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At least 145 records · Page 8

Handling Qualities of Large Flexible Aircraft

The effects on handling qualities of elastic modes interaction with the rigid body dynamics of a large flexible aircraft are studied by a mathematical computer simulation. An analytical method to predict the pilot ratings when there is a severe modes interactions is developed. This is done by extending the optimal control model of the human pilot response to include the mode decomposition mechanism into the model. The handling qualities are determined for a longitudinal tracking task using a large flexible aircraft with parametric variations in the undamped natural frequencies of the two lowest frequency, symmetric elastic modes made to induce varying amounts of mode interaction.

Poopaka, S.↗

Simulated Fuel Usage for Drag Compensated Spacecraft in Low Earth Orbit

Atmospheric drag causes the greatest uncertainty in the spacecraft flight dynamics equation for spacecraft in Low Earth Orbit (LEO). The continuously varying atmospheric density levels require increased spacecraft tracking to accurately predict spacecraft location. In addition, periodic propulsive maneuvers must be designed and performed to counteract the effects of drag on the spacecraft orbit. If atmospheric drag effects can be continuously and autonomously counteracted through the use of a drag-free control system, they will essentially be eliminated from the spacecraft flight dynamics equation. The main perturbations on the spacecraft will then be those due to the Earth s gravitational field, which are easily predicted. Although theoretically beneficial from a flight dynamics perspective, the costs associated with drag-free control must be determined and weighed against those benefits before the feasibility of drag-free control of spacecraft in LEO can be determined. Through the use of a MATLAEV Satellite Tool Kit simulation, this paper attempts to quantify one such cost associated with drag-free control: the amount of fuel needed for continuous drag compensation as measured by cumulative orbital velocity changes, or AV. This AV cost can then be compared to the fuel required for more traditional, periodic orbit raising maneuvers of every two to four weeks. The simulation considers various sized spacecraft, as measured by the spacecraft ballistic coefficient, in circular orbits of various altitudes and inclinations. The time between orbit raising maneuvers is allowed to decrease until it approaches near continuous. In this manner, the trend in AV cost can be seen as drag compensation moves from periodic to near continuous.

Fleck, Melissa E.↗

Artificial neural networks and approximate reasoning for intelligent control in space

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Berenji, Hamid R.↗

Space Shuttle Ascent Flight Design Process: Evolution and Lessons Learned

The Space Shuttle Ascent Flight Design team is responsible for defining a launch to orbit trajectory profile that satisfies all programmatic mission objectives and defines the ground and onboard reconfiguration requirements for this high-speed and demanding flight phase. This design, verification and reconfiguration process ensures that all applicable mission scenarios are enveloped within integrated vehicle and spacecraft certification constraints and criteria, and includes the design of the nominal ascent profile and trajectory profiles for both uphill and ground-to-ground aborts. The team also develops a wide array of associated training, avionics flight software verification, onboard crew and operations facility products. These key ground and onboard products provide the ultimate users and operators the necessary insight and situational awareness for trajectory dynamics, performance and event sequences, abort mode boundaries and moding, flight performance and impact predictions for launch vehicle stages for use in range safety, and flight software performance. These products also provide the necessary insight to or reconfiguration of communications and tracking systems, launch collision avoidance requirements, and day of launch crew targeting and onboard guidance, navigation and flight control updates that incorporate the final vehicle configuration and environment conditions for the mission. Over the course of the Space Shuttle Program, ascent trajectory design and mission planning has evolved in order to improve program flexibility and reduce cost, while maintaining outstanding data quality. Along the way, the team has implemented innovative solutions and technologies in order to overcome significant challenges. A number of these solutions may have applicability to future human spaceflight programs.

Picka, Bret A.↗

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗

Modeling Self-Pressurization and Spray Bar Pressure Control of a Cryogenic Storage Tank in Normal Gravity

This paper presents Computational Fluid Dynamics (CFD) models for simulating self-pressurization and spray bar cooling processes in a large-scale liquid hydrogen storage tank under normal gravity. The self-pressurization model utilizes the kinetics-based Schrage equation with the Volume-Of-Fluid (VOF) model to account for the evaporative and condensing interfacial mass fluxes. It uses a laminar approach to model natural convection and compares the pressures and temperatures predicted by the CFD model with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) self-pressurization experiment. Additionally, the predicted interfacial mass flux is presented. A CFD model for simulating pressure control using a spray bar is also presented. An Eulerian-Lagrangian approach models the interactions between the discrete droplets and the continuous ullage phase. The spray model is coupled with the VOF model by tracking particles in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. The T-sat model is used to calculate the droplet-ullage heat and mass transfer. In this model, droplets warm up to the saturation temperature corresponding to the ullage vapor pressure thereafter evaporating while remaining at the saturation temperature. The tank pressure, vapor, and liquid temperature evolutions are validated against data from the MHTB spray bar mixing experiment.

Self-Pressurization↗

Human transfer functions used to predict system performance parameters

Automatic, parameter-tracking, model-matching technique compares the responses of a human operator with those of an analog computer model of a human operator to predict and analyze the performance of mechanical or electromechanical systems prior to construction. Transfer functions represent the input-output relation of an operator controlling a closed-loop system.

Source record↗

Triple flame structure and diffusion flame stabilization

The stabilization of diffusion flames is studied using asymptotic techniques and numerical tools. The configuration studied corresponds to parallel streams of cold oxidizer and fuel initially separated by a splitter plate. It is shown that stabilization of a diffusion flame may only occur in this situation by two processes. First, the flame may be stabilized behind the flame holder in the wake of the splitter plate. For this case, numerical simulations confirm scalings previously predicted by asymptotic analysis. Second, the flame may be lifted. In this case a triple flame is found at longer distances downstream of the flame holder. The structure and propagation speed of this flame are studied by using an actively controlled numerical technique in which the triple flame is tracked in its own reference frame. It is then possible to investigate the triple flame structure and velocity. It is shown, as suggested from asymptotic analysis, that heat release may induce displacement speeds of the triple flame larger than the laminar flame speed corresponding to the stoichiometric conditions prevailing in the mixture approaching the triple flame. In addition to studying the characteristics of triple flames in a uniform flow, their resistance to turbulence is investigated by subjecting triple flames to different vortical configurations.

Veynante, D.↗

A Real-Time Position-Locating Algorithm for CCD-Based Sunspot Tracking

NASA Marshall Space Flight Center's (MSFC) EXperimental Vector Magnetograph (EXVM) polarimeter measures the sun's vector magnetic field. These measurements are taken to improve understanding of the sun's magnetic field in the hopes to better predict solar flares. Part of the procedure for the EXVM requires image motion stabilization over a period of a few minutes. A high speed tracker can be used to reduce image motion produced by wind loading on the EXVM, fluctuations in the atmosphere and other vibrations. The tracker consists of two elements, an image motion detector and a control system. The image motion detector determines the image movement from one frame to the next and sends an error signal to the control system. For the ground based application to reduce image motion due to atmospheric fluctuations requires an error determination at the rate of at least 100 hz. It would be desirable to have an error determination rate of 1 kHz to assure that higher rate image motion is reduced and to increase the control system stability. Two algorithms are presented that are typically used for tracking. These algorithms are examined for their applicability for tracking sunspots, specifically their accuracy if only one column and one row of CCD pixels are used. To examine the accuracy of this method two techniques are used. One involves moving a sunspot image a known distance with computer software, then applying the particular algorithm to see how accurately it determines this movement. The second technique involves using a rate table to control the object motion, then applying the algorithms to see how accurately each determines the actual motion. Results from these two techniques are presented.

Taylor, Jaime R.↗

Increased ephemeris accuracy using attitude-dependent aerodynamic force coefficients for inertially stabilized spacecraft

The FREEMAC program used to generate the aerodynamic coefficients, as well as associated routines that allow the results to be used in other software is described. These capabilities are applied in two numerical examples to the short-term orbit prediction of the Gamma Ray Observatory (GRO) and Hubble Space Telescope (HST) spacecraft. Predictions using attitude-dependent aerodynamic coefficients were made on a modified version of the PC-based Ephemeris Generation Program (EPHGEN) and were compared to definitive orbit solutions obtained from actual tracking data. The numerical results show improvement in the predicted semi-major axis and along-track positions that would seem to be worth the added computational effort. Finally, other orbit and attitude analysis applications are noted that could profit from using FREEMAC-calculated aerodynamic coefficients, including orbital lifetime studies, orbit determination methods, attitude dynamics simulators, and spacecraft control system component sizing.

Folta, David C.↗

Determination of atmospheric density using a space-launched projectile

A method is proposed that provides advance information about unpredictable atmospheric density dispersions that must be accommodated during random operations of aeroassisted-orbital-transfer vehicles (AOTVs). The principal feature is that a test or 'scout' projectile precedes the AOTV through the same region of the atmosphere as that of the predicted transatmospheric flight trajectory. The atmospheric density structure is determined from the vehicle's aerodynamic deceleration characteristics by on-board or ground-based tracking equipment. The time lag between passage of the projectile and the AOTV can be adjusted to only that time necessary to implement required guidance, navigation, and control (GN&C) corrections. The various strategies available to control the projectile's flight characteristics are analyzed in detail. The results are correlated with aerothermodynamic heating and materials requirements to ensure the survival of the projectile and, consequently, the capability of the AOTV to navigate a variable upper atmosphere within specified limits.

Menees, G. P.↗

Solar Power Satellite antenna phase control system hardware simulation, phase 4. Volume 3: SOLARSIM users manual

Documentation of the interactive software package designed to predict the effect of certain electrical and mechanical imperfections on the performance of the SPS system is presented. The capabilities of the SOLARSIM program to quantify the spacetenna performance parameter values are described. The SOLARSIM package can compute the RMS pointing error, title effects, MPTX code tracking loop performance, MPTX carrier tracking loop performance, averaged power pattern, and the power transfer efficiency.

Lindsey, W. C.↗

Verification of the Solar Dynamics Observatory High Gain Antenna Pointing Algorithm Using Flight Data

The Solar Dynamics Observatory (SDO) is a NASA spacecraft designed to study the Sun. It was launched on February 11, 2010 into a geosynchronous orbit, and uses a suite of attitude sensors and actuators to finely point the spacecraft at the Sun. SDO has three science instruments: the Atmospheric Imaging Assembly (AIA), the Helioseismic and Magnetic Imager (HMI), and the Extreme Ultraviolet Variability Experiment (EVE). SDO uses two High Gain Antennas (HGAs) to send science data to a dedicated ground station in White Sands, New Mexico. In order to meet the science data capture budget, the HGAs must be able to transmit data to the ground for a very large percentage of the time. Each HGA is a dual-axis antenna driven by stepper motors. Both antennas transmit data at all times, but only a single antenna is required in order to meet the transmission rate requirement. For portions of the year, one antenna or the other has an unobstructed view of the White Sands ground station. During other periods, however, the view from both antennas to the Earth is blocked for different portions of the day. During these times of blockage, the two HGAs take turns pointing to White Sands, with the other antenna pointing out to space. The HGAs handover White Sands transmission responsibilities to the unblocked antenna. There are two handover seasons per year, each lasting about 72 days, where the antennas hand off control every twelve hours. The non-tracking antenna slews back to the ground station by following a ground commanded trajectory and arrives approximately 5 minutes before the formerly tracking antenna slews away to point out into space. The SDO Attitude Control System (ACS) runs at 5 Hz, and the HGA Gimbal Control Electronics (GCE) run at 200 Hz. There are 40 opportunities for the gimbals to step each ACS cycle, with a hardware limitation of no more than one step every three GCE cycles. The ACS calculates the desired gimbal motion for tracking the ground station or for slewing, and sends the command to the GCE at 5 Hz. This command contains the number of gimbals steps for that ACS cycle, the direction of motion, the spacing of the steps, and the delay before taking the first step. The AIA and HMI instruments are sensitive to spacecraft jitter. Pre-flight analysis showed that jitter from the motion of the HGAs was a cause of concern. Three jitter mitigation techniques were developed to overcome the effects of jitter from different sources. The first method is the random step delay, which avoids gimbal steps hitting a cadence on a jitter-critical mode by pseudo-randomly delaying the first gimbal step in an ACS cycle. The second method of jitter mitigation is stagger stepping, which forbids the two antennas from taking steps during the same ACS cycle in order to avoid constructively adding jitter from two antennas. The third method is the inclusion of an instrument No Step Request (NSR), which allows the instruments to request a stoppage in gimbal stepping during the times when they are taking images. During the commissioning phase of the mission, a jitter test was performed onboard the spacecraft. Various sources of jitter, such as the reaction wheels, the High Gain Antenna motors, and the motion of the instrument filter wheels, were examined to determine the level of their effect on the instruments. During the HGA portion of the test, the jitter amplitudes from the single step of a gimbal were examined, as well as the amplitudes due to the execution of various gimbal rates. These jitter levels are compared with the gimbal jitter allocations for each instrument. Additionally, the jitter test provided insight into a readback delay that exists with the GCE. Pre-flight analysis suggested that gimbal steps scheduled to occur during the later portion of an ACS cycle would not be read during that cycle, resulting in a delay in the telemetered current gimbal position. Flight data from the jitter test confirmed this expectation. Analysis is presentehat shows the readback delay does not have a negative impact on gimbal control. The decision was made to consider implementing two of the jitter mitigation techniques on board the spacecraft: stagger stepping and the NSR. Flight data from two sets of handovers, one set without jitter mitigation and the other with mitigation enabled, were examined. The trajectory of the predicted handover was compared with the measured trajectory for the two cases, showing that tracking was not negatively impacted with the addition of the jitter mitigation techniques. Additionally, the individual gimbal steps were examined, and it was confirmed that the stagger stepping and NSRs worked as designed. An Image Quality Test was performed to determine the amount of cumulative jitter from the reaction wheels, HGAs, and instruments during various combinations of typical operations. In this paper, the flight results are examined from a test where the HGAs are following the path of a nominal handover with stagger stepping on and HMI NSRs enabled. In this case, the reaction wheels are moving at low speed and the instruments are taking pictures in their standard sequence. The flight data shows the level of jitter that the instruments see when their shutters are open. The HGA-induced jitter is well within the jitter requirement when the stagger step and NSR mitigation options are enabled. The SDO HGA pointing algorithm was designed to achieve nominal antenna pointing at the ground station, perform slews during handover season, and provide three HGA-induced jitter mitigation options without compromising pointing objectives. During the commissioning phase, flight data sets were collected to verify the HGA pointing algorithm and demonstrate its jitter mitigation capabilities.

Bourkland, Kristin L.↗

Laser tracking for vertical control

The Global Laser Tracking Network has provided LAGEOS ranging data of high accuracy since the first MERIT campaign in late 1983 and we can now resolve centimeter-level three dimensional positions of participating observatories at monthly intervals. In this analysis, the station height estimates have been considered separately from the horizontal components, and can be determined by the strongest stations with a formal standard error of 2 mm using eight years of continuous observations. The rate of change in the vertical can be resolved to a few mm/year, which is at the expected level of several geophysical effects. In comparing the behavior of the stations to that predicted by recent models of post-glacial rebound, we find no correlation in this very small effect. Particular attention must be applied to data and survey quality control when measuring the vertical component, and the survey observations are critical components of the geodynamic results. Seasonal patterns are observed in the heights of most stations, and the possibility of secular motion at the level of several millimeters per year cannot be excluded. Any such motion must be considered in the interpretation of horizontal inter-site measurements, and can help to identify mechanisms which can cause variations which occur linearly with time, seasonally, or abruptly.

Dunn, Peter↗

Dynamic response for thermal control and measurement and fast radiation thermometry

A preliminary evaluation was made by ORNL of a two-color ratio pyrometer (TCRP) for temperature control in the Modular Electromagnetic Levitation (MEL) experiment. A discussion was presented by Eric Spjut at the 1987 NASA Non-Contact Temperature Measurement Workshop (NASA Conf. Publ. 2503, pp. 182-213) in which he described the non-linear characteristics of the time response of TCPs. Researchers replicated his model and results and note that the non-linear response behavior is minimized for small temperature steps at high temperatures. They then used the predicted response in a model for a proportional or integral feedback controller and predicted the control characteristics for heating and cooling a 5-mm diameter sphere of niobium at high (1500 to 2750 K) temperatures. The analysis shows that for a slow (25-ms) time response for a commercial RCRP, overshoots of several hundred kelvins will result from a 100-K decrease in the setpoint, and temperature tracking errors of 14 to 45 K will occur for control temperature ramps of 1000K/s. For a fast (greater than 0.1 ms) time response, the overshoot and ramp response errors are largely eliminated.

Shepard, R. L.↗

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗

NASA Deep Space Network operating control

The primary function of the Deep Space Network (DSN) is to provide effective and reliable tracking and data acquisition for planetary and interplanetary space flight missions. This involves providing data to flight project mission operations, accepting commands from mission operations and transmitting the commands to stations and spacecraft, and providing a record of telemetry and command data to mission operations. Also included are network performance monitoring, the generation of predictions for antenna pointing and signal acquisition, network scheduling, and network validation tests. Descriptions are given of the three facilities and six systems of the DSN. Also described are interfaces, automation and standardized procedures, and discrepancy reporting. It is pointed out that the greatest challenge facing the DSN is the implementation of NASA's Network Consolidation Program, which is scheduled to be completed in 1986. The objectives of this program are enumerated.

Weisman, W. D.↗