↗
NASA NTRSDate not supplied

Algorithmic Detection of Elemental Biosignatures

Machine learning models that classify a sample as indicative or non-indicative of life could play an important role in life-detection missions. Their predictions result from agnostic algorithms and thereby add redundancy to judgements resulting from human expertise. Additionally, their important features can reveal the most informative measurements within the operational constraints of a life-detection mission. The Ladder of Life Detection (Neveu 2018) identifies the need for an understanding of how combinations of multiple biosignatures affect overall confidence. The present work provides a starting point to answer this need, and future work will expand the data types to obtain even more predictive combinations of features. Elemental abundance was chosen as a starting set of features due to its availability in diverse sample types, which are needed to train a generalizable model. A standardized dataset was collected, including 35 non-indicative, e.g., lunar rock, basalt; 19 indicative mixed, e.g., seawater, agricultural soil; 46 indicative non-alive, e.g., coal, chalk; and 10 indicative alive, e.g., biofilm, bacteria. This dataset could be valuable for complementary biosignature research. The samples were standardized to the same limit of detection of a simulated mission scenario. Four classification models were used: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), and Gaussian naïve Bayes (GNB). To obtain feature importances, KNN was run on three principal components of the training data and LR and SVM were run with L1 and L2 regularization. The performances and feature importances of the six model variants on 40:60 train to validation ratios were assessed with Monte Carlo simulations. ROC AUC and mean accuracy scores ranged between 82% - 94%, with sensitivity greater than specificity. For indicative of life predictors, all models had C and Ca as strong and Cl as medium; a majority of models had N, K, and P as medium. For non-indicative of life predictors, all models had Si as strong, and a majority of models had Mg, Al, and Ti as medium. Varied elements were Fe (slightly non-indicative), H (slightly indicative), O (widely varied), Na, Mn, and S. These results serve as a proof of concept and suggest important elemental signals beyond merely the CHNOPS of Earth-based life.

Algorithmic↗